diff --git a/DESCRIPTION b/DESCRIPTION
index 03548227..d8ec696b 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -39,13 +39,13 @@ VignetteBuilder: knitr
 Encoding: UTF-8
 LinkingTo: Rcpp, RcppArmadillo, RcppEigen, RcppProgress
 Depends:
-    Matrix,
     methods,
     stats,
     utils,
     R (>= 3.4)
 Imports:
     circlize,
+    cli,
     cowplot,
     ComplexHeatmap,
     dplyr,
@@ -55,6 +55,7 @@ Imports:
     leidenAlg (>= 1.1.1),
     lifecycle,
     magrittr,
+    Matrix,
     RANN,
     RColorBrewer,
     Rcpp,
diff --git a/NAMESPACE b/NAMESPACE
index 5c634ada..84bd3aaa 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -1,5 +1,6 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method("[",liger)
 S3method("[",ligerDataset)
 S3method("[[",liger)
 S3method(.DollarNames,liger)
@@ -189,7 +190,6 @@ exportClasses(ligerRNADataset)
 exportClasses(ligerSpatialDataset)
 exportMethods("$")
 exportMethods("$<-")
-exportMethods("[")
 exportMethods("cellMeta<-")
 exportMethods("coordinate<-")
 exportMethods("dataset<-")
@@ -234,6 +234,9 @@ exportMethods(scaleUnsharedData)
 exportMethods(show)
 exportMethods(varFeatures)
 exportMethods(varUnsharedFeatures)
+importClassesFrom(Matrix,dgCMatrix)
+importClassesFrom(Matrix,dgTMatrix)
+importClassesFrom(Matrix,dgeMatrix)
 importClassesFrom(S4Vectors,DataFrame)
 importFrom(Matrix,colSums)
 importFrom(Matrix,rowSums)
diff --git a/R/ATAC.R b/R/ATAC.R
index aa609a32..b3867a3e 100644
--- a/R/ATAC.R
+++ b/R/ATAC.R
@@ -50,33 +50,28 @@ imputeKNN <- function(
         knn_k = nNeighbors
 ) {
     .deprecateArgs(list(knn_k = "nNeighbors"), defunct = "scale")
-    # if (!requireNamespace("FNN", quietly = TRUE)) {
-    #     stop("Package \"foreach\" needed for this function to work. ",
-    #          "Please install it by command:\n",
-    #          "install.packages('FNN')",
-    #          call. = FALSE)
-    # }
     if (is.null(getMatrix(object, "H.norm")))
-        stop("Aligned factor loading has to be available for imputation. ",
-             "Please run `quantileNorm()` in advance.")
-
-    if (length(reference) > 1) {
-        stop("Can only have ONE reference dataset")
-    }
-    reference <- .checkUseDatasets(object, reference)
-    if (!inherits(dataset(object, reference), "ligerATACDataset"))
-        stop("Selected reference should be ATAC dataset.")
+        cli::cli_abort(
+            "Aligned factor loading has to be available for imputation.
+            Please run {.fn quantileNorm} in advance.")
+    reference <- .checkArgLen(reference, n = 1)
+    reference <- .checkUseDatasets(object, reference)#, modal = "atac")
     queries <- .checkUseDatasets(object, queries)
     if (any(queries %in% reference)) {
-        warning("Reference dataset cannot be inclued in the query ",
-                "datasets. Removed from query list.")
+        cli::cli_alert_warning(
+            "Reference dataset cannot be inclued in the query datasets."
+        )
+        cli::cli_alert_warning(
+            "Removed from query list: {.val {queries[queries %in% reference]}}"
+        )
         queries <- queries[!queries %in% reference]
     }
     object <- recordCommand(object, ..., dependencies = c("RANN", "Matrix"))
     if (isTRUE(verbose)) {
-        .log("Imputing all the datasets exept the reference dataset\n",
-             "Reference dataset: ", reference, "\n",
-             "Query datasets: ", paste(queries, collapse = ", "))
+        cli::cli_alert_info(
+            "Imputing {length(queries)} query dataset{?s}: {.val {queries}}"
+        )
+        cli::cli_alert_info("from reference dataset: {.val {reference}}")
     }
 
     referenceCells <- colnames(dataset(object, reference))
@@ -194,35 +189,36 @@ linkGenesAndPeaks <- function(
 ) {
     ## check dependency
     if (!requireNamespace("GenomicRanges", quietly = TRUE))
-        stop("Package \"GenomicRanges\" needed for this function to work. ",
-             "Please install it by command:\n",
-             "BiocManager::install('GenomicRanges')",
-             call. = FALSE)
+        cli::cli_abort(
+            "Package {.pkg GenomicRanges} is needed for this function to work.
+            Please install it by command:
+            {.code BiocManager::install('GenomicRanges')}")
 
     if (!requireNamespace("IRanges", quietly = TRUE))
-        stop("Package \"IRanges\" needed for this function to work. ",
-             "Please install it by command:\n",
-             "BiocManager::install('IRanges')",
-             call. = FALSE)
+        cli::cli_abort(
+            "Package {.pkg IRanges} is needed for this function to work.
+            Please install it by command:
+            {.code BiocManager::install('IRanges')}")
     if (!requireNamespace("psych", quietly = TRUE))
-        stop("Package \"psych\" needed for this function to work. ",
-             "Please install it by command:\n",
-             "BiocManager::install('psych')",
-             call. = FALSE)
+        cli::cli_abort(
+            "Package {.pkg psych} is needed for this function to work.
+            Please install it by command:
+            {.code BiocManager::install('psych')}")
     .deprecateArgs(list(path_to_coords = "pathToCoords",
                         genes.list = "useGenes", dist = "method"))
     method <- match.arg(method)
-    if (length(useDataset) != 1)
-        stop("Please select only one dataset")
     useDataset <- .checkUseDatasets(object, useDataset)
+    if (length(useDataset) != 1)
+        cli::cli_abort("Please select only one dataset")
     lad <- dataset(object, useDataset)
     if (!inherits(lad, "ligerATACDataset"))
-        stop("Specified dataset is not of `ligerATACDataset` class. ",
-             "Please try `imputeKNN()` with `query = ", useDataset, "`. ")
+        cli::cli_abort(
+            "Specified dataset is not of `ligerATACDataset` class.
+            Please try {.fn imputeKNN} with `query = '{useDataset}'`.")
     if (is.null(normData(lad)))
-        stop("Normalized gene expression not found in specified dataset.")
+        cli::cli_abort("Normalized gene expression not found in specified dataset.")
     if (is.null(normPeak(lad)))
-        stop("Normalized peak counts not found in specified dataset.")
+        cli::cli_abort("Normalized peak counts not found in specified dataset.")
 
     ### make GRanges object for peaks
     peakCounts <- normPeak(lad)
@@ -257,23 +253,26 @@ linkGenesAndPeaks <- function(
     if (is.null(useGenes)) useGenes <- colnames(geneCounts)
     missingGenes <- !useGenes %in% names(genesCoords)
     if (sum(missingGenes) != 0 && isTRUE(verbose))
-        .log("Ignoring ",sum(missingGenes),
-             " genes not found in given gene coordinates")
-
+        cli::cli_alert_warning(
+            "Ignoring {sum(missingGenes)} genes not found in given gene coordinates"
+        )
     useGenes <- useGenes[!missingGenes]
-    if (length(useGenes) == 0)
-        stop("Number of genes to be tested equals 0. Please check input ",
-             "`useGenes` or the coordinate file.")
-    else {
-        .log(length(useGenes), " genes to be tested against ", ncol(peakCounts),
-             " peaks")
+    if (length(useGenes) == 0) {
+        cli::cli_abort(
+            "Number of genes to be tested equals 0. Please check input
+            {.code useGenes} or the coordinate file."
+        )
+    } else {
+        cli::cli_alert_info(
+            "{length(useGenes)} genes to be tested against {ncol(peakCounts)} peaks"
+        )
     }
     genesCoords <- genesCoords[useGenes]
 
     ### construct regnet
     if (isTRUE(verbose)) {
-        .log("Calculating correlation for gene-peak pairs...")
-        pb <- utils::txtProgressBar(0, length(useGenes), style = 3)
+        cli::cli_alert_info("Calculating correlation for gene-peak pairs...")
+        cli::cli_progress_bar("", total = length(useGenes), type = "iter")
     }
 
     # Result would be a sparse matrix, initialize the `i`, `p`, `x` vectors.
@@ -320,9 +319,10 @@ linkGenesAndPeaks <- function(
         ind <- c(ind, as.numeric(peaks.use))
         indp <- c(indp, as.numeric(eachLen))
         values <- c(values, res.corr)
-        if (isTRUE(verbose)) utils::setTxtProgressBar(pb, pos)
+        if (isTRUE(verbose)) {
+            cli::cli_progress_update(set = pos)
+        }
     }
-    if (isTRUE(verbose)) cat("\n")
     # make final sparse matrix
     regnet <-  Matrix::sparseMatrix(
         i = ind, p = c(0, indp), x = values,
@@ -379,20 +379,22 @@ exportInteractTrack <- function(
     if (is.null(useGenes)) {
         useGenes <- colnames(corrMat)
     } else if (any(!useGenes %in% colnames(corrMat))) {
-        .log("Removed ", sum(!useGenes %in% colnames(corrMat)), " genes not ",
-             "found in `corrMat`")
+        cli::cli_alert_warning(
+            "Removed {sum(!useGenes %in% colnames(corrMat))} genes not found in {.code corrMat}"
+        )
         useGenes <- useGenes[useGenes %in% colnames(corrMat)]
     }
     # Filter useGenes by significance
     geneSel <- Matrix::colSums(corrMat[, useGenes, drop = FALSE] != 0) > 0
     if (length(useGenes) - sum(geneSel) > 0)
-        .log("Totally ", length(useGenes) - sum(geneSel), " selected genes do ",
-             "not have significant correlated peaks, out of ", length(useGenes),
-             " selected genes")
+        cli::cli_alert_warning(
+            "Totally {length(useGenes) - sum(geneSel)} selected genes do not have significant correlated peaks, out of {length(useGenes)} selected genes",
+            wrap = TRUE
+        )
     useGenes <- useGenes[geneSel]
     if (length(useGenes) == 0) {
-        stop("No gene requested is either available or ",
-             "having significant correlated peaks. ")
+        cli::cli_abort("No gene requested is either available or having
+                       significant correlated peaks. ")
     }
 
     ### make GRanges object for genes
@@ -414,8 +416,6 @@ exportInteractTrack <- function(
     if (!file.exists(outputPath)) file.create(outputPath)
     outputPath <- normalizePath(outputPath)
 
-    .log("Writing result to: ", outputPath)
-
     # Start writing BED file
     trackDoc <- paste0('track type=interact name="Interaction Track" ',
                        'description="Gene-Peaks Links" ',
@@ -459,6 +459,8 @@ exportInteractTrack <- function(
             fileEncoding = ""
         )
     }
+    cli::cli_alert_success("Result written at: {.file {outputPath}}")
+    invisible(NULL)
 }
 
 #' [Deprecated] Export predicted gene-pair interaction
diff --git a/R/DEG_marker.R b/R/DEG_marker.R
index 69978dfb..2916215c 100644
--- a/R/DEG_marker.R
+++ b/R/DEG_marker.R
@@ -96,7 +96,7 @@ runPairwiseDEG <- function(
         groups <- list(group1Idx, group2Idx)
         names(groups) <- c(group1Name, group2Name)
     } else {
-        stop("Please see `?runPairwiseDEG` for usage.")
+        cli::cli_abort("Please see {.code ?runPairwiseDEG} for usage.")
     }
     result <- .runDEG(object, groups = groups, method = method,
                       usePeak = usePeak, useReplicate = useReplicate,
@@ -161,7 +161,7 @@ runMarkerDEG <- function(
     allCellIdx <- seq(ncol(object))[object$dataset %in% useDatasets]
     conditionBy <- conditionBy %||% object@uns$defaultCluster
     if (is.null(conditionBy)) {
-        stop("No `conditionBy` given or default cluster not set.")
+        cli::cli_abort("No {.var conditionBy} given or default cluster not set.")
     }
     conditionBy <- .fetchCellMetaVar(
         object, conditionBy, cellIdx = allCellIdx,
@@ -241,6 +241,8 @@ runWilcoxon <- function(
 ) {
     method <- match.arg(method)
     allCellIdx <- unlist(groups)
+    if (length(allCellIdx) == 0)
+        cli::cli_abort(c(x = "No cell selected"))
     allCellBC <- colnames(object)[allCellIdx]
     datasetInvolve <- levels(object$dataset[allCellIdx, drop = TRUE])
     var <- factor(rep(names(groups), lengths(groups)), levels = names(groups))
@@ -258,8 +260,10 @@ runWilcoxon <- function(
     mat <- Reduce(cbind, dataList)
     mat <- mat[, allCellBC, drop = FALSE]
     if (method == "wilcoxon") {
+        cliID <- cli::cli_process_start("Running Wilcoxon rank-sum test")
         mat <- log1p(1e10*mat)
         result <- wilcoxauc(mat, var)
+        cli::cli_process_done(id = cliID)
     } else if (method == "pseudoBulk") {
         if (is.null(useReplicate)) {
             replicateAnn <- setupPseudoRep(var, nRep = nPsdRep,
@@ -292,18 +296,20 @@ runWilcoxon <- function(
 
 .DE.checkDataAvail <- function(object, useDatasets, method, usePeak) {
     if (isH5Liger(object, useDatasets)) { # nocov start
-        stop("HDF5 based datasets detected but is not supported. \n",
-             "Try `object.sub <- downsample(object, useSlot = ",
-             "'normData')` to create ANOTHER object with in memory data.")
+        cli::cli_abort(
+            c("HDF5 based datasets detected but is not supported. ",
+              "i" = "Try {.code object.sub <- downsample(object, useSlot = 'normData')} to create another object with in memory data")
+        )
     } # nocov end
     if (method == "wilcoxon") {
         slot <- ifelse(usePeak, "normPeak", "normData")
     } else if (method == "pseudoBulk") {
         if (!requireNamespace("DESeq2", quietly = TRUE)) # nocov start
-            stop("Package \"DESeq2\" needed for this function to work. ",
-                 "Please install it by command:\n",
-                 "BiocManager::install('DESeq2')",
-                 call. = FALSE) # nocov end
+            cli::cli_abort(
+                "Package {.pkg DESeq2} is needed for this function to work.
+                Please install it by command:
+                {.code BiocManager::install('DESeq2')}"
+            ) # nocov end
         slot <- ifelse(usePeak, "rawPeak", "rawData")
     }
     allAvail <- all(sapply(useDatasets, function(d) {
@@ -311,8 +317,10 @@ runWilcoxon <- function(
         !is.null(methods::slot(ld, slot))
     }))
     if (!allAvail)
-        stop(slot, " not all available for involved datasets. [method = \"",
-             method, "\", usePeak = ", usePeak, "]")
+        cli::cli_abort(
+            c("{.field {slot}} not all available for involved datasets: {.val {useDatasets}}",
+              "i" = "{.code method = '{method}'}; {.code usePeak = {usePeak}}")
+        )
     return(slot)
 }
 
@@ -345,9 +353,10 @@ makePseudoBulk <- function(mat, replicateAnn, minCellPerRep, verbose = TRUE) {
         subrep <- replicateAnn[replicateAnn$groups == gr,]
         splitLabel <- interaction(subrep, drop = TRUE)
         if (nlevels(splitLabel) < 2) {
-            stop("Too few replicates label for condition \"", gr, "\". ",
-                 "Cannot not create pseudo-bulks. Please use ",
-                 "consider creating pseudo-replicates or use wilcoxon instead.")
+            cli::cli_abort(
+                c("Too few replicates for condition {.val {gr}}. Cannot create pseudo-bulks.",
+                  "i" = "Please consider creating pseudo-replicates or using {.code method = 'wilcoxon'} instead.")
+            )
         }
     }
     splitLabel <- interaction(replicateAnn, drop = TRUE)
@@ -360,10 +369,9 @@ makePseudoBulk <- function(mat, replicateAnn, minCellPerRep, verbose = TRUE) {
     mat <- mat[, idx, drop = FALSE]
     replicateAnn <- replicateAnn[idx, , drop = FALSE]
     if (verbose) {
-        .log("Ignoring replicates with too few cells: ",
-             paste0(ignored, collapse = ", "))
-        .log("Replicate size:")
-        .log(paste0(levels(splitLabel), ": ", table(splitLabel), collapse = ", "), level = 2)
+        if (length(ignored) > 0) cli::cli_alert_warning("Ignoring replicates with too few cells: {.val {ignored}}")
+        cli::cli_alert_info("Replicate sizes:")
+        print(table(splitLabel))
     }
     pseudoBulks <- colAggregateSums_sparse(mat, as.integer(splitLabel) - 1,
                                            nlevels(splitLabel))
@@ -375,7 +383,7 @@ makePseudoBulk <- function(mat, replicateAnn, minCellPerRep, verbose = TRUE) {
 .callDESeq2 <- function(pseudoBulks, groups,
                          verbose = getOption("ligerVerbose")) {
     # DESeq2 workflow
-    if (isTRUE(verbose)) .log("Calling DESeq2 Wald test")
+    if (isTRUE(verbose)) cliID <- cli::cli_process_start("Calling DESeq2 Wald test")
     ## NOTE: DESeq2 wishes that the contrast/control group is the first level
     ## whereas we required it as the second in upstream input. So we need to
     ## reverse it here.
@@ -396,6 +404,7 @@ makePseudoBulk <- function(mat, replicateAnn, minCellPerRep, verbose = TRUE) {
     res$group <- levels(groups)[2]
     res <- res[, c(7, 8, 2, 5, 6)]
     colnames(res) <- c("feature", "group", "logFC", "pval", "padj")
+    if (isTRUE(verbose)) cli::cli_process_done(id = cliID)
     return(res)
 }
 
diff --git a/R/DoubletFinder.R b/R/DoubletFinder.R
index fa2e2f3d..1dc4c3dc 100644
--- a/R/DoubletFinder.R
+++ b/R/DoubletFinder.R
@@ -41,27 +41,29 @@ runDoubletFinder <- function(
         ...
 ) {
     if (!requireNamespace("DoubletFinder", quietly = TRUE)) { # nocov start
-        stop("DoubletFinder need to be installed. Please run:\n",
-             "remotes::install_github('chris-mcginnis-ucsf/DoubletFinder')")
+        cli::cli_abort(
+            "Package {.pkg DoubletFinder} is needed for this function to work.
+            Please install it by command:
+            {.code remotes::install_github('DoubletFinder')}")
     }
     if (!requireNamespace("Seurat", quietly = TRUE)) {
-        stop("Seurat need to be installed. Please run:\n",
-             "install.packages(\"Seurat\")")
+        cli::cli_abort(
+            "Package {.pkg Seurat} is needed for this function to work.
+            Please install it by command:
+            {.code install.packages('Seurat')}")
     } # nocov end
     useDatasets <- .checkUseDatasets(object, useDatasets = useDatasets)
-    nNeighbors <- .checkArgLen(nNeighbors, length(useDatasets), repN = TRUE)
-    if (!is.null(nExp)) {
-        nExp <- .checkArgLen(nExp, length(useDatasets), repN = TRUE)
-    } else {
-        nExp <- sapply(useDatasets, function(d) {
+    nNeighbors <- .checkArgLen(nNeighbors, length(useDatasets), repN = TRUE, class = "numeric")
+    nExp <- .checkArgLen(nExp, length(useDatasets), repN = TRUE, class = "numeric")
+    if (is.null(nExp))
+        nExp <- sapply(useDatasets, function(d)
             round(0.15 * ncol(dataset(object, d)))
-        })
-    }
+        )
     object <- recordCommand(object, ...,
                             dependencies = c("Seurat", "DoubletFinder"))
     for (i in seq_along(useDatasets)) {
         d <- useDatasets[i]
-        if (isTRUE(verbose)) .log("Running DoubletFinder on dataset: ", d)
+        if (isTRUE(verbose)) cliID <- cli::cli_process_start("Running DoubletFinder on dataset {.val {d}}")
         seu <- Seurat::CreateSeuratObject(rawData(object, d)) %>%
             Seurat::NormalizeData(verbose = FALSE) %>%
             Seurat::FindVariableFeatures(verbose = FALSE) %>%
@@ -74,6 +76,7 @@ runDoubletFinder <- function(
         DFCol <- grep(pattern = "DF.classifications", colnames(seuMeta))
         cellMeta(object, "DoubletFinder_pANN", useDatasets = d) <- seuMeta[,pANNCol]
         cellMeta(object, "DoubletFinder_classification", useDatasets = d) <- seuMeta[,DFCol]
+        if (isTRUE(verbose)) cli::cli_process_done(id = cliID)
     }
     return(object)
 }
diff --git a/R/GSEA.R b/R/GSEA.R
index 04c0bcc1..dc6a0899 100644
--- a/R/GSEA.R
+++ b/R/GSEA.R
@@ -32,22 +32,22 @@ runGSEA <- function(
         custom_gene_sets = customGenesets
 ) {
     if (!requireNamespace("org.Hs.eg.db", quietly = TRUE)) # nocov start
-        stop("Package \"org.Hs.eg.db\" needed for this function to work. ",
-             "Please install it by command:\n",
-             "BiocManager::install('org.Hs.eg.db')",
-             call. = FALSE)
+        cli::cli_abort(
+            "Package {.pkg org.Hs.eg.db} is needed for this function to work.
+            Please install it by command:
+            {.code BiocManager::install('org.Hs.eg.db')}")
 
     if (!requireNamespace("reactome.db", quietly = TRUE))
-        stop("Package \"reactome.db\" needed for this function to work. ",
-             "Please install it by command:\n",
-             "BiocManager::install('reactome.db')",
-             call. = FALSE)
+        cli::cli_abort(
+            "Package {.pkg reactome.db} is needed for this function to work.
+            Please install it by command:
+            {.code BiocManager::install('reactome.db')}")
 
     if (!requireNamespace("fgsea", quietly = TRUE))
-        stop("Package \"fgsea\" needed for this function to work. ",
-             "Please install it by command:\n",
-             "BiocManager::install('fgsea')",
-             call. = FALSE) # nocov end
+        cli::cli_abort(
+            "Package {.pkg fgsea} is needed for this function to work.
+            Please install it by command:
+            {.code BiocManager::install('fgsea')}") # nocov end
 
     .deprecateArgs(list(gene_sets = "genesets",
                         mat_w = "useW",
@@ -164,14 +164,14 @@ runGOEnrich <- function(
         ...
 ) {
     if (!requireNamespace("gprofiler2", quietly = TRUE)) # nocov start
-        stop("Package \"gprofiler2\" needed for this function to work. ",
-             "Please install it by command:\n",
-             "install.packages('gprofiler2')",
-             call. = FALSE) # nocov end
+        cli::cli_abort(
+            "Package {.pkg gprofiler2} is needed for this function to work.
+            Please install it by command:
+            {.code install.packages('gprofiler2')}") # nocov end
+
     group <- group %||% unique(result$group)
     if (any(!group %in% result$group)) {
-        stop("Selected groups not available `result$group`: ",
-             paste(group[!group %in% result$group], collapse = ", "))
+        cli::cli_abort("Selected groups not available in {.code result$group}: {.val {group[!group %in% result$group]}}")
     }
     bg <- NULL
     domain_scope <- "annotated" # gprofiler2 default
@@ -190,9 +190,9 @@ runGOEnrich <- function(
     ordered_query <- FALSE
     if (!is.null(orderBy)) {
         ordered_query <- TRUE
-        if (length(orderBy) > 1) stop("Only one `orderBy` metric allowed")
+        if (length(orderBy) > 1) cli::cli_abort("Only one {.code orderBy} metric allowed")
         if (!orderBy %in% c("logFC", "pval", "padj")) {
-            stop("`orderBy` should be one of 'logFC', 'pval' or 'padj'.")
+            cli::cli_abort("{.code orderBy} should be one of {.val logFC}, {.val pval} or {.val padj}.")
         }
         if (orderBy == "logFC") {
             resultUp <- resultUp[order(resultUp$logFC, decreasing = TRUE),]
diff --git a/R/zzz.R b/R/aaa.R
similarity index 100%
rename from R/zzz.R
rename to R/aaa.R
diff --git a/R/classConversion.R b/R/classConversion.R
index b451f906..3a0747ae 100644
--- a/R/classConversion.R
+++ b/R/classConversion.R
@@ -1,68 +1,6 @@
-setClass("ligerDataset")
-setClassUnion("matrixLike", c("matrix", "dgCMatrix", "dgTMatrix", "dgeMatrix"))
-
 #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 # From other things to liger class ####
 #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#' Converting other classes of data to a liger object
-#' @description
-#' This function converts data stored in SingleCellExperiment (SCE), Seurat
-#' object or a merged sparse matrix (dgCMatrix) into a liger object. This is
-#' designed for a container object or matrix that already contains multiple
-#' datasets to be integerated with LIGER. For individual datasets, please use
-#' \code{\link{createLiger}} instead.
-#' @export
-#' @param object Object.
-#' @param datasetVar Specify the dataset belonging by: 1. Select a variable from
-#' existing metadata in the object (e.g. colData column); 2. Specify a
-#' vector/factor that assign the dataset belonging. 3. Give a single character
-#' string which means that all data is from one dataset (must not be a metadata
-#' variable, otherwise it is understood as 1.). Default \code{NULL} gathers
-#' things into one dataset and names it "sample" for dgCMatrix, attempts
-#' to find variable "sample" from SCE or "orig.ident" from Seurat.
-#' @param modal Modality setting for each dataset. See
-#' \code{\link{createLiger}}.
-#' @param ... Additional arguments passed to \code{\link{createLiger}}
-#' @details
-#' For Seurat V5 structure, it is highly recommended that users make use of its
-#' split layer feature, where things like "counts", "data", and "scale.data"
-#' can be held for each dataset in the same Seurat object, e.g. with
-#' "count.ctrl", "count.stim", not merged. If a Seurat object with split layers
-#' is given, \code{datasetVar} will be ignored and the layers will be directly
-#' used.
-#' @return a \linkS4class{liger} object.
-#' @rdname as.liger
-#' @examples
-#' # dgCMatrix (common sparse matrix class), usually obtained from other
-#' # container object, and contains multiple samples merged in one.
-#' matList <- rawData(pbmc)
-#' multiSampleMatrix <- mergeSparseAll(matList)
-#' # The `datasetVar` argument expects the variable assigning the sample source
-#' pbmc2 <- as.liger(multiSampleMatrix, datasetVar = pbmc$dataset)
-#' pbmc2
-#'
-#' sce <- SingleCellExperiment::SingleCellExperiment(
-#'     assays = list(counts = multiSampleMatrix)
-#' )
-#' sce$sample <- pbmc$dataset
-#' pbmc3 <- as.liger(sce, datasetVar = "sample")
-#' pbmc3
-#'
-#' seu <- SeuratObject::CreateSeuratObject(multiSampleMatrix)
-#' # Seurat creates variable "orig.ident" by identifying the cell barcode
-#' # prefixes, which is indeed what we need in this case. Users might need
-#' # to be careful and have it confirmed first.
-#' pbmc4 <- as.liger(seu, datasetVar = "orig.ident")
-#' pbmc4
-#'
-#' # As per Seurat V5 updates with layered data, specifically helpful udner the
-#' # scenario of dataset integration. "counts" and etc for each datasets can be
-#' # split into layers.
-#' seu5 <- seu
-#' seu5[["RNA"]] <- split(seu5[["RNA"]], pbmc$dataset)
-#' print(SeuratObject::Layers(seu5))
-#' pbmc5 <- as.liger(seu5)
-as.liger <- function(object, ...) UseMethod("as.liger", object)
 
 #' @rdname as.liger
 #' @export
@@ -80,7 +18,7 @@ as.liger.dgCMatrix <- function(
     datasetVar <- droplevels(datasetVar)
 
     rawDataList <- splitRmMiss(object, datasetVar)
-    modal <- .checkArgLen(modal, length(rawDataList))
+    modal <- .checkArgLen(modal, length(rawDataList), class = "character")
     createLiger(rawData = rawDataList, modal = modal, ...)
 }
 
@@ -94,15 +32,17 @@ as.liger.SingleCellExperiment <- function(
         ...
 ) {
     if (!requireNamespace("SingleCellExperiment", quietly = TRUE)) # nocov start
-        stop("Package \"SingleCellExperiment\" needed for this function ",
-             "to work. Please install it by command:\n",
-             "BiocManager::install('SingleCellExperiment')",
-             call. = FALSE)
+        cli::cli_abort(
+            "Package {.pkg SingleCellExperiment} is needed for this function to work.
+            Please install it by command:
+            {.code BiocManager::install('SingleCellExperiment')}"
+        )
     if (!requireNamespace("SummarizedExperiment", quietly = TRUE))
-        stop("Package \"SummarizedExperiment\" needed for this function ",
-             "to work. Please install it by command:\n",
-             "BiocManager::install('SummarizedExperiment')",
-             call. = FALSE) # nocov end
+        cli::cli_abort(
+            "Package {.pkg SummarizedExperiment} is needed for this function to work.
+            Please install it by command:
+            {.code BiocManager::install('SummarizedExperiment')}"
+        ) # nocov end
     raw <- SingleCellExperiment::counts(object)
 
     if (is.null(datasetVar)) {
@@ -121,7 +61,7 @@ as.liger.SingleCellExperiment <- function(
     if (!is.factor(datasetVar)) datasetVar <- factor(datasetVar)
     datasetVar <- droplevels(datasetVar)
     raw <- splitRmMiss(raw, datasetVar)
-    modal <- .checkArgLen(modal, length(raw))
+    modal <- .checkArgLen(modal, length(raw), class = "character")
     lig <- createLiger(raw, modal = modal, ...)
     colDataCopy <- SummarizedExperiment::colData(object)
     for (cdn in colnames(colDataCopy)) {
@@ -129,8 +69,8 @@ as.liger.SingleCellExperiment <- function(
             same <- identical(colDataCopy[[cdn]], cellMeta(lig, cdn))
             if (same) next
             cdnNew <- paste0("SCE_", cdn)
-            warning("Variable name \"", cdn, "\" in colData of SingleCellExperiment ",
-                    "conflicts with liger default variables. Modified to ", cdnNew, ".")
+            cli::cli_alert_warning(
+                "Variable name {.val {cdn}} in colData of SingleCellExperiment conflicts with liger default variables. Modified to {.val {cdnNew}}.")
         } else {
             cdnNew <- cdn
         }
@@ -179,7 +119,7 @@ as.liger.Seurat <- function(
     }
 
     datasetVar <- datasetVar %||% "Seurat"
-    modal <- .checkArgLen(modal, length(raw))
+    modal <- .checkArgLen(modal, length(raw), class = "character")
     lig <- createLiger(raw, modal = modal, ...)
     colnames(object) <- colnames(lig)
     for (cdn in colnames(object[[]])) {
@@ -187,8 +127,8 @@ as.liger.Seurat <- function(
             same <- identical(object[[cdn, drop = TRUE]], cellMeta(lig, cdn))
             if (same) next
             cdnNew <- paste0("Seurat_", cdn)
-            warning("Variable name \"", cdn, "\" in meta.data of Seurat ",
-                    "conflicts with liger default variables. Modified to ", cdnNew, ".")
+            cli::cli_alert_warning(
+                "Variable name {.val {cdn}} in meta.data of Seurat conflicts with liger default variables. Modified to {.val {cdnNew}}.")
         } else {
             cdnNew <- cdn
         }
@@ -205,32 +145,6 @@ as.liger.Seurat <- function(
 #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 # From other things to ligerDataset class ####
 #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#' Converting other classes of data to a as.ligerDataset object
-#' @description
-#' Works for converting a matrix or container object to a single ligerDataset,
-#' and can also convert the modality preset of a ligerDataset. When used with
-#' a dense matrix object, it automatically converts the matrix to sparse form
-#' (\code{\link[Matrix]{dgCMatrix-class}}). When used with container objects
-#' such as Seurat or SingleCellExperiment, it is highly recommended that the
-#' object contains only one dataset/sample which is going to be integrated with
-#' LIGER. For multi-sample objects, please use \code{\link{as.liger}} with
-#' dataset source variable specified.
-#' @export
-#' @param object Object.
-#' @param modal Modality setting for each dataset. Choose from \code{"default"},
-#' \code{"rna"}, \code{"atac"}, \code{"spatial"}, \code{"meth"}.
-#' @param ... Additional arguments passed to \code{\link{createLigerDataset}}
-#' @return a \linkS4class{liger} object.
-#' @rdname as.ligerDataset
-#' @examples
-#' ctrl <- dataset(pbmc, "ctrl")
-#' ctrl
-#' # Convert the modality preset
-#' as.ligerDataset(ctrl, modal = "atac")
-#' rawCounts <- rawData(ctrl)
-#' class(rawCounts)
-#' as.ligerDataset(rawCounts)
-as.ligerDataset <- function(object, ...) UseMethod("as.ligerDataset", object)
 
 #' @rdname as.ligerDataset
 #' @export
@@ -246,10 +160,9 @@ as.ligerDataset.ligerDataset <- function(
     slotFromClass <- methods::slotNames(class(object))
     slotToClass <- methods::slotNames(newClass)
     if (any(!slotFromClass %in% slotToClass))
-        warning("Will remove information in the following slots when ",
-                "converting class from `", class(object), "` to `", newClass,
-                "`: ", paste(slotFromClass[!slotFromClass %in% slotToClass],
-                             collapse = ", "))
+        cli::cli_alert_warning(
+            "Will remove information in the following slots when converting class
+            from {.cls {class(object)}} to {.cls {newClass}}: {.val {slotFromClass[!slotFromClass %in% slotToClass]}}")
     newCallArgs <- list(Class = newClass)
     for (s in slotFromClass) {
         if (s %in% slotToClass)
@@ -308,10 +221,11 @@ as.ligerDataset.SingleCellExperiment <- function(
         ...
 ) {
     if (!requireNamespace("SingleCellExperiment", quietly = "TRUE")) # nocov start
-        stop("Package \"SingleCellExperiment\" needed for this function ",
-             "to work. Please install it by command:\n",
-             "BiocManager::install('SingleCellExperiment')",
-             call. = FALSE) # nocov end
+        cli::cli_abort(
+            "Package {.pkg SingleCellExperiment} is needed for this function to work.
+            Please install it by command:
+            {.code BiocManager::install('SingleCellExperiment')}"
+        ) # nocov end
     modal <- match.arg(modal)
     mat <- SingleCellExperiment::counts(object)
     createLigerDataset(rawData = mat, modal = modal, ...)
@@ -351,6 +265,7 @@ as.ligerDataset.SingleCellExperiment <- function(
 #' @param use.liger.genes [Defunct] Will be ignored and will always set LIGER
 #' variable features to the place.
 #' @export
+#' @rdname ligerToSeurat
 #' @return Always returns Seurat object(s) of the latest version. By default a
 #' Seurat object with split layers, e.g. with layers like "counts.ctrl" and
 #' "counts.stim". If \code{merge = TRUE}, return a single Seurat object with
@@ -386,7 +301,7 @@ ligerToSeurat <- function(
     rawDataList <- rawDataList[!sapply(rawDataList, is.null)]
     if (isTRUE(merge)) rawDataList <- mergeSparseAll(rawDataList)
     if (!length(rawDataList)) {
-        stop("rawData not found.")
+        cli::cli_abort("rawData not found.")
     }
     Assay <- SeuratObject::CreateAssay5Object(rawDataList)
 
@@ -588,8 +503,8 @@ convertOldLiger.mem <- function(object) {
         if (!is.null(dataList$rawData)) features <- rownames(dataList$rawData)
         else features <- rownames(dataList$normData)
         if (is.null(features)) {
-            warning("Cannot detect feature names for dataset \"", d, "\". ",
-                    "Skipped.")
+            cli::cli_alert_danger(
+                "Cannot detect feature names for dataset {.val {d}}. Skipped.")
             next
         }
         ftPassing <- .checkIDIdentical(
@@ -627,10 +542,12 @@ convertOldLiger.mem <- function(object) {
 }
 
 convertOldLiger.H5 <- function(object, h5FilePath = NULL) {
-    .log("Please use caution when restoring an H5 based liger object, because ",
-         "old version does not have solid restriction on cell/feature ",
-         "identifier matching. New rliger assumes all data was produced ",
-         "with standard old rliger workflow.")
+    cli::cli_alert_warning(
+        "Please use caution when restoring an H5 based liger object, because
+        the old version does not have any solid restriction on cell/feature
+        identifier matching. New rliger > 1.99 assumes all data was produced
+        with standard old rliger workflow.", wrap = TRUE
+    )
     dataLists <- list()
     if (.hasSlot(object, "H")) dataLists$H <- object@H
     if (.hasSlot(object, "V")) dataLists$V <- object@V
@@ -712,8 +629,7 @@ convertOldLiger.H5 <- function(object, h5FilePath = NULL) {
         if (!is.null(h5FilePath[[d]])) h5Path <- h5FilePath[[d]]
         else h5Path <- object@h5file.info[[d]]$file.path
         if (!hdf5r::is_hdf5(name = h5Path)) {
-            stop("File path for dataset \"", d, "\" not found or is not an H5 ",
-                 "file: ", h5Path)
+            cli::cli_abort("File path for dataset {.val {d}} not found or is not an H5 file: {.file {h5Path}}")
         }
         h5Format <- object@h5file.info[[d]]$format.type
         ldList[[d]] <- do.call(createH5LigerDataset, c(
@@ -750,7 +666,7 @@ convertOldLiger.H5 <- function(object, h5FilePath = NULL) {
     for (slot in names(onCol)) {
         if (is.na(slot)) next
         if (!identical(colnames(onCol[[slot]]), ref)) {
-            warning("Inconsistent column ID in slot `", slot, "`.")
+            cli::cli_alert_danger("Inconsistent column ID in slot {slot}.")
             colPassing[slot] <- FALSE
         }
     }
@@ -759,7 +675,7 @@ convertOldLiger.H5 <- function(object, h5FilePath = NULL) {
     for (slot in names(onRow)) {
         if (is.na(slot)) next
         if (!identical(rownames(onRow[[slot]]), ref)) {
-            warning("Inconsistent row ID in slot `", slot, "`.")
+            cli::cli_alert_danger("Inconsistent row ID in slot {slot}.")
             rowPassing[slot] <- FALSE
         }
     }
@@ -784,11 +700,11 @@ convertOldLiger.H5 <- function(object, h5FilePath = NULL) {
             return(TRUE)
         },
         error = function(e) {
-            .log("Skipped slot `", name, "` which is not available.")
+            cli::cli_alert_warning("Skipped slot {name} which is not available.")
             return(FALSE)
         },
         warining = function(w) {
-            .log(w)
+            cli::cli_alert_warning(w)
             return(FALSE)
         }
     )
diff --git a/R/classes.R b/R/classes.R
new file mode 100644
index 00000000..d1f473f9
--- /dev/null
+++ b/R/classes.R
@@ -0,0 +1,480 @@
+setClassUnion("dgCMatrix_OR_NULL", c("dgCMatrix", "NULL"))
+setClassUnion("matrix_OR_NULL", c("matrix", "NULL"))
+setClassUnion("matrixLike", c("matrix", "dgCMatrix", "dgTMatrix", "dgeMatrix"))
+setClassUnion("matrixLike_OR_NULL", c("matrixLike", "NULL"))
+setClassUnion("character_OR_NULL", c("character", "NULL"))
+# It is quite hard to handle "H5D here, which is indeed defined as an R6 class.
+# I'm not sure if this is a proper solution
+setOldClass("H5D")
+setOldClass("H5Group")
+suppressWarnings(setClassUnion("dgCMatrix_OR_H5D_OR_NULL", c("dgCMatrix", "H5D", "NULL")))
+setClassUnion("matrix_OR_H5D_OR_NULL", c("matrix", "H5D", "NULL"))
+setClassUnion("matrixLike_OR_H5D_OR_H5Group_OR_NULL", c("matrixLike", "H5D", "H5Group", "NULL"))
+setClassUnion("index",
+              members = c("logical", "numeric", "character"))
+setClassUnion("Number_or_NULL", c("integer", "numeric", "NULL"))
+setClassUnion("dataframe", c("data.frame", "DataFrame", "NULL", "missing"))
+
+#' @importClassesFrom Matrix dgCMatrix dgTMatrix dgeMatrix
+NULL
+
+
+#' ligerDataset class
+#'
+#' Object for storing dastaset specific information. Will be embedded within a
+#' higher level \linkS4class{liger} object
+#' @docType class
+#' @rdname ligerDataset-class
+#' @slot rawData Raw data.
+#' @slot normData Normalized data
+#' @slot scaleData Scaled data, usually with subset variable features
+#' @slot scaleUnsharedData Scaled data of features not shared with other
+#' datasets
+#' @slot varUnsharedFeatures Variable features not shared with other datasets
+#' @slot V matrix
+#' @slot A matrix
+#' @slot B matrix
+#' @slot H matrix
+#' @slot U matrix
+#' @slot h5fileInfo list
+#' @slot featureMeta Feature metadata, DataFrame
+#' @slot colnames character
+#' @slot rownames character
+#' @importClassesFrom S4Vectors DataFrame
+#' @exportClass ligerDataset
+ligerDataset <- setClass(
+    "ligerDataset",
+    representation(
+        rawData = "dgCMatrix_OR_H5D_OR_NULL",
+        normData = "dgCMatrix_OR_H5D_OR_NULL",
+        scaleData = "matrixLike_OR_H5D_OR_H5Group_OR_NULL",
+        scaleUnsharedData = "matrixLike_OR_H5D_OR_H5Group_OR_NULL",
+        varUnsharedFeatures = "character",
+        H = "matrix_OR_NULL",
+        V = "matrix_OR_NULL",
+        A = "matrix_OR_NULL",
+        B = "matrix_OR_NULL",
+        U = "matrix_OR_NULL",
+        h5fileInfo = "list",
+        featureMeta = "DataFrame",
+        colnames = "character",
+        rownames = "character"
+    )
+)
+
+.checkLigerDatasetBarcodes <- function(x) {
+    # cell barcodes all consistant
+    if (is.null(colnames(x))) {
+        return(paste0("No valid cell barcode detected for ligerDataset.\n",
+                      "Please create object with matrices with colnames."))
+    }
+    for (slot in c("rawData", "normData", "scaleData", "scaleUnsharedData",
+                   "H")) {
+        if (!slot %in% methods::slotNames(x)) next
+        data <- methods::slot(x, slot)
+        if (!is.null(data)) {
+            barcodes.slot <- colnames(data)
+            if (!identical(colnames(x), barcodes.slot)) {
+                return(paste0("Inconsistant cell identifiers in `", slot,
+                              "` slot."))
+            }
+        }
+    }
+
+    for (slot in c("scaleData", "V")) {
+        featuresToCheck <- rownames(methods::slot(x, slot))
+        check <- !featuresToCheck %in% rownames(x)
+        if (any(check)) {
+            msg <- paste0("Features in ", slot, " not found from dataset: ",
+                          paste(featuresToCheck[check], collapse = ", "))
+            return(msg)
+        }
+    }
+    TRUE
+}
+
+.checkH5LigerDatasetLink <- function(x) {
+    restoreGuide <- "Please try running `restoreH5Liger(object)`."
+    if (!"H5File" %in% names(h5fileInfo(x))) {
+        return(paste("`h5fileInfo` incomplete.", restoreGuide))
+    }
+    h5file <- getH5File(x)
+    if (is.null(h5file)) {
+        return(paste("`H5File` is NULL in `h5fileInfo` slot.", restoreGuide))
+    }
+    if (!h5file$is_valid) {
+        return(paste("`H5File` is invalid in `h5fileInfo` slot.", restoreGuide))
+    }
+    if (!is.null(rawData(x))) {
+        if (!rawData(x)$is_valid) {
+            return(paste("`rawData` slot is invalid.", restoreGuide))
+        }
+    }
+    if (!is.null(normData(x))) {
+        if (!normData(x)$is_valid) {
+            return(paste("`normData` slot is invalid.", restoreGuide))
+        }
+    }
+    if (!is.null(scaleData(x))) {
+        if (!scaleData(x)$is_valid) {
+            return(paste("`scaleData` slot is invalid.", restoreGuide))
+        }
+    }
+    TRUE
+}
+
+.valid.ligerDataset <- function(object) {
+    if (isH5Liger(object)) {
+        # message("Checking h5 ligerDataset validity")
+        .checkH5LigerDatasetLink(object)
+    } else {
+        # message("Checking in memory ligerDataset validity")
+        .checkLigerDatasetBarcodes(object)
+    }
+    # TODO more checks
+    # TODO debating on whether to have check of the matching between scaleData
+    # features and selected variable features.
+}
+
+setValidity("ligerDataset", .valid.ligerDataset)
+
+#' @title liger class
+#' @rdname liger-class
+#' @docType class
+#' @description \code{liger} object is the main data container for LIGER
+#' analysis in R. The slot \code{datasets} is a list where each element should
+#' be a \linkS4class{ligerDataset} object containing dataset specific
+#' information, such as the expression matrices. The other parts of liger object
+#' stores information that can be shared across the analysis, such as the cell
+#' metadata and factorization result matrices.
+#'
+#' This manual provides explanation to the \code{liger} object structure as well
+#' as usage of class-specific methods. Please see detail sections for more
+#' information.
+#'
+#' For \code{liger} objects created with older versions of rliger package,
+#' please try updating the objects individually with
+#' \code{\link{convertOldLiger}}.
+#' @slot datasets list of \linkS4class{ligerDataset} objects. Use generic
+#' \code{dataset}, \code{dataset<-}, \code{datasets} or \code{datasets<-} to
+#' interact with. See detailed section accordingly.
+#' @slot cellMeta \linkS4class{DFrame} object for cell metadata. Pre-existing
+#' metadata, QC metrics, cluster labeling, low-dimensional embedding and etc.
+#' are all stored here. Use generic \code{cellMeta}, \code{cellMeta<-},
+#' \code{$}, \code{[[]]} or \code{[[]]<-} to interact with. See detailed section
+#' accordingly.
+#' @slot varFeatures Character vector of feature names. Use generic
+#' \code{varFeatures} or \code{varFeatures<-} to interact with. See detailed
+#' section accordingly.
+#' @slot W Matrix of gene loading for each factor. See
+#' \code{\link{runIntegration}}.
+#' @slot H.norm Matrix of aligned factor loading for each cell. See
+#' \code{\link{quantileNorm}} and \code{\link{runIntegration}}.
+#' @slot commands List of \linkS4class{ligerCommand} objects. Record of
+#' analysis. Use \code{commands} to retrieve information. See detailed section
+#' accordingly.
+#' @slot uns List for unstructured meta-info of analyses or presets.
+#' @slot version Record of version of rliger2 package
+#' @importClassesFrom S4Vectors DataFrame
+#' @importFrom ggplot2 fortify
+liger <- setClass(
+    "liger",
+    representation(
+        datasets = "list",
+        cellMeta = "DataFrame",
+        varFeatures = "character_OR_NULL",
+        W = "matrix_OR_NULL",
+        H.norm = "matrix_OR_NULL",
+        uns = "list",
+        commands = "list",
+        version = "ANY"
+    ),
+    methods::prototype(
+        cellMeta = methods::new("DFrame"),
+        version = utils::packageVersion("rliger2")
+    )
+)
+
+
+.checkAllDatasets <- function(x) {
+    for (ld in datasets(x)) {
+        methods::validObject(ld)
+    }
+    return(NULL)
+}
+
+.checkLigerBarcodes <- function(x) {
+    bcFromDatasets <- unlist(lapply(datasets(x), colnames), use.names = FALSE)
+    if (!identical(colnames(x), bcFromDatasets)) {
+        return("liger object barcodes do not match to barcodes in datasets")
+    }
+    if (!is.null(x@H.norm)) {
+        if (!identical(rownames(x@H.norm), bcFromDatasets)) {
+            return("H.norm barcodes do not match to barcodes in datasets.")
+        }
+    }
+    if (!"dataset" %in% names(cellMeta(x))) {
+        return("`datasets` variable missing in cellMeta(x)")
+    }
+    datasetNamesFromDatasets <- rep(names(x), lapply(datasets(x), ncol))
+    names(datasetNamesFromDatasets) <- NULL
+
+    if (!identical(datasetNamesFromDatasets, as.character(x$dataset))) {
+        return("names of datasets do not match
+               `datasets` variable in cellMeta")
+    }
+    return(NULL)
+}
+
+.checkLigerVarFeature <- function(x) {
+    if (!is.null(varFeatures(x)) &&
+        length(varFeatures(x)) > 0) {
+        if (!is.null(x@W))
+            if (!identical(rownames(x@W), varFeatures(x)))
+                return("Variable features do not match dimension of W matrix")
+        for (d in names(x)) {
+            ld <- dataset(x, d)
+            if (!is.null(ld@V)) {
+                if (!identical(rownames(ld@V), varFeatures(x)))
+                    return(paste("Variable features do not match dimension",
+                                 "of V matrix in dataset", d))
+            }
+
+            if (!is.null(scaleData(ld))) {
+                if (!isH5Liger(ld)) {
+                    if (!identical(rownames(scaleData(ld)), varFeatures(x)))
+                        return(paste("Variable features do not match dimension",
+                                     "of scaleData in dataset", d))
+                } else {
+                    if (inherits(scaleData(ld), "H5D")) {
+                        if (scaleData(ld)$dims[1] != length(varFeatures(x)))
+                            return(paste("Variable features do not match ",
+                                         "dimension of scaleData in dataset ",
+                                         "(H5)", d))
+                    } else if (inherits(scaleData(ld), "H5Group")) {
+                        if (scaleData(ld)[["featureIdx"]]$dims != length(varFeatures(x))) {
+                            return(paste("Variable features do not match ",
+                                         "dimension of scaleData in dataset ",
+                                         "(H5)", d))
+                        }
+                        scaleDataIdx <- scaleData(ld)[["featureIdx"]][]
+                        if (!identical(rownames(ld)[scaleDataIdx], varFeatures(x))) {
+                            return("HDF5 scaled data feature index does not ",
+                                   "match variable features")
+                        }
+                    }
+                }
+            }
+        }
+    }
+    return(NULL)
+}
+
+.valid.liger <- function(object) {
+    # message("Checking liger object validity")
+    res <- .checkAllDatasets(object)
+    if (!is.null(res)) return(res)
+    res <- .checkLigerBarcodes(object)
+    if (!is.null(res)) return(res)
+    res <- .checkLigerVarFeature(object)
+    if (!is.null(res)) return(res)
+    # TODO more checks
+}
+
+setValidity("liger", .valid.liger)
+
+
+
+setClassUnion("POSIXct_or_NULL", c("POSIXct", "NULL"))
+
+#' ligerCommand object: Record the input and time of a LIGER function call
+#' @slot funcName Name of the function
+#' @slot time A time stamp object
+#' @slot call A character string converted from system call
+#' @slot parameters List of all arguments except the \linkS4class{liger} object.
+#' Large object are summarized to short string.
+#' @slot objSummary List of attributes of the \linkS4class{liger} object as a
+#' snapshot when command is operated.
+#' @slot ligerVersion Character string converted from
+#' \code{packageVersion("rliger2")}.
+#' @slot dependencyVersion Named character vector of version number, if any
+#' dependency library has a chance to be included by the function. A
+#' dependency might only be invoked under certain conditions, such as using
+#' an alternative algorithm, which a call does not actually reach to, but it
+#' would still be included for this call.
+#' @exportClass ligerCommand
+#' @export
+#' @rdname ligerCommand-class
+ligerCommand <- setClass(
+    Class = "ligerCommand",
+    representation(
+        funcName = "character",
+        time = "POSIXct_or_NULL",
+        call = "character",
+        parameters = "list",
+        objSummary = "list",
+        ligerVersion = "character",
+        dependencyVersion = "character"
+    ),
+    prototype(
+        funcName = character(),
+        time = NULL,
+        parameters = list(),
+        objSummary = list(
+            datasets = character(),
+            nCells = numeric(),
+            nFeatures = numeric(),
+            nVarFeatures = numeric(),
+            cellMetaNames = character(),
+            ligerVersion = character(),
+            dependencyVersion = character()
+        )
+    )
+)
+
+
+################################################################################
+# Developer guide for adding a new sub-class of `ligerDataset` for new modality
+################################################################################
+#
+# Below is a check-list of the TODOs when new sub-classes need to be added.
+# Please follow them carefully, and refer to existing code as examples.
+#
+# 1. Add `setClass` chunk for defining the new subclass, pay attention to:
+#   a. Naming convention should be `liger{Modal}Dataset`, in camelCase
+#   b. contains = "ligerDataset"
+#   c. add new slots for modality specific information with `representation`
+#   d. if the default new information could be empty, add `prototype`
+# 2. In files `zzz.R`, `import.R`, `classConversion.R`, search for
+#    text "modal". When seeing a multi-option vector argument, add a unique
+#    abbreviation of this new data type to the vector. Don't forget updating
+#    valid options in the manual documentaion as well.
+# 3. If the new slot(s) added is thought to be retrieved by future developers
+#    or users, getter and setter methods MUST be implemented.
+# 4. Please go through the implementation of the following functions in file
+#    `ligerDataset-class.R`, and make sure data in the new slot(s) is properly
+#    handled.
+#   a. .checkLigerDatasetBarcodes()
+#   b. `dimnames<-()` (search: `setReplaceMethod("dimnames"`)
+#   c. `[` (search: "[")
+#
+################################################################################
+
+#' Subclass of ligerDataset for RNA modality
+#' @description Inherits from \linkS4class{ligerDataset} class. Contained slots
+#' can be referred with the link. This subclass does not have any different from
+#' the default \code{ligerDataset} class except the class name.
+#' @export
+#' @exportClass ligerRNADataset
+ligerRNADataset <- setClass(
+    "ligerRNADataset", contains = "ligerDataset"
+)
+
+
+#' Subclass of ligerDataset for ATAC modality
+#'
+#' @description Inherits from \linkS4class{ligerDataset} class. Contained slots
+#' can be referred with the link.
+#' @slot rawPeak sparse matrix
+#' @slot normPeak sparse matrix
+#' @exportClass ligerATACDataset
+#' @export
+ligerATACDataset <- setClass(
+    "ligerATACDataset",
+    contains = "ligerDataset",
+    representation = representation(rawPeak = "matrixLike_OR_NULL",
+                                    normPeak = "matrixLike_OR_NULL"),
+    prototype = prototype(rawPeak = NULL, normPeak = NULL)
+)
+
+.valid.ligerATACDataset <- function(object) {
+    passSuperClassCheck <- .valid.ligerDataset(object)
+    if (!isTRUE(passSuperClassCheck)) return(passSuperClassCheck)
+    for (slot in c("rawPeak", "normPeak")) {
+        data <- methods::slot(object, slot)
+        if (!is.null(data)) {
+            barcodes.slot <- colnames(data)
+            if (!identical(object@colnames, barcodes.slot)) {
+                return(paste0("Inconsistant cell identifiers in `", slot,
+                              "` slot."))
+            }
+        }
+    }
+}
+
+setValidity("ligerATACDataset", .valid.ligerATACDataset)
+
+#' Subclass of ligerDataset for Spatial modality
+#'
+#' @description Inherits from \linkS4class{ligerDataset} class. Contained slots
+#' can be referred with the link.
+#' @slot coordinate dense matrix
+#' @exportClass ligerSpatialDataset
+#' @export
+ligerSpatialDataset <- setClass(
+    "ligerSpatialDataset",
+    contains = "ligerDataset",
+    representation = representation(coordinate = "matrix_OR_NULL"),
+    prototype = prototype(coordinate = NULL)
+)
+
+.checkCoords <- function(ld, value) {
+    if (is.null(rownames(value))) {
+        cli::cli_alert_warning("No rownames with given spatial coordinate. Assuming they match with the cells.")
+        rownames(value) <- colnames(ld)
+    }
+    if (is.null(colnames(value))) {
+        if (ncol(value) <= 3) {
+            colnames(value) <- c("x", "y", "z")[seq(ncol(value))]
+        } else {
+            cli::cli_abort("More than 3 dimensions for the coordinates but no colnames are given.")
+        }
+        cli::cli_alert_warning(
+            "No colnames with given spatial coordinate. Setting to {.val {colnames(value)}}"
+        )
+    }
+    full <- matrix(NA, nrow = ncol(ld), ncol = ncol(value),
+                   dimnames = list(colnames(ld), colnames(value)))
+    cellIsec <- intersect(rownames(value), colnames(ld))
+    full[cellIsec, colnames(value)] <- value[cellIsec,]
+    if (any(is.na(full))) {
+        cli::cli_alert_warning("NA generated for missing cells.")
+    }
+    if (any(!rownames(value) %in% rownames(full))) {
+        cli::cli_alert_warning("Cells in given coordinate not found in the dataset.")
+    }
+    return(full)
+}
+
+.valid.ligerSpatialDataset <- function(object) {
+    passSuperClassCheck <- .valid.ligerDataset(object)
+    if (!isTRUE(passSuperClassCheck)) return(passSuperClassCheck)
+    coord <- object@coordinate
+    if (!is.null(coord)) {
+        barcodes.slot <- rownames(coord)
+        if (!identical(object@colnames, barcodes.slot)) {
+            return(paste0("Inconsistant cell identifiers in `coordinate` slot."))
+        }
+    }
+}
+
+setValidity("ligerSpatialDataset", .valid.ligerSpatialDataset)
+
+
+
+#' Subclass of ligerDataset for Methylation modality
+#'
+#' @description Inherits from \linkS4class{ligerDataset} class. Contained slots
+#' can be referred with the link. \code{\link{scaleNotCenter}} applied on
+#' datasets of this class will automatically be taken by reversing the
+#' normalized data instead of scaling the variable features.
+#' @exportClass ligerMethDataset
+#' @export
+ligerMethDataset <- setClass(
+    "ligerMethDataset",
+    contains = "ligerDataset"
+)
+
+.valid.ligerMethDataset <- function(object) .valid.ligerDataset(object)
+
+setValidity("ligerMethDataset", .valid.ligerMethDataset)
diff --git a/R/clustering.R b/R/clustering.R
index 8b36f690..5b153588 100644
--- a/R/clustering.R
+++ b/R/clustering.R
@@ -67,7 +67,7 @@ runCluster <- function(
         groupSingletons = TRUE,
         clusterName = paste0(method, "_cluster"),
         seed = 1,
-        verbose = getOption("ligerVerbose")
+        verbose = getOption("ligerVerbose", TRUE)
 ) {
     method <- match.arg(method)
     object <- switch(method,
@@ -77,12 +77,12 @@ runCluster <- function(
     Hsearch <- searchH(object, useRaw)
     H <- Hsearch$H
     useRaw <- Hsearch$useRaw
-    type <- ifelse(useRaw, " unnormalized ", " quantile normalized ")
+    type <- ifelse(useRaw, "unnormalized", "quantile normalized")
 
     if (!is.null(useDims)) H <- H[, useDims, drop = FALSE]
 
     if (isTRUE(verbose))
-        .log(method, " clustering on", type, "cell factor loadings...")
+        cli::cli_process_start("{method} clustering on {type} cell factor loadings...")
     knn <- RANN::nn2(H, k = nNeighbors, eps = eps)
     snn <- ComputeSNN(knn$nn.idx, prune = prune)
     if (!is.null(seed)) set.seed(seed)
@@ -110,7 +110,7 @@ runCluster <- function(
             nIterations = nIterations,
             algorithm = 1,
             randomSeed = seed,
-            printOutput = TRUE,
+            printOutput = verbose,
             edgefilename = edgeOutPath
         )
         unlink(edgeOutPath)
@@ -123,7 +123,11 @@ runCluster <- function(
                               groupSingletons = groupSingletons,
                               verbose = verbose)
     cellMeta(object, clusterName, check = FALSE) <- clusts
+    if (isTRUE(verbose))
+        cli::cli_process_done(msg_done = "{method} clustering on {type} cell factor loadings ... Found {nlevels(clusts)} clusters.")
     object@uns$defaultCluster <- object@uns$defaultCluster %||% clusterName
+    if (isTRUE(verbose))
+        cli::cli_alert_info("cellMeta variable {.field {clusterName}} is now set as default.")
     return(object)
 }
 
@@ -211,7 +215,7 @@ groupSingletons <- function(
     }
     if (!isTRUE(groupSingletons)) {
         if (isTRUE(verbose)) {
-            .log(length(singletons), " singletons identified. ")
+            cli::cli_alert_info("{length(singletons)} singletons identified.")
         }
         ids <- as.character(ids)
         ids[ids %in% singletons] <- "singleton"
@@ -243,8 +247,7 @@ groupSingletons <- function(
     }
     ids <- factor(ids)
     if (isTRUE(verbose))
-        .log(length(singletons), " singletons identified. ",
-             length(levels(ids)), " final clusters.")
+        cli::cli_alert_info("{length(singletons)} singletons identified.")
     return(ids)
 }
 
@@ -287,13 +290,13 @@ mapCellMeta <- function(
 ) {
     object <- recordCommand(object, ...)
     from <- cellMeta(object, from)
-    if (!is.factor(from)) stop("`from` must be a factor class variable.")
+    if (!is.factor(from))
+        cli::cli_abort("{.var from} must be a {.cls factor}.")
     mapping <- list(...)
     fromCats <- names(mapping)
     notFound <- fromCats[!fromCats %in% levels(from)]
     if (length(notFound) > 0) {
-        stop("The following categories requested not found: ",
-             paste0(notFound, collapse = ", "))
+        cli::cli_abort("{length(notFound)} categor{?y is/ies are} requested but not found: {.val {notFound}}")
     }
 
     toCats <- unlist(mapping)
diff --git a/R/dotplot.R b/R/dotplot.R
index 0d7c13c7..569098d7 100644
--- a/R/dotplot.R
+++ b/R/dotplot.R
@@ -290,7 +290,10 @@ plotClusterFactorDot <- function(
     )
     if (length(viridisOption) != 1 ||
         !viridisOption %in% viridisAvail)
-        stop("`viridisOption` has to be one value from the available choices.")
+        cli::cli_abort(
+            c("{.var viridisOption} has to be one value from the available choices: ",
+              "{.val {viridisAvail}}")
+        )
 
     ## Font-size specification
     # Broadcast one-param setting to each
diff --git a/R/embedding.R b/R/embedding.R
index 71aeb639..7d42dd6e 100644
--- a/R/embedding.R
+++ b/R/embedding.R
@@ -71,16 +71,19 @@ runUMAP <- function(
     Hsearch <- searchH(object, useRaw)
     H <- Hsearch$H
     useRaw <- Hsearch$useRaw
-    type <- ifelse(useRaw, " unnormalized ", " quantile normalized ")
+    type <- ifelse(useRaw, "unnormalized", "quantile normalized")
     if (isTRUE(verbose))
-        .log("Generating UMAP on", type, "cell factor loadings...")
+        cli::cli_process_start("Generating UMAP on {type} cell factor loadings...")
     if (!is.null(useDims)) H <- H[, useDims, drop = FALSE]
     umap <- uwot::umap(H,
                        n_components = as.integer(nDims),
                        metric = distance,
                        n_neighbors = as.integer(nNeighbors),
                        min_dist = minDist)
+    if (isTRUE(verbose)) cli::cli_process_done()
     dimRed(object, dimredName) <- umap
+    if (isTRUE(verbose))
+        cli::cli_alert_info("cellMeta variable {.field {dimredName}} is now set as default.")
     return(object)
 }
 
@@ -161,10 +164,9 @@ runTSNE <- function(
     Hsearch <- searchH(object, useRaw)
     H <- Hsearch$H
     useRaw <- Hsearch$useRaw
-    type <- ifelse(useRaw, " unnormalized ", " quantile normalized ")
+    type <- ifelse(useRaw, "unnormalized", "quantile normalized")
     if (isTRUE(verbose))
-        .log("Generating TSNE (", method, ") on", type,
-             "cell factor loadings...")
+        cli::cli_process_start("Generating TSNE ({method}) on {type} cell factor loadings...")
     if (!is.null(useDims)) H <- H[, useDims, drop = FALSE]
     if (method == "Rtsne") {
         set.seed(seed)
@@ -183,8 +185,11 @@ runTSNE <- function(
                           theta = theta,
                           perplexity = perplexity)
     }
+    if (isTRUE(verbose)) cli::cli_process_done()
     dimRed(object, dimredName) <- tsne
     object@uns$TSNE <- list(method = method)
+    if (isTRUE(verbose))
+        cli::cli_alert_info("cellMeta variable {.field {dimredName}} is now set as default.")
     return(object)
 }
 
diff --git a/R/factorMarker.R b/R/factorMarker.R
index 41299fc2..8ae4fc7b 100644
--- a/R/factorMarker.R
+++ b/R/factorMarker.R
@@ -66,7 +66,7 @@ getFactorMarkers <- function(
     dataset1 <- .checkUseDatasets(object, useDatasets = dataset1)
     dataset2 <- .checkUseDatasets(object, useDatasets = dataset2)
     if (any(isH5Liger(object, dataset = c(dataset1, dataset2))))
-        stop("Please use in-memory liger object for this analysis.`")
+        cli::cli_abort("Please use in-memory {.cls liger} object for this analysis")
     if (is.null(nGenes)) {
         nGenes <- length(varFeatures(object))
     }
@@ -78,11 +78,13 @@ getFactorMarkers <- function(
     }
     useFactors <- which(abs(datasetSpecificity) <= factorShareThresh)
     if (length(useFactors) == 0) {
-        stop("No factor passed the dataset specificity threshold, ",
-             "please try a larger `factorShareThresh`.")
+        cli::cli_abort(
+            c("No factor passed the dataset specificity threshold",
+              i = "please try a larger {.var factorShareThresh}.")
+        )
     }
     if (length(useFactors) == 1 && isTRUE(verbose)) {
-        warning("Only 1 factor passed the dataset specificity threshold.")
+        cli::cli_alert_warning("Only 1 factor passed the dataset specificity threshold.")
     }
 
     H <- getMatrix(object, "H", dataset = c(dataset1, dataset2))
@@ -101,10 +103,16 @@ getFactorMarkers <- function(
     W_matrices <- list()
     vargene <- varFeatures(object)
     if (isTRUE(verbose)) {
-        .log("Performing wilcoxon test between datasets \"", dataset1,
-             "\" and \"", dataset2, "\", \nbasing on factor loading.")
-        if (!isTRUE(printGenes))
-            pb <- utils::txtProgressBar(0, length(useFactors), style = 3)
+        if (isTRUE(printGenes)) {
+            cli::cli_alert_info(
+                "Performing wilcoxon test between {.val {dataset1}} and {.val {dataset2}} basing on factor loading."
+            )
+        } else {
+            cli::cli_progress_bar(
+                name = "Testing between {.val {dataset1}} and {.val {dataset2}}",
+                total = length(useFactors), type = "iter", clear = FALSE
+            )
+        }
     }
     for (j in seq_along(useFactors)) {
         i <- useFactors[j]
@@ -116,8 +124,7 @@ getFactorMarkers <- function(
         # if not max factor for any cell in either dataset
         if (sum(labels[[dataset1]] == i) <= 1 ||
             sum(labels[[dataset2]] == i) <= 1) {
-            warning("Factor ", i, " did not appear as max in ",
-                    "any cell in either dataset", immediate. = TRUE)
+            cli::cli_alert_warning("Factor {i} did not appear as max in any cell in either dataset")
             next
         }
 
@@ -164,15 +171,16 @@ getFactorMarkers <- function(
 
         if (isTRUE(verbose)) {
             if (isTRUE(printGenes)) {
-                .log("Factor ", i)
-                message("Dataset 1:\n",
+                cli::cli_h2("Factor {i}")
+                cat("Dataset 1:\n",
                         paste(topGenesV1, collapse = ", "),
                         "\nShared:\n",
                         paste(topGenesW, collapse = ", "),
                         "\nDataset 2\n",
                         paste(topGenesV2, collapse = ", "), "\n")
             } else {
-                utils::setTxtProgressBar(pb, j)
+                cli::cli_progress_update(set = j)
+                # utils::setTxtProgressBar(pb, j)
             }
         }
 
diff --git a/R/generics.R b/R/generics.R
new file mode 100644
index 00000000..5bc866b4
--- /dev/null
+++ b/R/generics.R
@@ -0,0 +1,519 @@
+#' @section Matrix access:
+#' For \code{ligerDataset} object, \code{rawData()}, \code{normData},
+#' \code{scaleData()} and \code{scaleUnsharedData()} methods are exported for
+#' users to access the corresponding feature expression matrix. Replacement
+#' methods are also available to modify the slots.
+#'
+#' For other matrices, such as the \eqn{H} and \eqn{V}, which are dataset
+#' specific, please use \code{getMatrix()} method with specifying slot name.
+#' Directly accessing slot with \code{@} is generally not recommended.
+#' @export
+#' @rdname ligerDataset-class
+setGeneric("rawData", function(x, dataset = NULL) standardGeneric("rawData"))
+
+#' @export
+#' @rdname ligerDataset-class
+setGeneric(
+    "rawData<-",
+    function(x, dataset = NULL, check = TRUE, value) standardGeneric("rawData<-")
+)
+
+#' @export
+#' @rdname ligerDataset-class
+setGeneric("normData", function(x, dataset = NULL) standardGeneric("normData"))
+
+#' @export
+#' @rdname ligerDataset-class
+setGeneric(
+    "normData<-",
+    function(x, dataset = NULL, check = TRUE, value) standardGeneric("normData<-")
+)
+
+#' @export
+#' @rdname ligerDataset-class
+setGeneric(
+    "scaleData",
+    function(x, dataset = NULL) standardGeneric("scaleData")
+)
+
+#' @export
+#' @rdname ligerDataset-class
+setGeneric(
+    "scaleData<-",
+    function(x, dataset = NULL, check = TRUE, value) standardGeneric("scaleData<-")
+)
+
+#' @export
+#' @rdname ligerDataset-class
+setGeneric(
+    "scaleUnsharedData",
+    function(x, dataset = NULL) standardGeneric("scaleUnsharedData")
+)
+
+#' @export
+#' @rdname ligerDataset-class
+setGeneric(
+    "scaleUnsharedData<-",
+    function(x, dataset = NULL, check = TRUE, value) standardGeneric("scaleUnsharedData<-")
+)
+
+#' @export
+#' @rdname ligerDataset-class
+setGeneric(
+    "getMatrix",
+    function(x, slot = "rawData", dataset = NULL, returnList = FALSE) {
+        standardGeneric("getMatrix")
+    }
+)
+
+#' @section H5 file and information access:
+#' A \code{ligerDataset} object has a slot called \code{h5fileInfo}, which is a
+#' list object. The first element is called \code{$H5File}, which is an
+#' \code{H5File} class object and is the connection to the input file. The
+#' second element is \code{$filename} which stores the absolute path of the H5
+#' file in the current machine. The third element \code{$formatType} stores the
+#' name of preset being used, if applicable. The other following keys pair with
+#' paths in the H5 file that point to specific data for constructing a feature
+#' expression matrix.
+#'
+#' \code{h5fileInfo()} method access the list described above and simply
+#' retrieves the corresponding value. When \code{info = NULL}, returns the whole
+#' list. When \code{length(info) == 1}, returns the requested list value. When
+#' more info requested, returns a subset list.
+#'
+#' The replacement method modifies the list elements and corresponding slot
+#' value (if applicable) at the same time. For example, running
+#' \code{h5fileInfo(obj, "rawData") <- newPath} not only updates the list, but
+#' also updates the \code{rawData} slot with the \code{H5D} class data at
+#' "newPath" in the \code{H5File} object.
+#'
+#' \code{getH5File()} is a wrapper and is equivalent to
+#' \code{h5fileInfo(obj, "H5File")}.
+#' @export
+#' @rdname ligerDataset-class
+setGeneric("h5fileInfo", function(x, info = NULL) standardGeneric("h5fileInfo"))
+
+#' @export
+#' @rdname ligerDataset-class
+setGeneric(
+    "h5fileInfo<-",
+    function(x, info = NULL, check = TRUE, value) {
+        standardGeneric("h5fileInfo<-")
+    }
+)
+
+
+#' @export
+#' @rdname ligerDataset-class
+setGeneric("getH5File", function(x, dataset = NULL) standardGeneric("getH5File"))
+
+#' @export
+#' @rdname ligerDataset-class
+setMethod("getH5File",
+          signature = signature(x = "ligerDataset", dataset = "missing"),
+          function(x, dataset = NULL) h5fileInfo(x, "H5File"))
+
+
+#' @section Feature metadata access:
+#' A slot \code{featureMeta} is included for each \code{ligerDataset} object.
+#' This slot requires a \code{\link[S4Vectors]{DataFrame-class}} object, which
+#' is the same as \code{cellMeta} slot of a \linkS4class{liger} object. However,
+#' the associated S4 methods only include access to the whole table for now.
+#' Internal information access follows the same way as data.frame operation.
+#' For example, \code{featureMeta(ligerD)$nCell} or
+#' \code{featureMeta(ligerD)[varFeatures(ligerObj), "gene_var"]}.
+#' @export
+#' @rdname ligerDataset-class
+setGeneric("featureMeta", function(x, check = NULL) {
+    standardGeneric("featureMeta")
+})
+
+#' @export
+#' @rdname ligerDataset-class
+setGeneric("featureMeta<-", function(x, check = TRUE, value) {
+    standardGeneric("featureMeta<-")
+})
+
+
+
+
+
+
+
+#' @section Dataset access:
+#' \code{datasets()} method only accesses the \code{datasets} slot, the list of
+#' \linkS4class{ligerDataset} objects. \code{dataset()} method accesses a single
+#' dataset, with subsequent cell metadata updates and checks bonded when adding
+#' or modifying a dataset. Therefore, when users want to modify something inside
+#' a \code{ligerDataset} while no cell metadata change should happen, it is
+#' recommended to use: \code{datasets(x)[[name]] <- ligerD} for efficiency,
+#' though the result would be the same as \code{dataset(x, name) <- ligerD}.
+#'
+#' \code{length()} and \code{names()} methods are implemented to access the
+#' number and names of datasets. \code{names<-} method is supported for
+#' modifying dataset names, with taking care of the "dataset" variable in cell
+#' metadata.
+#' @section Matrix access:
+#' For \code{liger} object, \code{rawData()}, \code{normData},
+#' \code{scaleData()} and \code{scaleUnsharedData()} methods are exported for
+#' users to access the corresponding feature expression matrix with
+#' specification of one dataset. For retrieving a type of matrix from multiple
+#' datasets, please use \code{getMatrix()} method.
+#'
+#' When only one matrix is expected to be retrieved by \code{getMatrix()}, the
+#' matrix itself will be returned. A list will be returned if multiple matrices
+#' is requested (by querying multiple datasets) or \code{returnList} is set to
+#' \code{TRUE}.
+#' @export
+#' @rdname liger-class
+setGeneric("datasets", function(x, check = NULL) standardGeneric("datasets"))
+
+#' @export
+#' @rdname liger-class
+setGeneric(
+    "datasets<-",
+    function(x, check = TRUE, value) standardGeneric("datasets<-")
+)
+
+#' @export
+#' @rdname liger-class
+setGeneric("dataset", function(x, dataset = NULL) standardGeneric("dataset"))
+
+#' @export
+#' @rdname liger-class
+setGeneric("dataset<-", function(x, dataset, type = NULL, qc = TRUE, value) {
+    standardGeneric("dataset<-")
+})
+
+
+#' @export
+#' @rdname liger-class
+#' @section Cell metadata access:
+#' Three approaches are provided for access of cell metadata. A generic function
+#' \code{cellMeta} is implemented with plenty of options and multi-variable
+#' accessibility. Besides, users can use double-bracket (e.g.
+#' \code{ligerObj[[varName]]}) or dollor-sign (e.g. \code{ligerObj$nUMI}) to
+#' access or modify single variables.
+#'
+#' For users' convenience of generating a customized ggplot with available cell
+#' metadata, the S3 method \code{fortify.liger} is implemented. With this under
+#' the hook, users can create simple ggplots by directly starting with
+#' \code{ggplot(ligerObj, aes(...))} where cell metadata variables can be
+#' directly thrown into \code{aes()}.
+#'
+#' Special partial metadata insertion is implemented specifically for mapping
+#' categorical annotation from sub-population (subset object) back to original
+#' experiment (full-size object). For example, when sub-clustering and
+#' annotation is done for a specific cell-type of cells (stored in
+#' \code{subobj}) subset from an experiment (stored as \code{obj}), users can do
+#' \code{cellMeta(obj, "sub_ann", cellIdx = colnames(subobj)) <- subobj$sub_ann}
+#' to map the value back, leaving other cells non-annotated with NAs. Plotting
+#' with this variable will then also show NA cells with default grey color.
+#' Furthermore, sub-clustering labels for other cell types can also be mapped
+#' to the same variable. For example, \code{cellMeta(obj, "sub_ann",
+#' cellIdx = colnames(subobj2)) <- subobj2$sub_ann}. As long as the labeling
+#' variables are stored as factor class (categorical), the levels (category
+#' names) will be properly handled and merged. Other situations follow the R
+#' default behavior (e.g. categories might be converted to integer numbers if
+#' mapped to numerical variable in the original object). Note that this feature
+#' is only available with using the generic function \code{cellMeta} but not
+#' with the \code{`[[`} or \code{`$`} accessing methods due to syntax reasons.
+#'
+#' The generic \code{defaultCluster} works as both getter and setter. As a
+#' setter, users can do \code{defaultCluster(obj) <- "existingVariableName"} to
+#' set a categorical variable as default cluster used for visualization or
+#' downstream analysis. Users can also do \code{defaultCluster(obj,
+#' "newVarName") <- factorOfLabels} to push new labeling into the object and set
+#' as default. For getter method, the function returns a factor object of the
+#' default cluster labeling. Argument \code{useDatasets} can be used for
+#' requiring that given or retrieved labeling should match with cells in
+#' specified datasets. We generally don't recommend setting \code{"dataset"} as
+#' a default cluster because it is a preserved (always existing) field in
+#' metadata and can lead to meaningless result when running analysis that
+#' utilizes both clustering information and the dataset source information.
+setGeneric(
+    "cellMeta",
+    function(x, columns = NULL, useDatasets = NULL, cellIdx = NULL, as.data.frame = FALSE, ...) {
+        standardGeneric("cellMeta")
+    }
+)
+
+#' @export
+#' @rdname liger-class
+setGeneric(
+    "cellMeta<-",
+    function(x, columns = NULL, useDatasets = NULL, cellIdx = NULL, inplace = FALSE, check = FALSE, value) {
+        standardGeneric("cellMeta<-")
+    }
+)
+
+#' @export
+#' @rdname liger-class
+setGeneric(
+    "defaultCluster",
+    function(x, useDatasets = NULL, ...) {
+        standardGeneric("defaultCluster")
+    }
+)
+
+#' @export
+#' @rdname liger-class
+setGeneric(
+    "defaultCluster<-",
+    function(x, name = NULL, useDatasets = NULL, ..., value) {
+        standardGeneric("defaultCluster<-")
+    }
+)
+
+#' @export
+#' @rdname liger-class
+#' @section Dimension reduction access:
+#' Currently, low-dimensional representaion of cells, presented as dense
+#' matrices, are all stored in \code{cellMeta} slot, and can totally be accessed
+#' with generics \code{cellMeta} and \code{cellMeta<-}. In addition to that,
+#' we provide specific generics \code{dimRed} and \code{dimRed<-} for getting
+#' and setting matrix like cell metadata, respectively. Adding a matrix to the
+#' object looks as simple as \code{dimRed(obj, "name") <- matrixLike}. It can
+#' be retrived back with \code{dimRed(obj, "name")}. Similar to having a default
+#' cluster labeling, we also constructed the feature of default dimRed. It can
+#' be set with \code{defaultDimRed(obj) <- "existingMatLikeVar"} and the matrix
+#' can be retrieved with \code{defaultDimRed(obj)}.
+setGeneric(
+    "dimRed",
+    function(x, name = NULL, useDatasets = NULL, ...) {
+        standardGeneric("dimRed")
+    }
+)
+
+#' @export
+#' @rdname liger-class
+setGeneric(
+    "dimRed<-",
+    function(x, name = NULL, useDatasets = NULL, ..., value) {
+        standardGeneric("dimRed<-")
+    }
+)
+
+#' @export
+#' @rdname liger-class
+setGeneric(
+    "defaultDimRed",
+    function(x, useDatasets = NULL) {
+        standardGeneric("defaultDimRed")
+    }
+)
+
+#' @export
+#' @rdname liger-class
+setGeneric(
+    "defaultDimRed<-",
+    function(x, name, useDatasets = NULL, value) {
+        standardGeneric("defaultDimRed<-")
+    }
+)
+
+#' @export
+#' @rdname liger-class
+#' @section Variable feature access:
+#' The \code{varFeatures} slot allows for character vectors of gene names.
+#' \code{varFeatures(x)} returns this vector and \code{value} for
+#' \code{varFeatures<-} method has to be a character vector or \code{NULL}.
+#' The replacement method, when \code{check = TRUE} performs checks on gene
+#' name consistency check across the \code{scaleData}, \code{H}, \code{V} slots
+#' of inner \code{ligerDataset} objects as well as the \code{W} and
+#' \code{H.norm} slots of the input \code{liger} object.
+setGeneric("varFeatures", function(x) standardGeneric("varFeatures"))
+
+#' @export
+#' @rdname liger-class
+setGeneric(
+    "varFeatures<-",
+    function(x, check = TRUE, value) standardGeneric("varFeatures<-")
+)
+
+
+
+#' @export
+#' @rdname liger-class
+setGeneric("varUnsharedFeatures", function(x, dataset = NULL) {
+    standardGeneric("varUnsharedFeatures")
+})
+
+#' @export
+#' @rdname liger-class
+setGeneric(
+    "varUnsharedFeatures<-",
+    function(x, dataset, check = TRUE, value) {
+        standardGeneric("varUnsharedFeatures<-")
+    }
+)
+
+#' @section Command records:
+#' rliger functions, that perform calculation and update the \code{liger}
+#' object, will be recorded in a \code{ligerCommand} object and stored in the
+#' \code{commands} slot, a list, of \code{liger} object. Method
+#' \code{commands()} is implemented to retrieve or show the log history.
+#' Running with \code{funcName = NULL} (default) returns all command labels.
+#' Specifying \code{funcName} allows partial matching to all command labels
+#' and returns a subset list (of \code{ligerCommand} object) of matches (or
+#' the \code{ligerCommand} object if only one match found). If \code{arg} is
+#' further specified, a subset list of parameters from the matches will be
+#' returned. For example, requesting a list of resolution values used in
+#' all louvain cluster attempts: \code{commands(ligerObj, "louvainCluster",
+#' "resolution")}
+#' @export
+#' @rdname liger-class
+setGeneric(
+    "commands",
+    function(x, funcName = NULL, arg = NULL) standardGeneric("commands")
+)
+
+
+
+
+
+
+
+
+
+
+#' Access ligerSpatialDataset coordinate data
+#' @description Similar as how default \linkS4class{ligerDataset} data is
+#' accessed.
+#' @param x \linkS4class{ligerSpatialDataset} object or a \linkS4class{liger}
+#' object.
+#' @param dataset Name or numeric index of an spatial dataset.
+#' @param check Logical, whether to perform object validity check on setting new
+#' value.
+#' @param value \code{\link{matrix}}.
+#' @return The retrieved coordinate matrix or the updated \code{x} object.
+#' @rdname coordinate
+#' @export
+setGeneric("coordinate", function(x, dataset) standardGeneric("coordinate"))
+
+#' @rdname coordinate
+#' @export
+setGeneric("coordinate<-", function(x, dataset, check = TRUE, value) standardGeneric("coordinate<-"))
+
+
+
+
+#' Access ligerATACDataset peak data
+#' @description Similar as how default \linkS4class{ligerDataset} data is
+#' accessed.
+#' @param x \linkS4class{ligerATACDataset} object or a \linkS4class{liger}
+#' object.
+#' @param dataset Name or numeric index of an ATAC dataset.
+#' @param check Logical, whether to perform object validity check on setting new
+#' value.
+#' @param value \code{\link[Matrix]{dgCMatrix-class}} matrix.
+#' @return The retrieved peak count matrix or the updated \code{x} object.
+#' @rdname peak
+#' @export
+setGeneric("rawPeak", function(x, dataset) standardGeneric("rawPeak"))
+
+#' @rdname peak
+#' @export
+setGeneric("rawPeak<-", function(x, dataset, check = TRUE, value) standardGeneric("rawPeak<-"))
+
+#' @rdname peak
+#' @export
+setGeneric("normPeak", function(x, dataset) standardGeneric("normPeak"))
+
+#' @rdname peak
+#' @export
+setGeneric("normPeak<-", function(x, dataset, check = TRUE, value) standardGeneric("normPeak<-"))
+
+
+
+
+
+
+#' Converting other classes of data to a liger object
+#' @description
+#' This function converts data stored in SingleCellExperiment (SCE), Seurat
+#' object or a merged sparse matrix (dgCMatrix) into a liger object. This is
+#' designed for a container object or matrix that already contains multiple
+#' datasets to be integerated with LIGER. For individual datasets, please use
+#' \code{\link{createLiger}} instead.
+#' @export
+#' @param object Object.
+#' @param datasetVar Specify the dataset belonging by: 1. Select a variable from
+#' existing metadata in the object (e.g. colData column); 2. Specify a
+#' vector/factor that assign the dataset belonging. 3. Give a single character
+#' string which means that all data is from one dataset (must not be a metadata
+#' variable, otherwise it is understood as 1.). Default \code{NULL} gathers
+#' things into one dataset and names it "sample" for dgCMatrix, attempts
+#' to find variable "sample" from SCE or "orig.ident" from Seurat.
+#' @param modal Modality setting for each dataset. See
+#' \code{\link{createLiger}}.
+#' @param ... Additional arguments passed to \code{\link{createLiger}}
+#' @details
+#' For Seurat V5 structure, it is highly recommended that users make use of its
+#' split layer feature, where things like "counts", "data", and "scale.data"
+#' can be held for each dataset in the same Seurat object, e.g. with
+#' "count.ctrl", "count.stim", not merged. If a Seurat object with split layers
+#' is given, \code{datasetVar} will be ignored and the layers will be directly
+#' used.
+#' @return a \linkS4class{liger} object.
+#' @rdname as.liger
+#' @examples
+#' # dgCMatrix (common sparse matrix class), usually obtained from other
+#' # container object, and contains multiple samples merged in one.
+#' matList <- rawData(pbmc)
+#' multiSampleMatrix <- mergeSparseAll(matList)
+#' # The `datasetVar` argument expects the variable assigning the sample source
+#' pbmc2 <- as.liger(multiSampleMatrix, datasetVar = pbmc$dataset)
+#' pbmc2
+#'
+#' \donttest{
+#' sce <- SingleCellExperiment::SingleCellExperiment(
+#'     assays = list(counts = multiSampleMatrix)
+#' )
+#' sce$sample <- pbmc$dataset
+#' pbmc3 <- as.liger(sce, datasetVar = "sample")
+#' pbmc3
+#'
+#' seu <- SeuratObject::CreateSeuratObject(multiSampleMatrix)
+#' # Seurat creates variable "orig.ident" by identifying the cell barcode
+#' # prefixes, which is indeed what we need in this case. Users might need
+#' # to be careful and have it confirmed first.
+#' pbmc4 <- as.liger(seu, datasetVar = "orig.ident")
+#' pbmc4
+#'
+#' # As per Seurat V5 updates with layered data, specifically helpful udner the
+#' # scenario of dataset integration. "counts" and etc for each datasets can be
+#' # split into layers.
+#' seu5 <- seu
+#' seu5[["RNA"]] <- split(seu5[["RNA"]], pbmc$dataset)
+#' print(SeuratObject::Layers(seu5))
+#' pbmc5 <- as.liger(seu5)
+#' }
+as.liger <- function(object, ...) UseMethod("as.liger", object)
+
+#' Converting other classes of data to a as.ligerDataset object
+#' @description
+#' Works for converting a matrix or container object to a single ligerDataset,
+#' and can also convert the modality preset of a ligerDataset. When used with
+#' a dense matrix object, it automatically converts the matrix to sparse form
+#' (\code{\link[Matrix]{dgCMatrix-class}}). When used with container objects
+#' such as Seurat or SingleCellExperiment, it is highly recommended that the
+#' object contains only one dataset/sample which is going to be integrated with
+#' LIGER. For multi-sample objects, please use \code{\link{as.liger}} with
+#' dataset source variable specified.
+#' @export
+#' @param object Object.
+#' @param modal Modality setting for each dataset. Choose from \code{"default"},
+#' \code{"rna"}, \code{"atac"}, \code{"spatial"}, \code{"meth"}.
+#' @param ... Additional arguments passed to \code{\link{createLigerDataset}}
+#' @return a \linkS4class{liger} object.
+#' @rdname as.ligerDataset
+#' @examples
+#' ctrl <- dataset(pbmc, "ctrl")
+#' ctrl
+#' # Convert the modality preset
+#' as.ligerDataset(ctrl, modal = "atac")
+#' rawCounts <- rawData(ctrl)
+#' class(rawCounts)
+#' as.ligerDataset(rawCounts)
+as.ligerDataset <- function(object, ...) UseMethod("as.ligerDataset", object)
diff --git a/R/ggplotting.R b/R/ggplotting.R
index 3bf6c7e8..1cfdb6ab 100644
--- a/R/ggplotting.R
+++ b/R/ggplotting.R
@@ -143,13 +143,13 @@ plotCellScatter <- function(
     }
 
     plotList <- list()
-    titles <- .checkArgLen(titles, n = length(plotDFList), .stop = FALSE)
+    titles <- .checkArgLen(titles, n = length(plotDFList), class = "ANY", .stop = FALSE)
     for (i in seq_along(plotDFList)) {
-        .log("Plotting feature: ", names(plotDFList)[i], ", on ",
-             nrow(plotDFList[[i]]), " cells...")
+        cliID <- cli::cli_process_start("Plotting feature {.val {names(plotDFList)[i]}} on {.val {nrow(plotDFList[[i]])}} cells")
         plotList[[i]] <- .ggScatter(plotDF = plotDFList[[i]], x = x, y = y,
                                     colorBy = colorByParam[[i]],
                                     shapeBy = shapeBy, title = titles[i], ...)
+        cli::cli_process_done(cliID)
     }
     names(plotList) <- names(plotDFList)
 
@@ -450,7 +450,7 @@ plotCellViolin <- function(
         names(yParam) <- names(plotDFList)
     }
     plotList <- list()
-    titles <- .checkArgLen(titles, n = length(plotDFList), .stop = FALSE)
+    titles <- .checkArgLen(titles, n = length(plotDFList), class = "ANY", .stop = FALSE)
     for (i in seq_along(plotDFList)) {
         plotList[[i]] <- .ggCellViolin(plotDF = plotDFList[[i]],
                                        y = yParam[[i]], groupBy = groupBy,
@@ -799,11 +799,14 @@ plotCellViolin <- function(
     }
 
     if (isTRUE(plotly)) {
-        if (requireNamespace("plotly", quietly = FALSE)) {
+        if (requireNamespace("plotly", quietly = TRUE)) {
             plot <- plotly::ggplotly(plot)
         } else {
-            warning('Run `install.packages("plotly")` to enable web based ',
-                    "interactive browsing. Returning original ggplot.")
+            cli::cli_alert_danger(
+                "Package {.pkg plotly} is needed for interactive browsing."
+            )
+            cli::cli_alert_info("Please run {.code install.packages('plotly')} to enable it.")
+            cli::cli_alert_info("Returning the original {.cls ggplot}.")
         }
     }
     return(plot)
diff --git a/R/h5Utility.R b/R/h5Utility.R
index 7f38a995..e2a8d861 100644
--- a/R/h5Utility.R
+++ b/R/h5Utility.R
@@ -56,8 +56,12 @@ H5Apply <- function(
     colptr <- h5file[[h5meta$indptrName]]
     rowind <- h5file[[h5meta$indicesName]]
     data <- h5file[[h5meta[[useData]]]]
-    if (isTRUE(verbose)) pb <- utils::txtProgressBar(0, numChunks, style = 3)
+    if (isTRUE(verbose))
+        cliID <- cli::cli_progress_bar(name = "HDF5 chunk processing", type = "iter",
+                                       total = numChunks, clear = FALSE)
+        # pb <- utils::txtProgressBar(0, numChunks, style = 3)
     for (i in seq(numChunks)) {
+        Sys.sleep(0.1)
         start <- (i - 1)*chunkSize + 1
         end <- if (i*chunkSize > ncol(object)) ncol(object) else i*chunkSize
         colptrStart <- start
@@ -78,7 +82,8 @@ H5Apply <- function(
         init <- do.call(FUN, c(list(chunk, nnzStart:nnzEnd,
                                     start:end, init),
                                fun.args))
-        if (isTRUE(verbose)) utils::setTxtProgressBar(pb, i)
+        # if (isTRUE(verbose)) utils::setTxtProgressBar(pb, i)
+        if (isTRUE(verbose)) cli::cli_progress_update(id = cliID, set = i)
     }
     # Break a new line otherwise next message comes right after the "%" sign.
     if (isTRUE(verbose)) cat("\n")
@@ -182,7 +187,7 @@ safeH5Create <- function(object,
 #' lig <- restoreH5Liger(lig)
 restoreH5Liger <- function(object, filePath = NULL) {
     if (!inherits(object, "liger") && !inherits(object, "ligerDataset")) {
-        stop("Please specify a liger or ligerDataset object to restore.")
+        cli::cli_abort("Please specify a {.cls liger} or {.cls ligerDataset} object to restore.")
     }
     if (inherits(object, "ligerDataset")) {
         if (isTRUE(methods::validObject(object, test = TRUE))) {
@@ -191,13 +196,12 @@ restoreH5Liger <- function(object, filePath = NULL) {
         h5.meta <- h5fileInfo(object)
         if (is.null(filePath)) filePath <- h5.meta$filename
         if (is.null(filePath)) {
-            stop("No filename identified")
+            cli::cli_abort("No filename identified.")
         }
         if (!file.exists(filePath)) {
-            stop("HDF5 file path does not exist:\n",
-                 filePath)
+            cli::cli_abort("HDF5 file path does not exist: {.file {filePath}}")
         }
-        .log("filename identified: ", filePath)
+        cliID <- cli::cli_process_start("Restoring HDF5 link from: {.file {filePath}}")
         h5file <- hdf5r::H5File$new(filePath, mode = "r+")
         h5.meta$filename <- h5file$filename
         pathChecks <- unlist(lapply(h5.meta[4:10], function(x) {
@@ -207,18 +211,23 @@ restoreH5Liger <- function(object, filePath = NULL) {
         if (any(!pathChecks)) {
             info.name <- names(pathChecks)[!pathChecks]
             paths <- unlist(h5.meta[info.name])
-            errorMsg <- paste(paste0('HDF5 info "', info.name,
-                                     '" not found at path: "', paths, '"'),
-                              collapse = "\n  ")
-            stop(errorMsg)
+            errMsg_cli <- paste0("HDF5 info {.val ", info.name, "} not found at path: {.val ", paths, "}")
+            lapply(errMsg_cli, cli::cli_alert_danger)
+            cli::cli_abort(
+                "Cannot restore this dataset."
+            )
+            # errorMsg <- paste(paste0('HDF5 info "', info.name,
+            #                          '" not found at path: "', paths, '"'),
+            #                   collapse = "\n  ")
+            # stop(errorMsg)
         }
         barcodes <- h5file[[h5.meta$barcodesName]]
         if (identical(barcodes, colnames(object))) {
-            stop("Barcodes in the HDF5 file do not match to object.")
+            cli::cli_abort("Barcodes in the HDF5 file do not match to object.")
         }
         features <- h5file[[h5.meta$genesName]]
         if (identical(features, rownames(object))) {
-            stop("Features in the HDF5 file do not match to object.")
+            cli::cli_abort("Features in the HDF5 file do not match to object.")
         }
         # All checks passed!
         h5.meta$H5File <- h5file
@@ -230,25 +239,27 @@ restoreH5Liger <- function(object, filePath = NULL) {
             scaleData(object, check = FALSE) <- h5file[[h5.meta$scaleData]]
         }
         methods::validObject(object)
+        cli::cli_process_done(id = cliID)
     } else {
         # Working for liger object
         if (!is.null(filePath)) {
             if (!is.list(filePath) || is.null(names(filePath)))
-                stop("`filePath` has to be a named list for liger object.")
+                cli::cli_abort(
+                    "{.var filePath} has to be named list of {.cls liger} objects."
+                )
         }
         for (d in names(object)) {
             if (isH5Liger(object, d)) {
                 path <- NULL
                 if (d %in% names(filePath)) {
-                    if (!hdf5r::is.h5file(filePath[[d]]))
-                        warning("Path for dataset \"", d,
-                                "\" is not an HDF5 file: ",
-                                filePath[[d]])
-                    else path <- filePath[[d]]
+                    if (!hdf5r::is.h5file(filePath[[d]])) {
+                        cli::cli_alert_danger("Path for dataset {.val {d}} is not an HDF5 file: {.file {filePath[[d]]}}")
+                    } else path <- filePath[[d]]
                 }
-                .log("Restoring dataset \"", d, "\"")
+                cliID <- cli::cli_process_start("Restoring dataset {.val {d}}")
                 datasets(object, check = FALSE)[[d]] <-
                     restoreH5Liger(dataset(object, d), filePath[[d]])
+                cli::cli_process_done(id = cliID)
             }
         }
     }
@@ -270,7 +281,7 @@ restoreOnlineLiger <- function(object, file.path = NULL) {
 
 .inspectH5Path <- function(path) {
     if (length(path) != 1 || !is.character(path)) {
-        stop("`path` has to be a single character.")
+        cli::cli_abort("{.var path} has to be a single {.cls character}.")
     }
     path <- trimws(path, whitespace = "/")
     path <- strsplit(path, "/")[[1]]
diff --git a/R/heatmap.R b/R/heatmap.R
index c746eb27..b016f240 100644
--- a/R/heatmap.R
+++ b/R/heatmap.R
@@ -225,7 +225,10 @@ plotFactorHeatmap <- function(
     )
     if (length(viridisOption) != 1 ||
         !viridisOption %in% viridisAvail)
-        stop("`viridisOption` has to be one value from the available choices.")
+        cli::cli_abort(
+            c("{.var viridisOption} has to be one value from the available choices: ",
+              "{.val {viridisAvail}}")
+        )
 
     ## Font-size specification
     # Broadcast one-param setting to each
@@ -391,9 +394,9 @@ plotFactorHeatmap <- function(
                 if (var %in% names(colList)) {
                     df[[var]] <- droplevels(df[[var]])
                     if (any(!levels(df[[var]]) %in% names(colList[[var]]))) {
-                        stop("Given customized annotation color must have ",
-                             "names matching to all available levels in the ",
-                             "annotation.")
+                        cli::cli_abort(
+                            "Given customized annotation color must have names matching to all available levels in the annotation."
+                        )
                     }
                     annCol[[var]] <- colList[[var]][levels(df[[var]])]
                 } else {
diff --git a/R/import.R b/R/import.R
index 571aa616..84d96313 100644
--- a/R/import.R
+++ b/R/import.R
@@ -83,12 +83,12 @@ createLiger <- function(
                         indices.name = "indicesName",
                         indptr.name = "indptrName", genes.name = "genesName",
                         barcodes.name = "barcodesName"))
-    if (!is.list(rawData)) stop("`rawData` has to be a named list.")
+    if (!is.list(rawData)) cli::cli_abort("{.var rawData} has to be a named list.")
 
     nData <- length(rawData)
     if (missing(modal) || is.null(modal)) modal <- "default"
     modal <- tolower(modal)
-    modal <- .checkArgLen(modal, nData, repN = TRUE)
+    modal <- .checkArgLen(modal, nData, repN = TRUE, class = "character")
 
     # TODO handle h5 specific argument for hybrid of H5 and in memory stuff.
     datasets <- list()
@@ -188,9 +188,8 @@ createLigerDataset <- function(
     args <- as.list(environment())
     additional <- list(...)
     # Necessary initialization of slots
-    if (is.null(rawData) && is.null(normData) && is.null(scaleData)) {
-        stop("At least one type of expression data (rawData, normData or ",
-             "scaleData) has to be provided")
+    if (is.null(rawData) && is.null(normData)) {
+        cli::cli_abort("At least one of {.field rawData} or {.field normData} has to be provided.")
     }
     # Look for proper colnames and rownames
     cn <- NULL
@@ -291,8 +290,7 @@ createH5LigerDataset <- function(
             genesName <- "raw.var"
             genes <- h5file[[genesName]][]
         } else {
-            stop("Specified `formatType` '", formatType,
-                 "' is not supported for now.")
+            cli::cli_abort("Specified {.var formatType} ({.val {formatType}}) is not supported for now.")
         }
     } else {
         barcodes <- h5file[[barcodesName]][]
@@ -373,22 +371,23 @@ readLiger <- function(
         h5FilePath = NULL,
         update = TRUE) {
     obj <- readRDS(filename)
-    if (!inherits(obj, "liger"))
-        stop("Object is not of class \"liger\".")
+    if (!inherits(obj, "liger")) # nocov start
+        cli::cli_abort("Object is not of class {.cls liger}.") # nocov end
     ver <- obj@version
     if (ver >= package_version("1.99.0")) {
         if (isH5Liger(obj)) obj <- restoreH5Liger(obj)
         return(obj)
     }
-    .log("Older version (", ver, ") of liger object detected.")
+    cli::cli_alert_info("Older version ({.val {ver}}) of {.cls liger} object detected.")
     if (isTRUE(update)) {
-        .log("Updating the object structure to make it compatible ",
-             "with current version (", utils::packageVersion("rliger2"), ")")
+        cli::cli_alert_info(
+            "Updating the object structure to make it compatible with current version {.val {utils::packageVersion('rliger2')}}"
+        )
         return(convertOldLiger(obj, dimredName = dimredName,
                                clusterName = clusterName,
                                h5FilePath = h5FilePath))
     } else {
-        .log("`update = FALSE` specified. Returning the original object.")
+        cli::cli_alert_info("{.code update = FALSE} specified. Returning the original object.")
         return(obj)
     }
 }
@@ -451,12 +450,15 @@ importPBMC <- function(
     for (i in seq(nrow(info))) {
         f <- info$filename[i]
         if (file.exists(f) && isFALSE(overwrite)) {
-            warning("File already exists, skipped. set `overwrite = TRUE` ",
-                    "to force downloading: ", f)
+            cli::cli_alert_warning(
+                "Skipping file already exists at: {.file {f}}. "
+            )
+            cli::cli_alert_info("Set {.code overwrite = TRUE} to forcing download.")
             doDownload[i] <- FALSE
             next
         }
-        if (isTRUE(verbose)) .log("Downloading from ", info$url[i], " to ", f)
+        if (isTRUE(verbose))
+            cli::cli_alert_info("Downloading from {.url {info$url[i]}} to {.file {f}}")
     }
     if (sum(doDownload) > 0) {
         utils::download.file(info$url[doDownload],
@@ -500,12 +502,15 @@ importBMMC <- function(
     for (i in seq(nrow(info))) {
         f <- info$filename[i]
         if (file.exists(f) && isFALSE(overwrite)) {
-            warning("File already exists, skipped. set `overwrite = TRUE` ",
-                    "to force downloading: ", f)
+            cli::cli_alert_warning(
+                "Skipping file already exists at: {.file {f}}. "
+            )
+            cli::cli_alert_info("Set {.code overwrite = TRUE} to forcing download.")
             doDownload[i] <- FALSE
             next
         }
-        if (isTRUE(verbose)) .log("Downloading from ", info$url[i], " to ", f)
+        if (isTRUE(verbose))
+            cli::cli_alert_info("Downloading from {.url {info$url[i]}} to {.file {f}}")
     }
     if (sum(doDownload) > 0) {
         utils::download.file(info$url[doDownload],
@@ -548,12 +553,15 @@ importCGE <- function(
     for (i in seq(nrow(info))) {
         f <- info$filename[i]
         if (file.exists(f) && isFALSE(overwrite)) {
-            warning("File already exists, skipped. set `overwrite = TRUE` ",
-                    "to force downloading: ", f)
+            cli::cli_alert_warning(
+                "Skipping file already exists at: {.file {f}}. "
+            )
+            cli::cli_alert_info("Set {.code overwrite = TRUE} to forcing download.")
             doDownload[i] <- FALSE
             next
         }
-        if (isTRUE(verbose)) .log("Downloading from ", info$url[i], " to ", f)
+        if (isTRUE(verbose))
+            cli::cli_alert_info("Downloading from {.url {info$url[i]}} to {.file {f}}")
     }
     if (sum(doDownload) > 0) {
         utils::download.file(info$url[doDownload],
@@ -708,34 +716,38 @@ read10X <- function(
                 if (is.null(reference)) {
                     if (length(refsExist) == 1) {
                         reference <- refsExist
-                        .log("Using reference: ", reference)
+                        cli::cli_alert_info("Using referece {.val {reference}}")
                     } else {
-                        stop("Multiple references found, please select one ",
-                             "from: ", paste0(refsExist, collapse = ", "))
+                        cli::cli_abort(
+                            "Multiple references found, please select one from: {.val {refsExist}}"
+                        )
                     }
                 } else if (length(reference) == 1) {
                     if (!reference %in% refsExist) {
-                        stop("Specified reference not found, please select ",
-                             "one from: ", paste0(refsExist, collapse = ", "))
+                        cli::cli_abort(
+                            "Specified reference not found, please select one from: {.val {refsExist}}"
+                        )
                     }
                 } else {
-                    stop("Multiple reference specified but only one allowed.")
+                    cli::cli_abort("Multiple reference specified but only one allowed.")
                 }
                 path <- file.path(path, reference)
             }
             names(path) <- dirSampleNames
-            .log("Found the following sample folders with possible sub-folder ",
-                 "structure: \n", paste0(dirSampleNames, collapse = ", "))
+            cli::cli_alert_info(
+                c("Found the following sample folders with possible sub-folder structure: ",
+                  "{.val {dirSampleNames}}")
+            )
         } # else mtxDirs
     } # else mtxDirs
 
     allData <- list()
-    sampleNames <- .checkArgLen(sampleNames, length(path), repN = FALSE)
+    sampleNames <- .checkArgLen(sampleNames, length(path), repN = FALSE, class = "character")
     if (is.null(sampleNames) && !is.null(names(path))) {
         sampleNames <- names(path)
     } else {
         if (any(duplicated(sampleNames))) {
-            stop("Cannot set duplicated sample names.")
+            cli::cli_abort("Cannot set duplicated sample names.")
         }
     }
 
@@ -743,14 +755,13 @@ read10X <- function(
         if (isTRUE(verbose)) {
             name <- sampleNames[i]
             if (is.null(name)) name <- paste0("sample ", i)
-            .log("Reading from ", name, "...")
+            cliID <- cli::cli_process_start("Reading from {.val {name}}")
         }
         if (is.list(path)) run <- path[[i]]
         else run <- path[i]
 
         if (!dir.exists(run)) {
-            stop("Directory provided does not exist: ",
-                 normalizePath(run, mustWork = FALSE))
+            cli::cli_abort("Directory provided does not exist: {.file {normalizePath(run, mustWork = FALSE)}}")
         }
         barcode.loc <- file.path(run, 'barcodes.tsv')
         gene.loc <- file.path(run, 'genes.tsv')
@@ -764,15 +775,13 @@ read10X <- function(
             matrix.loc <- addgz(matrix.loc)
         }
         if (!file.exists(barcode.loc)) {
-            stop("Barcode file missing. Expecting ", basename(barcode.loc))
+            cli::cli_abort("Barcode file is missing. Expecting {.file {barcode.loc}}")
         }
         if (!isOldVer && !file.exists(features.loc) ) {
-            stop("Gene name or features file missing. Expecting ",
-                 basename(features.loc))
+            cli::cli_abort("Gene name or features file is missing. Expecting {.file {features.loc}}")
         }
         if (!file.exists(matrix.loc)) {
-            stop("Expression matrix file missing. Expecting ",
-                 basename(matrix.loc))
+            cli::cli_abort("Expression matrix file is missing. Expecting {.file {matrix.loc}}")
         }
         data <- read10XFiles(matrixPath = matrix.loc, barcodesPath = barcode.loc,
                              featuresPath = ifelse(isOldVer, gene.loc, features.loc),
@@ -780,6 +789,7 @@ read10X <- function(
                              cellCol = cellCol)
         if (isOldVer) names(data) <- "Gene Expression"
         allData[[i]] <- data
+        if (isTRUE(verbose)) cli::cli_process_done(id = cliID)
     }
     if (!is.null(sampleNames)) names(allData) <- sampleNames
     if (isTRUE(returnList)) return(allData)
@@ -858,23 +868,25 @@ read10XATAC <- function(
             # Now paths are sample/outs/*_peak_bc_matrix/
             path <- file.path(outsPaths, subdir)
             if (!dir.exists(path)) {
-                stop("Cannot find folder '", path, "', not standard ",
-                     "`cellranger-", pipeline, "` output. ",
-                     "Please try with the other `pipeline`.")
+                cli::cli_abort(
+                    c("Cannot find folder {.file {path}}, not standard {.code cellranger-{pipeline}} output. ",
+                      "i" = "Please try with the other {.code pipeline}.")
+                )
             }
             names(path) <- dirSampleNames
-            .log("Found the following sample folders with possible sub-folder ",
-                 "structure: \n", paste0(dirSampleNames, collapse = ", "))
+            cli::cli_alert_info(
+                "Found the following sample folders with possible sub-folder structure: {.val {dirSampleNames}}"
+            )
         } # else mtxDirs
     } # else mtxDirs
 
     allData <- list()
-    sampleNames <- .checkArgLen(sampleNames, length(path), repN = FALSE)
+    sampleNames <- .checkArgLen(sampleNames, length(path), repN = FALSE, class = "character")
     if (is.null(sampleNames) && !is.null(names(path))) {
         sampleNames <- names(path)
     } else {
         if (any(duplicated(sampleNames))) {
-            stop("Cannot set duplicated sample names.")
+            cli::cli_abort("Cannot set duplicated sample names.")
         }
     }
 
@@ -882,14 +894,13 @@ read10XATAC <- function(
         if (isTRUE(verbose)) {
             name <- sampleNames[i]
             if (is.null(name)) name <- paste0("sample ", i)
-            .log("Reading from ", name, "...")
+            cliID <- cli::cli_process_start("Reading from {.val {name}}")
         }
         if (is.list(path)) run <- path[[i]]
         else run <- path[i]
 
         if (!dir.exists(run)) {
-            stop("Directory provided does not exist: ",
-                 normalizePath(run, mustWork = FALSE))
+            cli::cli_abort("Directory provided does not exist: {.file {normalizePath(run, mustWork = FALSE)}}")
         }
         barcode.loc <- switch(pipeline,
                               arc = "barcodes.tsv.gz",
@@ -904,15 +915,13 @@ read10XATAC <- function(
         )
 
         if (!file.exists(barcode.loc)) {
-            stop("Barcode file missing. Expecting ", basename(barcode.loc))
+            cli::cli_abort("Barcode file is missing. Expecting {.file {barcode.loc}}")
         }
         if (!file.exists(feature.loc) ) {
-            stop("Peak or feature file missing. Expecting ",
-                 basename(feature.loc))
+            cli::cli_abort("Peak or feature file is missing. Expecting {.file {feature.loc}}")
         }
         if (!file.exists(matrix.loc)) {
-            stop("Expression matrix file missing. Expecting ",
-                 basename(matrix.loc))
+            cli::cli_abort("Expression matrix file is missing. Expecting {.file {matrix.loc}}")
         }
         data <- read10XFiles(matrixPath = matrix.loc,
                              barcodesPath = barcode.loc,
@@ -921,16 +930,18 @@ read10XATAC <- function(
                              geneCol = geneCol, cellCol = cellCol,
                              isATAC = pipeline == "atac")
         if (pipeline == "arc" && !arcFeatureType %in% names(data)) {
-            stop("No ATAC data retrieved from cellranger-arc pipeline. ",
-                 "Please see if the following available feature types match ",
-                 "with need and select one for `arcFeatureType`: ",
-                 paste0(names(data), collapse = ", "))
+            cli::cli_abort(
+                c("No ATAC data retrieved from cellranger-arc pipeline. ",
+                "Please see if the following available feature types match ",
+                "with need and select one for `arcFeatureType`: {.val {names(data)}}")
+            )
         }
         data <- switch(pipeline,
                        arc = data[[arcFeatureType]],
                        atac = data[[1]]
         )
         allData[[i]] <- data
+        cli::cli_process_done(id = cliID)
     }
     if (!is.null(sampleNames)) names(allData) <- sampleNames
     if (isTRUE(returnList)) return(allData)
@@ -984,16 +995,14 @@ read10XFiles <- function(
                            "-", feature.names[, 3])
     } else {
         if (ncol(feature.names) < geneCol) {
-            stop("`geneCol` was set to ", geneCol, " but feature.tsv.gz ",
-                 "(or genes.tsv) only has ", ncol(feature.names), " columns.",
-                 " Try setting `geneCol` to a value <= ",
-                 ncol(feature.names), ".")
+            cli::cli_abort(
+                c("{.var geneCol} was set to {.val {geneCol}} but {.file feature.tsv.gz} (or {.file genes.tsv}) only has {ncol(fetures.names)} columns.",
+                  "i" = "Try setting {.var geneCol} to a value <= {ncol(feature.names)}.")
+            )
         }
         if (any(is.na(feature.names[, geneCol]))) {
-            warning(
-                "Some features names are NA. Replacing NA names with ID from the ",
-                "opposite column requested",
-                call. = FALSE, immediate. = TRUE
+            cli::cli_alert_warning(
+                "Some feature names are NA. Replacing NA names with ID from the opposite column requested"
             )
             na.features <- which(is.na(feature.names[, geneCol]))
             replacement.column <- ifelse(geneCol == 2, 1, 2)
@@ -1009,8 +1018,9 @@ read10XFiles <- function(
         data_types <- factor(feature.names$V3)
         lvls <- levels(data_types)
         if (length(lvls) > 1) {
-            .log("10X data contains more than one type and is being ",
-                 "returned as a list containing matrices of each type.")
+            cli::cli_alert_warning(
+                "10X data contains more than one type and is being returned as a list containing matrices of each type."
+            )
         }
         expr_name <- "Gene Expression"
         # Return Gene Expression first
diff --git a/R/integration.R b/R/integration.R
index ac37b71b..41130fd6 100644
--- a/R/integration.R
+++ b/R/integration.R
@@ -243,14 +243,12 @@ runINMF.liger <- function(
     object <- removeMissing(object, orient = "cell", verbose = verbose)
     data <- lapply(datasets(object), function(ld) {
         if (is.null(scaleData(ld)))
-            stop("Scaled data not available. ",
-                 "Run `scaleNotCenter(object)` first")
+            cli::cli_abort("Scaled data not available. Run {.fn scaleNotCenter} first.")
         return(scaleData(ld))
     })
     dataClasses <- sapply(data, function(x) class(x)[1])
     if (!all(dataClasses == dataClasses[1])) {
-        stop("Currently the scaledData of all datasets have to be of the ",
-             "same class.")
+        cli::cli_abort("Currently the scaledData of all datasets have to be of the same class.")
     }
     out <- .runINMF.list(
         object = data,
@@ -326,8 +324,8 @@ runINMF.Seurat <- function(
     }
     for (i in seq_along(Es)) {
         if (any(Es[[i]]@x < 0)) {
-            stop("Negative data encountered for integrative Non-negative ",
-                 "Matrix Factorization. Please run `scaleNotCenter()` first.")
+            cli::cli_abort("Negative data encountered for integrative {.emph Non-negative} Matrix Factorization.
+                           Please run {.fn scaleNotCenter} first.")
         }
     }
 
@@ -380,27 +378,23 @@ runINMF.Seurat <- function(
         features = NULL
 ) {
     if (!requireNamespace("RcppPlanc", quietly = TRUE)) # nocov start
-        stop("RcppPlanc installation required. Currently, please get the ",
-             "GitHub private repository access from the lab and run: \n",
-             "devtools::install_github(\"welch-lab/RcppPlanc\")") # nocov end
+        cli::cli_abort(
+        "Package {.pkg RcppPlanc} is required for iNMF integration.
+        Please install it by command:
+        {.code devtools::install_github('welch-lab/RcppPlanc')}") # nocov end
 
     bestResult <- list()
     bestObj <- Inf
     bestSeed <- seed
     for (i in seq(nRandomStarts)) {
         if (isTRUE(verbose) && nRandomStarts > 1) {
-            .log("Replicate run ", i, "...")
+            cli::cli_alert_info("Replicate run [{i}/{nRandomStarts}]")
         }
         set.seed(seed = seed + i - 1)
-        if (inherits(object[[1]], "H5D")) {
-            # RcppPlanc::bppinmf_h5dense()
-            stop("TODO: Push Yichen to test bppinmf_h5sparse/bppinmf_h5dense!")
-        } else {
-            out <- RcppPlanc::inmf(objectList = object, k = k, lambda = lambda,
-                                   niter = nIteration, Hinit = HInit,
-                                   Vinit = VInit, Winit = WInit,
-                                   verbose = verbose)
-        }
+        out <- RcppPlanc::inmf(objectList = object, k = k, lambda = lambda,
+                               niter = nIteration, Hinit = HInit,
+                               Vinit = VInit, Winit = WInit,
+                               verbose = verbose)
         if (out$objErr < bestObj) {
             bestResult <- out
             bestObj <- out$objErr
@@ -408,7 +402,7 @@ runINMF.Seurat <- function(
         }
     }
     if (isTRUE(verbose) && nRandomStarts > 1) {
-        .log("Best objective error: ", bestObj, "\nBest seed: ", bestSeed)
+        cli::cli_alert_success("Best objective error: {bestObj}; Best seed: {bestSeed}")
     }
     barcodeList <- lapply(object, colnames)
     features <- rownames(object[[1]])
@@ -684,7 +678,7 @@ runOnlineINMF.liger <- function(
     Es <- lapply(datasets(object), function(ld) {
         sd <- scaleData(ld)
         if (is.null(sd))
-            stop("Scaled data not available. Run `scaleNotCenter()` first")
+            cli::cli_abort("Scaled data not available. Run {.fn scaleNotCenter} first.")
         # if (inherits(sd, "H5D")) return(.H5DToH5Mat(sd))
         # else
         if (inherits(sd, "H5Group"))
@@ -699,19 +693,20 @@ runOnlineINMF.liger <- function(
         BInit <- BInit %||% getMatrix(object, "B", returnList = TRUE)
         if (is.null(WInit) || any(sapply(VInit, is.null)) ||
             any(sapply(AInit, is.null)) || any(sapply(BInit, is.null))) {
-            stop("Cannot find complete online iNMF result for current ",
-                 "datasets. Please run `runOnlineINMF()` without `newDataset` ",
-                 "first.")
+            cli::cli_abort(
+                "Cannot find complete online iNMF result for current datasets.
+                Please run {.fn runOnlineINMF} without {.code newDataset} first"
+            )
         }
 
         newNames <- names(newDatasets)
         if (any(newNames %in% names(object))) {
-            stop("Names of `newDatasets` overlap with existing datasets.")
+            cli::cli_abort("Names of {.var newDatasets} overlap with existing datasets.")
         }
         if (is.list(newDatasets)) {
             # A list of raw data
             if (is.null(names(newDatasets))) {
-                stop("The list of new datasets must be named.")
+                cli::cli_abort("The list of new datasets must be named.")
             }
             for (i in seq_along(newDatasets)) {
                 if (inherits(newDatasets[[i]], "dgCMatrix")) {
@@ -721,14 +716,14 @@ runOnlineINMF.liger <- function(
                     ld <- createH5LigerDataset(newDatasets[[i]])
                     dataset(object, names(newDatasets[i])) <- ld
                 } else {
-                    stop("Cannot interpret `newDatasets` element ", i)
+                    cli::cli_abort("Cannot interpret {.var newDatasets} element {i}")
                 }
             }
         } else if (inherits(newDatasets, "liger")) {
             # A liger object with all new datasets
             object <- c(object, newDatasets)
         } else {
-            stop("`newDatasets` must be either a named list or a liger object")
+            cli::cli_abort("{.var newDatasets} must be either a named list or a {.cls liger} object")
         }
 
         object <- normalize(object, useDatasets = newNames)
@@ -807,27 +802,16 @@ runOnlineINMF.liger <- function(
         ...
 ) {
     if (!requireNamespace("RcppPlanc", quietly = TRUE)) # nocov start
-        stop("RcppPlanc installation required. Currently, please get the ",
-             "GitHub private repository access from the lab and run: \n",
-             "devtools::install_github(\"welch-lab/RcppPlanc\")") # nocov end
+        cli::cli_abort(
+            "Package {.pkg RcppPlanc} is required for online iNMF integration.
+        Please install it by command:
+        {.code devtools::install_github('welch-lab/RcppPlanc')}") # nocov end
     nDatasets <- length(object) + length(newDatasets)
     barcodeList <- c(lapply(object, colnames), lapply(newDatasets, colnames))
     names(barcodeList) <- c(names(object), names(newDatasets))
     features <- rownames(object[[1]])
     if (!is.null(seed)) set.seed(seed)
 
-    # # If minibatchSize > smallest invovled dataset, auto reset with warning
-    # minibatchSize_min <- min(sapply(object, ncol))
-    # if (!is.null(newDatasets)) {
-    #     minibatchSize_min2 <- min(sapply(newDatasets, ncol))
-    #     minibatchSize_min <- min(minibatchSize_min, minibatchSize_min2)
-    # }
-    # if (minibatchSize > minibatchSize_min) {
-    #     warning("Minibatch size larger than the smallest dataset involved.\n",
-    #             "  Setting to the smallest dataset size: ", minibatchSize_min,
-    #             immediate. = TRUE)
-    #     minibatchSize <- minibatchSize_min
-    # }
     res <- RcppPlanc::onlineINMF(objectList = object, newDatasets = newDatasets,
                                  project = projection, k = k, lambda = lambda,
                                  maxEpoch = maxEpochs,
@@ -901,8 +885,8 @@ runOnlineINMF.Seurat <- function(
     }
     for (i in seq_along(Es)) {
         if (any(Es[[i]]@x < 0)) {
-            stop("Negative data encountered for integrative Non-negative ",
-                 "Matrix Factorization. Please run `scaleNotCenter()` first.")
+            cli::cli_abort("Negative data encountered for integrative {.emph Non-negative} Matrix Factorization.
+                           Please run {.fn scaleNotCenter} first.")
         }
     }
 
@@ -1147,15 +1131,15 @@ runUINMF.liger <- function(
 
     Elist <- lapply(datasets(object), function(ld) {
         if (is.null(scaleData(ld)))
-            stop("Scaled data not available. ",
-                 "Run `scaleNotCenter(object)` first")
+            cli::cli_abort("Scaled data not available. Run {.fn scaleNotCenter} first.")
         return(scaleData(ld))
     })
     Ulist <- getMatrix(object, "scaleUnsharedData", returnList = TRUE)
     if (all(sapply(Ulist, is.null))) {
-        stop("No scaled data for unshared feature found. Run `selectGenes()` ",
-             "with `useUnsharedDatasets` specified, ",
-             "and then `scaleNotCenter()`.")
+        cli::cli_abort(
+            "No scaled data for unshared feature found. Run {.fn selectGenes}
+            with {.code useUnsharedDatasets} specified, and then {.fn scaleNotCenter}."
+        )
     }
     res <- .runUINMF.list(Elist, Ulist, k = k, lambda = lambda,
                           nIteration = nIteration,
@@ -1187,10 +1171,16 @@ runUINMF.liger <- function(
         seed = 1,
         verbose = getOption("ligerVerbose")
 ) {
+    if (!requireNamespace("RcppPlanc", quietly = TRUE)) # nocov start
+        cli::cli_abort(
+        "Package {.pkg RcppPlanc} is required for mosaic iNMF integration with unshared features.
+        Please install it by command:
+        {.code devtools::install_github('welch-lab/RcppPlanc')}")# nocov end
     bestObj <- Inf
     bestRes <- NULL
     bestSeed <- NULL
     for (i in seq(nRandomStarts)) {
+        cli::cli_alert_info("Replicate start [{i}/{nRandomStarts}]")
         seed <- seed + i - 1
         set.seed(seed)
         res <- RcppPlanc::uinmf(object, unsharedList, k = k, lambda = lambda,
@@ -1202,7 +1192,7 @@ runUINMF.liger <- function(
         }
     }
     if (isTRUE(verbose) && nRandomStarts > 1) {
-        .log("Best objective error: ", bestObj, "\nBest seed: ", bestSeed)
+        cli::cli_alert_success("Best objective error: {bestObj}; Best seed: {bestSeed}")
     }
     rm(res)
     features <- rownames(object[[1]])
@@ -1323,8 +1313,9 @@ quantileNorm.liger <- function(
     .checkValidFactorResult(object, checkV = FALSE)
     reference <- reference %||% names(which.max(sapply(datasets(object), ncol)))
     reference <- .checkUseDatasets(object, useDatasets = reference)
-    if (length(reference) != 1)
-        stop("Should specify only one reference dataset.")
+    if (length(reference) != 1) {
+        cli::cli_abort("Should specify only one reference dataset.")
+    }
     object <- recordCommand(object, ..., dependencies = "RANN")
     out <- .quantileNorm.HList(
         object = getMatrix(object, "H"),
@@ -1369,7 +1360,7 @@ quantileNorm.Seurat <- function(
     resName <- paste0(reduction, "Norm")
     reduction <- object[[reduction]]
     if (!inherits(reduction, "DimReduc")) {
-        stop("Specified `reduction` does not points to a DimReduc.")
+        cli::cli_abort("Specified {.var reduction} does not points to a {.cls DimReduc}.")
     }
     # Retrieve some information. Might have better ways instead of using `@`
     ## Due to proper formatting in Seurat object, Hconcat is already cell x k
@@ -1416,19 +1407,15 @@ quantileNorm.Seurat <- function(
     set.seed(seed)
     if (is.character(reference)) {
         if (length(reference) != 1 || !reference %in% names(object))
-            stop("Should specify one existing dataset as reference. ",
-                 "(character `reference` wrong length or not found)")
+            cli::cli_abort("Should specify one existing dataset as reference.")
     } else if (is.numeric(reference)) {
         if (length(reference) != 1 || reference > length(object))
-            stop("Should specify one dataset within the range. ",
-                 "(numeric `reference` wrong length or out of bound)")
+            cli::cli_abort("Should specify one existing dataset as reference.")
     } else if (is.logical(reference)) {
         if (length(reference) != length(object) || sum(reference) != 1)
-            stop("Should specify one dataset within the range. ",
-                 "(logical `reference` wrong length or ",
-                 "too many selection)")
+            cli::cli_abort("Should specify one existing dataset as reference.")
     } else {
-        stop("Unable to understand `reference`. See `?quantileNorm`.")
+        cli::cli_abort("Unable to understand {.var reference}. See {.code ?quantileNorm}.")
     }
     useDims <- useDims %||% seq_len(nrow(object[[1]]))
     # Transposing all H to cell x k
diff --git a/R/liger-class.R b/R/liger-methods.R
similarity index 60%
rename from R/liger-class.R
rename to R/liger-methods.R
index b1af5db9..bb11127f 100644
--- a/R/liger-class.R
+++ b/R/liger-methods.R
@@ -1,164 +1,3 @@
-setClassUnion("dgCMatrix_OR_NULL", c("dgCMatrix", "NULL"))
-setClassUnion("matrix_OR_NULL", c("matrix", "NULL"))
-setClassUnion("matrixLike_OR_NULL", c(
-    "matrix", "dgCMatrix", "dgTMatrix", "dgeMatrix", "NULL"
-))
-setClassUnion("character_OR_NULL", c("character", "NULL"))
-setClassUnion("matrixLike", c(
-    "matrix", "dgCMatrix", "dgTMatrix", "dgeMatrix"
-))
-setClassUnion("Number_or_NULL", c("integer", "numeric", "NULL"))
-
-setClassUnion("dataframe", c("data.frame", "DataFrame", "NULL", "missing"))
-
-#' @title liger class
-#' @rdname liger-class
-#' @docType class
-#' @description \code{liger} object is the main data container for LIGER
-#' analysis in R. The slot \code{datasets} is a list where each element should
-#' be a \linkS4class{ligerDataset} object containing dataset specific
-#' information, such as the expression matrices. The other parts of liger object
-#' stores information that can be shared across the analysis, such as the cell
-#' metadata and factorization result matrices.
-#'
-#' This manual provides explanation to the \code{liger} object structure as well
-#' as usage of class-specific methods. Please see detail sections for more
-#' information.
-#'
-#' For \code{liger} objects created with older versions of rliger package,
-#' please try updating the objects individually with
-#' \code{\link{convertOldLiger}}.
-#' @slot datasets list of \linkS4class{ligerDataset} objects. Use generic
-#' \code{dataset}, \code{dataset<-}, \code{datasets} or \code{datasets<-} to
-#' interact with. See detailed section accordingly.
-#' @slot cellMeta \linkS4class{DFrame} object for cell metadata. Pre-existing
-#' metadata, QC metrics, cluster labeling, low-dimensional embedding and etc.
-#' are all stored here. Use generic \code{cellMeta}, \code{cellMeta<-},
-#' \code{$}, \code{[[]]} or \code{[[]]<-} to interact with. See detailed section
-#' accordingly.
-#' @slot varFeatures Character vector of feature names. Use generic
-#' \code{varFeatures} or \code{varFeatures<-} to interact with. See detailed
-#' section accordingly.
-#' @slot W Matrix of gene loading for each factor. See
-#' \code{\link{runIntegration}}.
-#' @slot H.norm Matrix of aligned factor loading for each cell. See
-#' \code{\link{quantileNorm}} and \code{\link{runIntegration}}.
-#' @slot commands List of \linkS4class{ligerCommand} objects. Record of
-#' analysis. Use \code{commands} to retrieve information. See detailed section
-#' accordingly.
-#' @slot uns List for unstructured meta-info of analyses or presets.
-#' @slot version Record of version of rliger2 package
-#' @importClassesFrom S4Vectors DataFrame
-#' @importFrom ggplot2 fortify
-liger <- setClass(
-    "liger",
-    representation(
-        datasets = "list",
-        cellMeta = "DataFrame",
-        varFeatures = "character_OR_NULL",
-        W = "matrix_OR_NULL",
-        H.norm = "matrix_OR_NULL",
-        uns = "list",
-        commands = "list",
-        version = "ANY"
-    ),
-    methods::prototype(
-        cellMeta = methods::new("DFrame"),
-        version = utils::packageVersion("rliger2")
-    )
-)
-
-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-# Validity ####
-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-.checkAllDatasets <- function(x) {
-    for (ld in datasets(x)) {
-        methods::validObject(ld)
-    }
-    return(NULL)
-}
-
-.checkLigerBarcodes <- function(x) {
-    bcFromDatasets <- unlist(lapply(datasets(x), colnames), use.names = FALSE)
-    if (!identical(colnames(x), bcFromDatasets)) {
-        return("liger object barcodes do not match to barcodes in datasets")
-    }
-    if (!is.null(x@H.norm)) {
-        if (!identical(rownames(x@H.norm), bcFromDatasets)) {
-            return("H.norm barcodes do not match to barcodes in datasets.")
-        }
-    }
-    if (!"dataset" %in% names(cellMeta(x))) {
-        return("`datasets` variable missing in cellMeta(x)")
-    }
-    datasetNamesFromDatasets <- rep(names(x), lapply(datasets(x), ncol))
-    names(datasetNamesFromDatasets) <- NULL
-
-    if (!identical(datasetNamesFromDatasets, as.character(x$dataset))) {
-        return("names of datasets do not match
-               `datasets` variable in cellMeta")
-    }
-    return(NULL)
-}
-
-.checkLigerVarFeature <- function(x) {
-    if (!is.null(varFeatures(x)) &&
-        length(varFeatures(x)) > 0) {
-        if (!is.null(x@W))
-            if (!identical(rownames(x@W), varFeatures(x)))
-                return("Variable features do not match dimension of W matrix")
-        for (d in names(x)) {
-            ld <- dataset(x, d)
-            if (!is.null(ld@V)) {
-                if (!identical(rownames(ld@V), varFeatures(x)))
-                    return(paste("Variable features do not match dimension",
-                                 "of V matrix in dataset", d))
-            }
-
-            if (!is.null(scaleData(ld))) {
-                if (!isH5Liger(ld)) {
-                    if (!identical(rownames(scaleData(ld)), varFeatures(x)))
-                        return(paste("Variable features do not match dimension",
-                                     "of scaleData in dataset", d))
-                } else {
-                    if (inherits(scaleData(ld), "H5D")) {
-                        if (scaleData(ld)$dims[1] != length(varFeatures(x)))
-                            return(paste("Variable features do not match ",
-                                         "dimension of scaleData in dataset ",
-                                         "(H5)", d))
-                    } else if (inherits(scaleData(ld), "H5Group")) {
-                        if (scaleData(ld)[["featureIdx"]]$dims != length(varFeatures(x))) {
-                            return(paste("Variable features do not match ",
-                                         "dimension of scaleData in dataset ",
-                                         "(H5)", d))
-                        }
-                        scaleDataIdx <- scaleData(ld)[["featureIdx"]][]
-                        if (!identical(rownames(ld)[scaleDataIdx], varFeatures(x))) {
-                            return("HDF5 scaled data feature index does not ",
-                                   "match variable features")
-                        }
-                    }
-                }
-            }
-        }
-    }
-    return(NULL)
-}
-
-.valid.liger <- function(object) {
-    # message("Checking liger object validity")
-    res <- .checkAllDatasets(object)
-    if (!is.null(res)) return(res)
-    res <- .checkLigerBarcodes(object)
-    if (!is.null(res)) return(res)
-    res <- .checkLigerVarFeature(object)
-    if (!is.null(res)) return(res)
-    # TODO more checks
-}
-
-setValidity("liger", .valid.liger)
-
 #' Check if given liger object if under new implementation
 #' @param object A liger object
 #' @return \code{TRUE} if the version of \code{object} is later than or equal to
@@ -191,10 +30,6 @@ is.newLiger <- function(object) {
 #' \code{NULL} uses all cells.
 #' @param as.data.frame Logical, whether to apply
 #' \code{\link[base]{as.data.frame}} on the subscription. Default \code{FALSE}.
-#' @param i,j Feature and cell index for \code{`[`} method. For \code{`[[`}
-#' method, use a single variable name with \code{i} while \code{j} is not
-#' applicable.
-#' @param drop Not applicable.
 #' @param slot Name of slot to retrieve matrix from. Options shown in Usage.
 #' @param returnList Logical, whether to force return a list even when only one
 #' dataset-specific matrix (i.e. expression matrices, H, V or U) is requested.
@@ -276,6 +111,16 @@ setMethod(
 #' with \code{NULL} as the first element and valid cell identifiers as the
 #' second element. For \code{colnames<-} method, the character vector of cell
 #' identifiers. \code{rownames<-} method is not applicable.
+#' @section Subsetting:
+#' For more detail of subsetting a \code{liger} object or a
+#' \linkS4class{ligerDataset} object, please check out \code{\link{subsetLiger}}
+#' and \code{\link{subsetLigerDataset}}. Here, we set the S4 method
+#' "single-bracket" \code{[} as a quick wrapper to subset a \code{liger} object.
+#' Note that \code{j} serves as cell subscriptor which can be any valid index
+#' refering the collection of all cells (i.e. \code{rownames(cellMeta(obj))}).
+#' While \code{i}, the feature subscriptor can only be character vector because
+#' the features for each dataset can vary. \code{...} arugments are passed to
+#' \code{subsetLiger} so that advanced options are allowed.
 #' @rdname liger-class
 #' @export
 setMethod("dim", "liger", function(x) {
@@ -306,77 +151,51 @@ setReplaceMethod("dimnames", c("liger", "list"), function(x, value) {
 #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 # Subsetting ####
 #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#' @section Subsetting:
-#' For more detail of subsetting a \code{liger} object or a
-#' \linkS4class{ligerDataset} object, please check out \code{\link{subsetLiger}}
-#' and \code{\link{subsetLigerDataset}}. Here, we set the S4 method
-#' "single-bracket" \code{[} as a quick wrapper to subset a \code{liger} object.
-#' Note that \code{j} serves as cell subscriptor which can be any valid index
-#' refering the collection of all cells (i.e. \code{rownames(cellMeta(obj))}).
-#' While \code{i}, the feature subscriptor can only be character vector because
-#' the features for each dataset can vary. \code{...} arugments are passed to
-#' \code{subsetLiger} so that advanced options are allowed.
-#' @export
-#' @rdname liger-class
-setMethod(
-    "[",
-    signature(x = "liger", i = "character", j = "missing"),
-    function(x, i, j, ...) subsetLiger(x, featureIdx = i, cellIdx = NULL, ...)
-)
-
-#' @export
-#' @rdname liger-class
-setMethod(
-    "[",
-    signature(x = "liger", i = "missing", j = "index"),
-    function(x, i, j, ...) subsetLiger(x, featureIdx = NULL, cellIdx = j, ...)
-)
 
+#' Subset liger with brackets
+#' @name sub-liger
+#' @param x A \linkS4class{liger} object
+#' @param i Feature subscriptor, passed to \code{featureIdx} of
+#' \code{\link{subsetLiger}}.
+#' @param j Cell subscriptor, passed to \code{cellIdx} of
+#' \code{\link{subsetLiger}}.
+#' @param ... Additional arguments passed to \code{\link{subsetLiger}}.
 #' @export
-#' @rdname liger-class
-setMethod(
-    "[",
-    signature(x = "liger", i = "character", j = "index"),
-    function(x, i, j, ...) subsetLiger(x, featureIdx = i, cellIdx = j, ...)
-)
+#' @return Subset of \code{x} with specified features and cells.
+#' @seealso \code{\link{subsetLiger}}
+#' @method [ liger
+#' @examples
+#' pbmcPlot[varFeatures(pbmcPlot)[1:10], 1:10]
+`[.liger` <- function(x, i, j, ...) {
+    if (missing(i)) i <- NULL
+    if (missing(j)) j <- NULL
+    subsetLiger(x, featureIdx = i, cellIdx = j, ...)
+}
+# setMethod(
+#     "[",
+#     signature(x = "liger", i = "character", j = "missing"),
+#     function(x, i, j, ...) subsetLiger(x, featureIdx = i, cellIdx = NULL, ...)
+# )
+#
+# #' @export
+# #' @rdname liger-class
+# setMethod(
+#     "[",
+#     signature(x = "liger", i = "missing", j = "index"),
+#     function(x, i, j, ...) subsetLiger(x, featureIdx = NULL, cellIdx = j, ...)
+# )
+#
+# #' @export
+# #' @rdname liger-class
+# setMethod(
+#     "[",
+#     signature(x = "liger", i = "character", j = "index"),
+#     function(x, i, j, ...) subsetLiger(x, featureIdx = i, cellIdx = j, ...)
+# )
 
 #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 # Datasets ####
 #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#' @section Dataset access:
-#' \code{datasets()} method only accesses the \code{datasets} slot, the list of
-#' \linkS4class{ligerDataset} objects. \code{dataset()} method accesses a single
-#' dataset, with subsequent cell metadata updates and checks bonded when adding
-#' or modifying a dataset. Therefore, when users want to modify something inside
-#' a \code{ligerDataset} while no cell metadata change should happen, it is
-#' recommended to use: \code{datasets(x)[[name]] <- ligerD} for efficiency,
-#' though the result would be the same as \code{dataset(x, name) <- ligerD}.
-#'
-#' \code{length()} and \code{names()} methods are implemented to access the
-#' number and names of datasets. \code{names<-} method is supported for
-#' modifying dataset names, with taking care of the "dataset" variable in cell
-#' metadata.
-#' @section Matrix access:
-#' For \code{liger} object, \code{rawData()}, \code{normData},
-#' \code{scaleData()} and \code{scaleUnsharedData()} methods are exported for
-#' users to access the corresponding feature expression matrix with
-#' specification of one dataset. For retrieving a type of matrix from multiple
-#' datasets, please use \code{getMatrix()} method.
-#'
-#' When only one matrix is expected to be retrieved by \code{getMatrix()}, the
-#' matrix itself will be returned. A list will be returned if multiple matrices
-#' is requested (by querying multiple datasets) or \code{returnList} is set to
-#' \code{TRUE}.
-#' @export
-#' @rdname liger-class
-setGeneric("datasets", function(x, check = NULL) standardGeneric("datasets"))
-
-#' @export
-#' @rdname liger-class
-setGeneric(
-    "datasets<-",
-    function(x, check = TRUE, value) standardGeneric("datasets<-")
-)
 
 #' @export
 #' @rdname liger-class
@@ -403,15 +222,7 @@ setReplaceMethod("datasets", signature(x = "liger", check = "missing"),
                      x
                  })
 
-#' @export
-#' @rdname liger-class
-setGeneric("dataset", function(x, dataset = NULL) standardGeneric("dataset"))
 
-#' @export
-#' @rdname liger-class
-setGeneric("dataset<-", function(x, dataset, type = NULL, qc = TRUE, value) {
-    standardGeneric("dataset<-")
-})
 
 #' @export
 #' @rdname liger-class
@@ -420,8 +231,7 @@ setMethod("dataset", signature(x = "liger", dataset = "character_OR_NULL"),
               if (is.null(dataset)) return(datasets(x)[[1]])
               else {
                   if (!dataset %in% names(x)) {
-                      stop('Specified dataset name "', dataset,
-                           '" not found in liger object.')
+                      cli::cli_abort("Specified dataset name {.val {dataset}} not found in {.cls liger} object")
                   }
                   return(datasets(x)[[dataset]])
               }
@@ -491,6 +301,7 @@ setMethod("dataset", signature(x = "liger", dataset = "numeric"),
     }
     return(newDF)
 }
+
 .expandDataFrame <- function(df, idx) {
     dfList <- as.list(df)
     dfList <- lapply(dfList, function(x, idx) {
@@ -532,7 +343,7 @@ setReplaceMethod("dataset", signature(x = "liger", dataset = "character",
                      x@cellMeta <- cm
                      # x@W is genes x k, no need to worry
                      if (!is.null(x@H.norm)) {
-                         message("Filling in NAs to H.norm matrix")
+                         cli::cli_alert_info("Finning in NAs to H.norm matrix")
                          H.normNew <- matrix(
                              NA, ncol(value), ncol(x@H.norm),
                              dimnames = list(colnames(value), NULL))
@@ -568,22 +379,24 @@ setReplaceMethod("dataset", signature(x = "liger", dataset = "character",
 
 #' @export
 #' @rdname liger-class
-setReplaceMethod("dataset", signature(x = "liger", dataset = "character",
-                                      type = "missing", qc = "ANY",
-                                      value = "NULL"),
-                 function(x, dataset, type = NULL, qc = TRUE, value) {
-                     if (!dataset %in% names(x)) {
-                         warning("Specified dataset name not found in ",
-                                 "liger object. Nothing would happen.")
-                     } else {
-                         idxToRemove <- x$dataset == dataset
-                         x@datasets[[dataset]] <- NULL
-                         x@cellMeta <- x@cellMeta[!idxToRemove, , drop = FALSE]
-                         x@H.norm <- x@H.norm[!idxToRemove, , drop = FALSE]
-                         x@cellMeta$dataset <- droplevels(x@cellMeta$dataset)
-                     }
-                     x
-                 })
+setReplaceMethod(
+    "dataset",
+    signature(x = "liger", dataset = "character", type = "missing", qc = "ANY",
+              value = "NULL"),
+    function(x, dataset, type = NULL, qc = TRUE, value) {
+        if (!dataset %in% names(x)) {
+            cli::cli_alert_warning(
+                "Specified dataset name {.val {dataset}} not found in {.cls liger} object. Nothing would happen.")
+        } else {
+            idxToRemove <- x$dataset == dataset
+            x@datasets[[dataset]] <- NULL
+            x@cellMeta <- x@cellMeta[!idxToRemove, , drop = FALSE]
+            x@H.norm <- x@H.norm[!idxToRemove, , drop = FALSE]
+            x@cellMeta$dataset <- droplevels(x@cellMeta$dataset)
+        }
+        x
+    }
+)
 
 #' @rdname liger-class
 #' @export
@@ -622,66 +435,6 @@ setMethod("length", signature(x = "liger"), function(x) {
 #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 # Cell metadata ####
 #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#' @export
-#' @rdname liger-class
-#' @section Cell metadata access:
-#' Three approaches are provided for access of cell metadata. A generic function
-#' \code{cellMeta} is implemented with plenty of options and multi-variable
-#' accessibility. Besides, users can use double-bracket (e.g.
-#' \code{ligerObj[[varName]]}) or dollor-sign (e.g. \code{ligerObj$nUMI}) to
-#' access or modify single variables.
-#'
-#' For users' convenience of generating a customized ggplot with available cell
-#' metadata, the S3 method \code{fortify.liger} is implemented. With this under
-#' the hook, users can create simple ggplots by directly starting with
-#' \code{ggplot(ligerObj, aes(...))} where cell metadata variables can be
-#' directly thrown into \code{aes()}.
-#'
-#' Special partial metadata insertion is implemented specifically for mapping
-#' categorical annotation from sub-population (subset object) back to original
-#' experiment (full-size object). For example, when sub-clustering and
-#' annotation is done for a specific cell-type of cells (stored in
-#' \code{subobj}) subset from an experiment (stored as \code{obj}), users can do
-#' \code{cellMeta(obj, "sub_ann", cellIdx = colnames(subobj)) <- subobj$sub_ann}
-#' to map the value back, leaving other cells non-annotated with NAs. Plotting
-#' with this variable will then also show NA cells with default grey color.
-#' Furthermore, sub-clustering labels for other cell types can also be mapped
-#' to the same variable. For example, \code{cellMeta(obj, "sub_ann",
-#' cellIdx = colnames(subobj2)) <- subobj2$sub_ann}. As long as the labeling
-#' variables are stored as factor class (categorical), the levels (category
-#' names) will be properly handled and merged. Other situations follow the R
-#' default behavior (e.g. categories might be converted to integer numbers if
-#' mapped to numerical variable in the original object). Note that this feature
-#' is only available with using the generic function \code{cellMeta} but not
-#' with the \code{`[[`} or \code{`$`} accessing methods due to syntax reasons.
-#'
-#' The generic \code{defaultCluster} works as both getter and setter. As a
-#' setter, users can do \code{defaultCluster(obj) <- "existingVariableName"} to
-#' set a categorical variable as default cluster used for visualization or
-#' downstream analysis. Users can also do \code{defaultCluster(obj,
-#' "newVarName") <- factorOfLabels} to push new labeling into the object and set
-#' as default. For getter method, the function returns a factor object of the
-#' default cluster labeling. Argument \code{useDatasets} can be used for
-#' requiring that given or retrieved labeling should match with cells in
-#' specified datasets. We generally don't recommend setting \code{"dataset"} as
-#' a default cluster because it is a preserved (always existing) field in
-#' metadata and can lead to meaningless result when running analysis that
-#' utilizes both clustering information and the dataset source information.
-setGeneric(
-    "cellMeta",
-    function(x, columns = NULL, useDatasets = NULL, cellIdx = NULL, as.data.frame = FALSE, ...) {
-        standardGeneric("cellMeta")
-    }
-)
-
-#' @export
-#' @rdname liger-class
-setGeneric(
-    "cellMeta<-",
-    function(x, columns = NULL, useDatasets = NULL, cellIdx = NULL, check = FALSE, value) {
-        standardGeneric("cellMeta<-")
-    }
-)
 
 .subsetCellMeta <- function(
         object,
@@ -696,8 +449,8 @@ setGeneric(
     if (!is.null(columns)) {
         notFound <- !columns %in% colnames(res)
         if (any(notFound)) {
-            warning("Specified variables from cellMeta not found: ",
-                    .nfstr(columns, colnames(res)))
+            cli::cli_alert_danger(
+                "Specified variables from cellMeta not found: {.val {columns[notFound]}}")
             columns <- columns[!notFound]
         }
         res <- res[, columns, ...]
@@ -713,7 +466,7 @@ setGeneric(
         cellIdx <- .idxCheck(object, idx = cellIdx, orient = "cell")
         if (is.vector(res) || is.factor(res)) res <- res[cellIdx]
         else if (!is.null(dim(res))) res <- res[cellIdx, , ...]
-        else stop("Result before idx subscription corrupted")
+        else cli::cli_abort("Result before idx subscription corrupted")
     }
     return(res)
 }
@@ -774,26 +527,64 @@ setReplaceMethod(
 
 #' @export
 #' @rdname liger-class
+#' @param inplace For \code{cellMeta<-} method, when \code{columns} is for
+#' existing variable and \code{useDatasets} or \code{cellIdx} indicate partial
+#' insertion to the object, whether to by default (\code{TRUE}) in-place insert
+#' \code{value} into the variable for selected cells or to replace the whole
+#' variable with non-selected part left as NA.
 setReplaceMethod(
     "cellMeta",
     signature(x = "liger", columns = "character"),
-    function(x, columns = NULL, useDatasets = NULL, cellIdx = NULL, check = FALSE, value) {
+    function(x, columns = NULL, useDatasets = NULL, cellIdx = NULL,
+             inplace = TRUE, check = FALSE, value) {
+        # 1 - check cell selection
         if (is.null(cellIdx) && !is.null(useDatasets)) {
             if (!is.character(useDatasets)) useDatasets <- names(x)[useDatasets]
             cellIdx <- which(x@cellMeta$dataset %in% useDatasets)
         } else {
             cellIdx <- .idxCheck(x, cellIdx, "cell")
         }
+        if (length(cellIdx) == 0)
+            cli::cli_abort("No cell selected with either {.val cellIdx} or {.var useDatasets}.")
+
+        # 2 - check value matching or length/dimension
+        barcodes <- colnames(x)[cellIdx]
         if (is.null(dim(value))) {
             # Vector/factor like
-            value <- .checkArgLen(value, n = length(cellIdx))
-        }
-        # if (is.null(dim(value)) && length(value) != length(cellIdx)) {
-        #     stop("Length of value does not match with cell index.")
-        # }
-        if (!is.null(dim(value)) && nrow(value) != length(cellIdx)) {
-            stop("nrow of value does not match with cell index.")
+            if (is.null(names(value))) {
+                # No name matching, require exact length
+                value <- .checkArgLen(value, n = length(cellIdx), class = c("vector", "factor"))
+            } else {
+                if (!all(barcodes %in% names(value))) {
+                    cli::cli_abort(
+                        c("{.code names(value)} do not contain all cells selected. ",
+                          "These are not involved: ",
+                          "{.val {barcodes[!barcodes %in% names(value)]}}")
+                    )
+                }
+                value <- value[barcodes]
+            }
+        } else {
+            # matrix like
+            if (is.null(rownames(value))) {
+                # no rowname matching, require extact nrow
+                if (nrow(value) != length(cellIdx)) {
+                    cli::cli_abort(
+                        "{.code nrow(value)} ({nrow(value)}) does not match with cells selected ({length(cellIdx)}).")
+                }
+            } else {
+                if (!all(barcodes %in% rownames(value))) {
+                    cli::cli_abort(
+                        c("{.code rownames(value)} do not contain all cells selected. ",
+                          "These are not involved: ",
+                          "{.val {barcodes[!barcodes %in% rownames(value)]}}")
+                    )
+                }
+                value <- value[barcodes, , drop = FALSE]
+            }
         }
+
+        # 3 - Insert value
         if (length(cellIdx) == ncol(x)) {
             x@cellMeta[[columns]] <- value
         } else if (length(cellIdx) < ncol(x)) {
@@ -811,65 +602,322 @@ setReplaceMethod(
                     } else {
                         x@cellMeta[[columns]][cellIdx] <- value
                     }
-                    if (!is.null(names(value))) {
-                        if (!identical(colnames(x)[cellIdx], names(value))) {
-                            warning("Names of inserted values do not ",
-                                    "match to cell IDs at specified index ",
-                                    "of the object. Forced to store using ",
-                                    "object colnames.")
-                        }
-                    }
                 } else {
                     # matrix like
-                    x@cellMeta[[columns]] <- matrix(NA, ncol(x), ncol(value))
+                    x@cellMeta[[columns]] <- matrix(
+                        NA, ncol(x), ncol(value),
+                        dimnames = list(colnames(x), colnames(value))
+                    )
                     x@cellMeta[[columns]][cellIdx,] <- value
-                    if (!is.null(colnames(value))) {
-                        colnames(x@cellMeta[[columns]]) <- colnames(value)
-                    }
-                    if (!is.null(rownames(value))) {
-                        if (!identical(rownames(value), colnames(x)[cellIdx])) {
-                            warning("Rownames of inserted values do not match ",
-                                    "to cell IDs at specified index of the ",
-                                    "object. Forced to store using object ",
-                                    "colnames.")
-                        }
-                    }
                 }
             } else {
-                if (is.null(dim(value)) && is.null(dim(x@cellMeta[[columns]]))) {
-                    # Both are 1D
-                    if (is.factor(value) && is.factor(x@cellMeta[[columns]])) {
-                        charVar <- as.character(x@cellMeta[[columns]])
-                        charVar[cellIdx] <- as.character(value)
-                        x@cellMeta[[columns]] <-
-                            factor(
-                                charVar,
-                                levels = unique(c(levels(x@cellMeta[[columns]]),
-                                                  levels(value)))
-                            )
+                if (isTRUE(inplace)) {
+                    # Modifying existing variable
+                    if (is.null(dim(value)) && is.null(dim(x@cellMeta[[columns]]))) {
+                        # Both are 1-D
+                        if (is.factor(value) && is.factor(x@cellMeta[[columns]])) {
+                            charVar <- as.character(x@cellMeta[[columns]])
+                            charVar[cellIdx] <- as.character(value)
+                            x@cellMeta[[columns]] <-
+                                factor(
+                                    charVar,
+                                    levels = unique(c(levels(x@cellMeta[[columns]]),
+                                                      levels(value)))
+                                )
+                        } else {
+                            x@cellMeta[[columns]][cellIdx] <- value
+                        }
+                    } else if (!is.null(dim(value)) && !is.null(dim(x@cellMeta[[columns]]))) {
+                        # Both are dimensional
+                        if (ncol(value) != ncol(x@cellMeta[[columns]])) {
+                            cli::cli_abort("Cannot insert value to a variable of different dimensionality")
+                        }
+                        x@cellMeta[[columns]][cellIdx,] <- value
                     } else {
-                        x@cellMeta[[columns]][cellIdx] <- value
+                        cli::cli_abort("Cannot insert value to a variable of different dimensionality")
                     }
-                } else if (!is.null(dim(value)) && !is.null(dim(x@cellMeta[[columns]]))) {
-                    # Both are dimensional
-                    if (ncol(value) != ncol(x@cellMeta[[columns]])) {
-                        stop("Cannot insert value to a variable of different ",
-                             "dimensionality")
-                    }
-                    x@cellMeta[[columns]][cellIdx,] <- value
                 } else {
-                    stop("Cannot insert value to a variable of different ",
-                         "dimensionality")
+                    x@cellMeta[[columns]] <- NULL
+                    # Remove and go to "Add new variable" case above
+                    cellMeta(x, columns = columns, cellIdx = cellIdx, check = check) <- value
                 }
             }
         } else {
-            stop("`cellIdx` pointing to more cells than available")
+            cli::cli_abort("{.var cellIdx} pointing to more cells than available")
         }
         if (isTRUE(check)) methods::validObject(x)
         x
     }
 )
 
+
+#' @export
+#' @rdname liger-class
+setMethod("rawData", c("liger", "ANY"),
+          function(x, dataset = NULL) {
+              if (is.null(dataset)) {
+                  getMatrix(x, slot = "rawData", returnList = TRUE)
+              } else {
+                  getMatrix(x, "rawData", dataset = dataset)
+              }
+          }
+)
+
+#' @export
+#' @rdname liger-class
+setReplaceMethod(
+    "rawData",
+    signature(x = "liger", dataset = "ANY", check = "ANY", value = "matrixLike_OR_NULL"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        dataset <- .checkUseDatasets(x, dataset)
+        if (length(dataset) != 1) cli::cli_abort("Need to specify one dataset to insert.")
+        if (isH5Liger(x, dataset))
+            cli::cli_abort("Cannot replace slot with in-memory data for H5 based object.")
+        x@datasets[[dataset]]@rawData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname liger-class
+setReplaceMethod(
+    "rawData",
+    signature(x = "liger", dataset = "ANY", check = "ANY", value = "H5D"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        dataset <- .checkUseDatasets(x, dataset)
+        if (length(dataset) != 1) cli::cli_abort("Need to specify one dataset to insert.")
+        if (!isH5Liger(x, dataset))
+            cli::cli_abort("Cannot replace slot with on-disk data for in-memory object.")
+        x@datasets[[dataset]]@rawData <- value
+        if (isTRUE(check)) methods::validObject(x@datasets[[dataset]])
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname liger-class
+setMethod("normData", c("liger", "ANY"),
+          function(x, dataset = NULL) {
+              if (is.null(dataset)) {
+                  getMatrix(x, slot = "normData", returnList = TRUE)
+              } else {
+                  getMatrix(x, "normData", dataset = dataset)
+              }
+          }
+)
+
+#' @export
+#' @rdname liger-class
+setReplaceMethod(
+    "normData",
+    signature(x = "liger", dataset = "ANY", check = "ANY", value = "matrixLike_OR_NULL"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        dataset <- .checkUseDatasets(x, dataset)
+        if (length(dataset) != 1) cli::cli_abort("Need to specify one dataset to insert.")
+        if (isH5Liger(x, dataset))
+            cli::cli_abort("Cannot replace slot with in-memory data for H5 based object.")
+        x@datasets[[dataset]]@normData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname liger-class
+setReplaceMethod(
+    "normData",
+    signature(x = "liger", dataset = "ANY", check = "ANY", value = "H5D"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        dataset <- .checkUseDatasets(x, dataset)
+        if (length(dataset) != 1) cli::cli_abort("Need to specify one dataset to insert.")
+        if (!isH5Liger(x, dataset))
+            cli::cli_abort("Cannot replace slot with on-disk data for in-memory object.")
+        x@datasets[[dataset]]@normData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname liger-class
+setMethod(
+    "scaleData",
+    signature(x = "liger", dataset = "ANY"),
+    function(x, dataset = NULL) {
+        if (is.null(dataset)) {
+            getMatrix(x, slot = "scaleData", returnList = TRUE)
+        } else {
+            getMatrix(x, "scaleData", dataset = dataset)
+        }
+    }
+)
+
+
+#' @export
+#' @rdname liger-class
+setReplaceMethod(
+    "scaleData",
+    signature(x = "liger", dataset = "ANY", check = "ANY", value = "matrixLike_OR_NULL"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        dataset <- .checkUseDatasets(x, dataset)
+        if (length(dataset) != 1) cli::cli_abort("Need to specify one dataset to insert.")
+        if (isH5Liger(x, dataset))
+            cli::cli_abort("Cannot replace slot with in-memory data for H5 based object.")
+        x@datasets[[dataset]]@scaleData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname liger-class
+setReplaceMethod(
+    "scaleData",
+    signature(x = "liger", dataset = "ANY", check = "ANY", value = "H5D"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        dataset <- .checkUseDatasets(x, dataset)
+        if (length(dataset) != 1) cli::cli_abort("Need to specify one dataset to insert.")
+        if (!isH5Liger(x, dataset))
+            cli::cli_abort("Cannot replace slot with on-disk data for in-memory object.")
+        x@datasets[[dataset]]@scaleData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname liger-class
+setReplaceMethod(
+    "scaleData",
+    signature(x = "liger", dataset = "ANY", check = "ANY", value = "H5Group"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        dataset <- .checkUseDatasets(x, dataset)
+        if (length(dataset) != 1) cli::cli_abort("Need to specify one dataset to insert.")
+        if (!isH5Liger(x, dataset))
+            cli::cli_abort("Cannot replace slot with on-disk data for in-memory object.")
+        x@datasets[[dataset]]@scaleData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname liger-class
+setMethod(
+    "scaleUnsharedData",
+    signature(x = "liger", dataset = "character"),
+    function(x, dataset) {
+        scaleUnsharedData(dataset(x, dataset))
+    }
+)
+
+
+#' @export
+#' @rdname liger-class
+setMethod(
+    "scaleUnsharedData",
+    signature(x = "liger", dataset = "numeric"),
+    function(x, dataset) {
+        scaleUnsharedData(dataset(x, dataset))
+    }
+)
+
+
+#' @export
+#' @rdname liger-class
+setReplaceMethod(
+    "scaleUnsharedData",
+    signature(x = "liger", dataset = "ANY", check = "ANY", value = "matrixLike_OR_NULL"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        dataset <- .checkUseDatasets(x, dataset)
+        if (length(dataset) != 1) cli::cli_abort("Need to specify one dataset to insert.")
+        if (isH5Liger(x, dataset))
+            cli::cli_abort("Cannot replace slot with in-memory data for H5 based object.")
+        x@datasets[[dataset]]@scaleUnsharedData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname liger-class
+setReplaceMethod(
+    "scaleUnsharedData",
+    signature(x = "liger", dataset = "ANY", check = "ANY", value = "H5D"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        dataset <- .checkUseDatasets(x, dataset)
+        if (length(dataset) != 1) cli::cli_abort("Need to specify one dataset to insert.")
+        if (!isH5Liger(x, dataset))
+            cli::cli_abort("Cannot replace slot with on-disk data for in-memory object.")
+        x@datasets[[dataset]]@scaleUnsharedData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname liger-class
+setReplaceMethod(
+    "scaleUnsharedData",
+    signature(x = "liger", dataset = "ANY", check = "ANY", value = "H5Group"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        dataset <- .checkUseDatasets(x, dataset)
+        if (length(dataset) != 1) cli::cli_abort("Need to specify one dataset to insert.")
+        if (!isH5Liger(x, dataset))
+            cli::cli_abort("Cannot replace slot with on-disk data for in-memory object.")
+        x@datasets[[dataset]]@scaleUnsharedData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+
+#' @export
+#' @rdname liger-class
+setMethod(
+    "getMatrix", signature(x = "liger"),
+    function(x,
+             slot = c("rawData", "normData", "scaleData",
+                      "scaleUnsharedData", "H", "V", "U", "A", "B",
+                      "W", "H.norm"),
+             dataset = NULL,
+             returnList = FALSE) {
+        slot <- match.arg(slot)
+        if (slot == "W") return(x@W)
+        if (slot == "H.norm") return(x@H.norm)
+        if (is.null(dataset)) {
+            return(lapply(datasets(x), function(ld) getMatrix(ld, slot)))
+        } else {
+            if (length(dataset) == 1) {
+                if (isTRUE(returnList)) {
+                    result <- list(getMatrix(dataset(x, dataset), slot))
+                    names(result) <- dataset
+                    return(result)
+                } else if (isFALSE(returnList))
+                    return(getMatrix(dataset(x, dataset), slot))
+            } else {
+                lds <- datasets(x)[dataset]
+                return(lapply(lds, function(ld) getMatrix(ld, slot)))
+            }
+        }
+    })
+
+#' @export
+#' @rdname liger-class
+setMethod("getH5File",
+          signature = signature(x = "liger", dataset = "ANY"),
+          function(x, dataset = NULL) {
+              if (is.null(dataset)) dataset <- names(x)
+              dataset <- .checkUseDatasets(x, dataset)
+              results <- lapply(datasets(x)[dataset],
+                                function(ld) h5fileInfo(ld, "H5File"))
+              if (length(results) == 1) results <- results[[1]]
+              results
+          })
+
+
 #' Get cell metadata variable
 #' @name sub-sub-liger
 #' @param x A \linkS4class{liger} object
@@ -944,23 +992,6 @@ setReplaceMethod("$", signature(x = "liger"),
                      cellMeta(x, columns = name) <- value
                      return(x)
                  })
-#' @export
-#' @rdname liger-class
-setGeneric(
-    "defaultCluster",
-    function(x, useDatasets = NULL, ...) {
-        standardGeneric("defaultCluster")
-    }
-)
-
-#' @export
-#' @rdname liger-class
-setGeneric(
-    "defaultCluster<-",
-    function(x, name = NULL, useDatasets = NULL, ..., value) {
-        standardGeneric("defaultCluster<-")
-    }
-)
 
 #' @export
 #' @rdname liger-class
@@ -987,17 +1018,14 @@ setReplaceMethod(
     "defaultCluster",
     signature(x = "liger", value = "character"),
     function(x, name = NULL, useDatasets = NULL, ..., value) {
-        useDatasets <- .checkUseDatasets(x, useDatasets)
-        cellIdx <- x$dataset %in% useDatasets
         if (length(value) == 1) {
             # If doing defaultCluster(obj) <- "someName"
             if (!is.null(name)) {
-                warning("Cannot have `name` when selecting a name with ",
-                        "`value`.")
+                cli::cli_alert_danger("Cannot have {.code name} when selecting a variable with {.code value}.")
             }
             name <- value
             if (!name %in% colnames(cellMeta(x))) {
-                stop("Selected name does not exist in `cellMeta(x)`")
+                cli::cli_abort("Selected variable does not exist in {.code cellMeta(x)}.")
             }
             x@uns$defaultCluster <- name
         } else {
@@ -1018,14 +1046,27 @@ setReplaceMethod(
         useDatasets <- .checkUseDatasets(x, useDatasets)
         cellIdx <- x$dataset %in% useDatasets
         if (length(value) != sum(cellIdx)) {
-            stop("Length of `value` does not match with the number of cells")
+            cli::cli_abort("Length of {.code value} does not match with the number of cells.")
         }
         if (is.null(name)) {
-            .log("Storing given cluster labels to cellMeta(x) field: ",
-                 "\"defaultCluster\"")
+            cli::cli_alert_info(
+                c("Storing given cluster labels to {.code cellMeta(x)} field: ",
+                  "{.val defaultCluster}.")
+            )
             name <- "defaultCluster"
         }
         if (is.null(names(value))) names(value) <- colnames(x)[cellIdx]
+        else {
+            if (all(names(value) %in% colnames(x)[cellIdx])) {
+                value <- value[colnames(x)[cellIdx]]
+            } else {
+                cli::cli_abort(
+                    c(x = "Not all {.code names(value)} match with target cells: ",
+                      "{.val {names(value)[!names(value) %in% colnames(x)[cellIdx]]}}",
+                      i = "Please have a check or try {.code unname(value)}.")
+                )
+            }
+        }
         cellMeta(x, name, cellIdx) <- value
         x@uns$defaultCluster <- name
         return(x)
@@ -1046,35 +1087,6 @@ setReplaceMethod(
     }
 )
 
-#' @export
-#' @rdname liger-class
-#' @section Dimension reduction access:
-#' Currently, low-dimensional representaion of cells, presented as dense
-#' matrices, are all stored in \code{cellMeta} slot, and can totally be accessed
-#' with generics \code{cellMeta} and \code{cellMeta<-}. In addition to that,
-#' we provide specific generics \code{dimRed} and \code{dimRed<-} for getting
-#' and setting matrix like cell metadata, respectively. Adding a matrix to the
-#' object looks as simple as \code{dimRed(obj, "name") <- matrixLike}. It can
-#' be retrived back with \code{dimRed(obj, "name")}. Similar to having a default
-#' cluster labeling, we also constructed the feature of default dimRed. It can
-#' be set with \code{defaultDimRed(obj) <- "existingMatLikeVar"} and the matrix
-#' can be retrieved with \code{defaultDimRed(obj)}.
-setGeneric(
-    "dimRed",
-    function(x, name = NULL, useDatasets = NULL, ...) {
-        standardGeneric("dimRed")
-    }
-)
-
-#' @export
-#' @rdname liger-class
-setGeneric(
-    "dimRed<-",
-    function(x, name = NULL, useDatasets = NULL, ..., value) {
-        standardGeneric("dimRed<-")
-    }
-)
-
 #' @export
 #' @rdname liger-class
 setMethod(
@@ -1088,14 +1100,14 @@ setMethod(
         if (is.null(name)) {
             for (i in seq_along(cellMeta(x))) {
                 if (!is.null(dim(cellMeta(x)[[i]]))) {
-                    warning("No default dimRed recorded. Returning the first ",
-                            "matrix like object in cellMeta(object)")
+                    cli::cli_alert_warning(
+                        "No default dimRed recorded. Returning the first matrix alike in {.code cellMeta(object)}.")
                     dimred <- cellMeta(x)[[i]]
                     break
                 }
             }
             if (is.null(dimred)) {
-                stop("No possible dimRed can be found in this liger object.")
+                cli::cli_abort("No possible dimRed can be found in this {.cls liger} object.")
             }
         } else {
             dimred <- cellMeta(x, name, x$dataset %in% useDatasets)
@@ -1117,7 +1129,7 @@ setMethod(
         useDatasets <- .checkUseDatasets(x, useDatasets)
         dimred <- cellMeta(x, name, x$dataset %in% useDatasets)
         if (is.null(dim(dimred))) {
-            stop("Retrieved data for \"", name, "\" is not a matrix.")
+            cli::cli_abort("Retrieved data for {.val {name}} is not a matrix.")
         }
         dimred <- as.matrix(dimred)
         rownames(dimred) <- colnames(x)[x$dataset %in% useDatasets]
@@ -1150,24 +1162,6 @@ setReplaceMethod(
     }
 )
 
-#' @export
-#' @rdname liger-class
-setGeneric(
-    "defaultDimRed",
-    function(x, useDatasets = NULL) {
-        standardGeneric("defaultDimRed")
-    }
-)
-
-#' @export
-#' @rdname liger-class
-setGeneric(
-    "defaultDimRed<-",
-    function(x, name, useDatasets = NULL, value) {
-        standardGeneric("defaultDimRed<-")
-    }
-)
-
 #' @export
 #' @rdname liger-class
 setMethod(
@@ -1189,10 +1183,10 @@ setReplaceMethod(
         value <- value[1]
         dimred <- cellMeta(x, value)
         if (is.null(dim(dimred))) {
-            stop("Specified variable is not matrix like.")
+            cli::cli_abort("Specified variable is not a matrix alike.")
         }
         if (ncol(dimred) == 0) {
-            stop("Cannot set unexisting variable as default dimRed.")
+            cli::cli_abort("Cannot set unexisting variable as default dimRed.")
         }
         x@uns$defaultDimRed <- value
         return(x)
@@ -1215,25 +1209,6 @@ setReplaceMethod(
     }
 )
 
-#' @export
-#' @rdname liger-class
-#' @section Variable feature access:
-#' The \code{varFeatures} slot allows for character vectors of gene names.
-#' \code{varFeatures(x)} returns this vector and \code{value} for
-#' \code{varFeatures<-} method has to be a character vector or \code{NULL}.
-#' The replacement method, when \code{check = TRUE} performs checks on gene
-#' name consistency check across the \code{scaleData}, \code{H}, \code{V} slots
-#' of inner \code{ligerDataset} objects as well as the \code{W} and
-#' \code{H.norm} slots of the input \code{liger} object.
-setGeneric("varFeatures", function(x) standardGeneric("varFeatures"))
-
-#' @export
-#' @rdname liger-class
-setGeneric(
-    "varFeatures<-",
-    function(x, check = TRUE, value) standardGeneric("varFeatures<-")
-)
-
 #' @export
 #' @rdname liger-class
 setMethod("varFeatures", signature(x = "liger"),
@@ -1256,10 +1231,9 @@ setReplaceMethod(
                 all(value %in% rownames(ld))
             }), use.names = FALSE)
             if (!all(checkResult)) {
-                problem <- names(x)[!checkResult]
-                warning("Not all variable features passed are ",
-                        "found in datasets: ",
-                        paste(problem, collapse = ", "))
+                cli::cli_alert_warning(
+                    "Not all variable features passed are found in datasets: {.val {names(x)[!checkResult]}}"
+                )
             }
         }
         x
@@ -1267,22 +1241,6 @@ setReplaceMethod(
 )
 
 
-
-#' @export
-#' @rdname liger-class
-setGeneric("varUnsharedFeatures", function(x, dataset = NULL) {
-    standardGeneric("varUnsharedFeatures")
-})
-
-#' @export
-#' @rdname liger-class
-setGeneric(
-    "varUnsharedFeatures<-",
-    function(x, dataset, check = TRUE, value) {
-        standardGeneric("varUnsharedFeatures<-")
-    }
-)
-
 #' @export
 #' @rdname liger-class
 setMethod("varUnsharedFeatures", signature(x = "liger"),
@@ -1298,12 +1256,6 @@ setMethod("varUnsharedFeatures", signature(x = "liger"),
           }
 )
 
-#' @export
-#' @rdname liger-class
-setMethod("varUnsharedFeatures",
-          signature(x = "ligerDataset", dataset = "missing"),
-          function(x, dataset = NULL) x@varUnsharedFeatures)
-
 #' @export
 #' @rdname liger-class
 setReplaceMethod(
@@ -1314,32 +1266,13 @@ setReplaceMethod(
         x@datasets[[dataset]]@varUnsharedFeatures <- value
         if (isTRUE(check)) {
             if (!all(value %in% rownames(x@datasets[[dataset]]))) {
-                warning("Not all features passed are found in dataset \"",
-                        dataset, "\".")
-            }
-        }
-        return(x)
-    }
-)
-
-#' @export
-#' @rdname liger-class
-setReplaceMethod(
-    "varUnsharedFeatures",
-    signature(x = "ligerDataset", dataset = "missing", check = "ANY", value = "character"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        x@varUnsharedFeatures <- value
-        if (isTRUE(check)) {
-            if (!all(value %in% rownames(x))) {
-                warning("Not all features passed are found.")
+                cli::cli_alert_warning("Not all features passed are found in dataset {.val {dataset}}.")
             }
         }
         return(x)
     }
 )
 
-
-
 #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 # S3 methods ####
 #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@@ -1364,7 +1297,7 @@ fortify.liger <- function(model, data, ...) {
 c.liger <- function(...) {
     objList <- list(...)
     if (any(sapply(objList, function(obj) !inherits(obj, "liger"))))
-        stop("Can only combine `liger` objects with `c(...)` method for now.")
+        cli::cli_abort("Can only combine {.cls liger} objects with {.fn c} method for now.")
     objList[[length(objList)]] <- recordCommand(objList[[length(objList)]])
     allDatasets <- list()
     allCellMeta <- NULL
@@ -1381,3 +1314,105 @@ c.liger <- function(...) {
                  varFeatures = varFeatures, commands = allCommands,
                  version = utils::packageVersion("rliger2"))
 }
+
+
+#' @export
+#' @rdname liger-class
+setMethod(
+    "commands",
+    signature(x = "liger", funcName = "ANY", arg = "ANY"),
+    function(x, funcName = NULL, arg = NULL) {
+        if (is.null(funcName)) return(names(x@commands))
+        cmdIdx <- c()
+        for (n in funcName) {
+            pat <- paste0("^", n)
+            cmdIdx <- c(cmdIdx, grep(pat, names(x@commands)))
+        }
+        cmdIdx <- sort(unique(cmdIdx))
+        result <- x@commands[cmdIdx]
+
+        if (length(result) == 1) result <- result[[1]]
+
+        if (!is.null(arg)) {
+            if (is.list(result))
+                result <- lapply(result, function(cmd) cmd@parameters[arg])
+            else result <- unlist(result@parameters[arg])
+        }
+        return(result)
+    }
+)
+
+
+#' @rdname peak
+#' @export
+setMethod("rawPeak", signature(x = "liger", dataset = "character"),
+          function(x, dataset) {
+              atac <- dataset(x, dataset)
+              if (!inherits(atac, "ligerATACDataset")) {
+                  cli::cli_abort("Specified dataset is not of {.cls ligerATACDataset} class.")
+              }
+              atac@rawPeak
+          })
+
+#' @rdname peak
+#' @export
+setReplaceMethod(
+    "rawPeak",
+    signature(x = "liger", dataset = "character"),
+    function(x, dataset, check = TRUE, value) {
+        if (!inherits(dataset(x, dataset), "ligerATACDataset"))
+            cli::cli_abort("Specified dataset is not of {.cls ligerATACDataset} class.")
+        x@datasets[[dataset]]@rawPeak <- value
+        if (isTRUE(check)) methods::validObject(dataset(x, dataset))
+        x
+    })
+
+#' @rdname peak
+#' @export
+setMethod("normPeak", signature(x = "liger", dataset = "character"),
+          function(x, dataset) {
+              atac <- dataset(x, dataset)
+              if (!inherits(atac, "ligerATACDataset")) {
+                  cli::cli_abort("Specified dataset is not of {.cls ligerATACDataset} class.")
+              }
+              atac@normPeak
+          })
+
+#' @rdname peak
+#' @export
+setReplaceMethod(
+    "normPeak",
+    signature(x = "liger", dataset = "character"),
+    function(x, dataset, check = TRUE, value) {
+        if (!inherits(dataset(x, dataset), "ligerATACDataset"))
+            cli::cli_abort("Specified dataset is not of {.cls ligerATACDataset} class.")
+        x@datasets[[dataset]]@normPeak <- value
+        if (isTRUE(check)) methods::validObject(dataset(x, dataset))
+        x
+    })
+
+
+#' @rdname coordinate
+#' @export
+setMethod("coordinate", signature(x = "liger", dataset = "character"),
+          function(x, dataset) {
+              spatial <- dataset(x, dataset)
+              if (!inherits(spatial, "ligerSpatialDataset")) {
+                  cli::cli_abort("Specified dataset is not of {.cls ligerSpatialDataset} class.")
+              }
+              spatial@coordinate
+          })
+
+#' @rdname coordinate
+#' @export
+setReplaceMethod(
+    "coordinate",
+    signature(x = "liger", dataset = "character"),
+    function(x, dataset, check = TRUE, value) {
+        if (!inherits(dataset(x, dataset), "ligerSpatialDataset"))
+            cli::cli_abort("Specified dataset is not of {.cls ligerSpatialDataset} class.")
+        value <- .checkCoords(ld = dataset(x, dataset), value = value)
+        x@datasets[[dataset]]@coordinate <- value
+        if (isTRUE(check)) methods::validObject(dataset(x, dataset))
+        x
+    })
diff --git a/R/ligerCommand-class.R b/R/ligerCommand_relates.R
similarity index 66%
rename from R/ligerCommand-class.R
rename to R/ligerCommand_relates.R
index 8ec6e695..f79652b7 100644
--- a/R/ligerCommand-class.R
+++ b/R/ligerCommand_relates.R
@@ -1,50 +1,3 @@
-setClassUnion("POSIXct_or_NULL", c("POSIXct", "NULL"))
-
-#' ligerCommand object: Record the input and time of a LIGER function call
-#' @slot funcName Name of the function
-#' @slot time A time stamp object
-#' @slot call A character string converted from system call
-#' @slot parameters List of all arguments except the \linkS4class{liger} object.
-#' Large object are summarized to short string.
-#' @slot objSummary List of attributes of the \linkS4class{liger} object as a
-#' snapshot when command is operated.
-#' @slot ligerVersion Character string converted from
-#' \code{packageVersion("rliger2")}.
-#' @slot dependencyVersion Named character vector of version number, if any
-#' dependency library has a chance to be included by the function. A
-#' dependency might only be invoked under certain conditions, such as using
-#' an alternative algorithm, which a call does not actually reach to, but it
-#' would still be included for this call.
-#' @exportClass ligerCommand
-#' @export
-#' @rdname ligerCommand-class
-ligerCommand <- setClass(
-    Class = "ligerCommand",
-    representation(
-        funcName = "character",
-        time = "POSIXct_or_NULL",
-        call = "character",
-        parameters = "list",
-        objSummary = "list",
-        ligerVersion = "character",
-        dependencyVersion = "character"
-    ),
-    prototype(
-        funcName = character(),
-        time = NULL,
-        parameters = list(),
-        objSummary = list(
-            datasets = character(),
-            nCells = numeric(),
-            nFeatures = numeric(),
-            nVarFeatures = numeric(),
-            cellMetaNames = character(),
-            ligerVersion = character(),
-            dependencyVersion = character()
-        )
-    )
-)
-
 # Call in a way like:
 # object <- recordCommand(object, dependencies = ...)
 # Conditionally, should be placed after input checks
@@ -56,8 +9,6 @@ recordCommand <- function(
         ...,
         dependencies = NULL
 ) {
-    #if (!inherits(object, "liger"))
-    #    stop("Can only record commands for operation on a liger object")
     # Generate time stamp
     time <- Sys.time()
     # Capture the call
@@ -192,12 +143,12 @@ setMethod(
 commandDiff <- function(object, cmd1, cmd2) {
     cmd1 <- commands(object, cmd1)
     if (!inherits(cmd1, "ligerCommand"))
-        stop("`cmd1` matching with multiple command records. ",
-             "Available options could be viewed with `commands(object)`.")
+        cli::cli_abort("{.code cmd1} matching with multiple command records.
+                       Availble options could be viewed with {.code commands(object)}.")
     cmd2 <- commands(object, cmd2)
     if (!inherits(cmd2, "ligerCommand"))
-        stop("`cmd2` matching with multiple command records. ",
-             "Available options could be viewed with `commands(object)`.")
+        cli::cli_abort("{.code cmd2} matching with multiple command records.
+                       Availble options could be viewed with {.code commands(object)}.")
     .cmdDiff(cmd1, cmd2)
 }
 
@@ -255,49 +206,4 @@ commandDiff <- function(object, cmd1, cmd2) {
     return(msg)
 }
 
-#' @section Command records:
-#' rliger functions, that perform calculation and update the \code{liger}
-#' object, will be recorded in a \code{ligerCommand} object and stored in the
-#' \code{commands} slot, a list, of \code{liger} object. Method
-#' \code{commands()} is implemented to retrieve or show the log history.
-#' Running with \code{funcName = NULL} (default) returns all command labels.
-#' Specifying \code{funcName} allows partial matching to all command labels
-#' and returns a subset list (of \code{ligerCommand} object) of matches (or
-#' the \code{ligerCommand} object if only one match found). If \code{arg} is
-#' further specified, a subset list of parameters from the matches will be
-#' returned. For example, requesting a list of resolution values used in
-#' all louvain cluster attempts: \code{commands(ligerObj, "louvainCluster",
-#' "resolution")}
-#' @export
-#' @rdname liger-class
-setGeneric(
-    "commands",
-    function(x, funcName = NULL, arg = NULL) standardGeneric("commands")
-)
-
-#' @export
-#' @rdname liger-class
-setMethod(
-    "commands",
-    signature(x = "liger", funcName = "ANY", arg = "ANY"),
-    function(x, funcName = NULL, arg = NULL) {
-        if (is.null(funcName)) return(names(x@commands))
-        cmdIdx <- c()
-        for (n in funcName) {
-            pat <- paste0("^", n)
-            cmdIdx <- c(cmdIdx, grep(pat, names(x@commands)))
-        }
-        cmdIdx <- sort(unique(cmdIdx))
-        result <- x@commands[cmdIdx]
-
-        if (length(result) == 1) result <- result[[1]]
-
-        if (!is.null(arg)) {
-            if (is.list(result))
-                result <- lapply(result, function(cmd) cmd@parameters[arg])
-            else result <- unlist(result@parameters[arg])
-        }
-        return(result)
-    }
-)
 
diff --git a/R/ligerDataset-class.R b/R/ligerDataset-class.R
deleted file mode 100644
index 89f942ed..00000000
--- a/R/ligerDataset-class.R
+++ /dev/null
@@ -1,1120 +0,0 @@
-setClassUnion("dgCMatrix_OR_NULL", c("dgCMatrix", "NULL"))
-setClassUnion("matrix_OR_NULL", c("matrix", "NULL"))
-setClassUnion("matrixLike", c("matrix", "dgCMatrix", "dgTMatrix", "dgeMatrix"))
-setClassUnion("matrixLike_OR_NULL", c("matrixLike", "NULL"))
-# It is quite hard to handle "H5D here, which is indeed defined as an R6 class.
-# I'm not sure if this is a proper solution
-setOldClass("H5D")
-setOldClass("H5Group")
-suppressWarnings(setClassUnion("dgCMatrix_OR_H5D_OR_NULL", c("dgCMatrix", "H5D", "NULL")))
-setClassUnion("matrix_OR_H5D_OR_NULL", c("matrix", "H5D", "NULL"))
-setClassUnion("matrixLike_OR_H5D_OR_H5Group_OR_NULL", c("matrixLike", "H5D", "H5Group", "NULL"))
-setClassUnion("index",
-              members = c("logical", "numeric", "character"))
-
-#' ligerDataset class
-#'
-#' Object for storing dastaset specific information. Will be embedded within a
-#' higher level \linkS4class{liger} object
-#' @docType class
-#' @rdname ligerDataset-class
-#' @slot rawData Raw data.
-#' @slot normData Normalized data
-#' @slot scaleData Scaled data, usually with subset variable features
-#' @slot scaleUnsharedData Scaled data of features not shared with other
-#' datasets
-#' @slot varUnsharedFeatures Variable features not shared with other datasets
-#' @slot V matrix
-#' @slot A matrix
-#' @slot B matrix
-#' @slot H matrix
-#' @slot U matrix
-#' @slot h5fileInfo list
-#' @slot featureMeta Feature metadata, DataFrame
-#' @slot colnames character
-#' @slot rownames character
-#' @importClassesFrom S4Vectors DataFrame
-#' @exportClass ligerDataset
-ligerDataset <- setClass(
-    "ligerDataset",
-    representation(
-        rawData = "dgCMatrix_OR_H5D_OR_NULL",
-        normData = "dgCMatrix_OR_H5D_OR_NULL",
-        scaleData = "matrixLike_OR_H5D_OR_H5Group_OR_NULL",
-        scaleUnsharedData = "matrixLike_OR_H5D_OR_H5Group_OR_NULL",
-        varUnsharedFeatures = "character",
-        H = "matrix_OR_NULL",
-        V = "matrix_OR_NULL",
-        A = "matrix_OR_NULL",
-        B = "matrix_OR_NULL",
-        U = "matrix_OR_NULL",
-        h5fileInfo = "list",
-        featureMeta = "DataFrame",
-        colnames = "character",
-        rownames = "character"
-    )
-)
-
-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-# Dataset creatinfg function ####
-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-#' Check if a liger or ligerDataset object is made of HDF5 file
-#' @param object A liger or ligerDataset object.
-#' @param dataset If \code{object} is of liger class, check a specific dataset.
-#' If \code{NULL}, Check if all datasets are made of HDF5 file. Default
-#' \code{NULL}.
-#' @return \code{TRUE} or \code{FALSE} for the specified check.
-#' @export
-#' @examples
-#' isH5Liger(pbmc)
-#' isH5Liger(pbmc, "ctrl")
-#' ctrl <- dataset(pbmc, "ctrl")
-#' isH5Liger(ctrl)
-isH5Liger <- function(object, dataset = NULL) {
-    if (inherits(object, "ligerDataset")) {
-        if (length(object@h5fileInfo) == 0) {
-            return(FALSE)
-        } else {
-            return(TRUE)
-        }
-    } else if (inherits(object, "liger")) {
-        dataset <- .checkUseDatasets(object, dataset)
-        allCheck <- unlist(lapply(datasets(object)[dataset], isH5Liger))
-        return(all(allCheck))
-    } else {
-        warning("Given object is not of liger or ligerDataset class.")
-        return(FALSE)
-    }
-}
-
-#' Return preset modality of a ligerDataset object or that of all datasets in a
-#' liger object
-#' @param object a \linkS4class{ligerDataset} object or a \linkS4class{liger}
-#' object
-#' @return A single character of modality setting value for
-#' \linkS4class{ligerDataset} \code{object}, or a named vector for
-#' \linkS4class{liger} object, where the names are dataset names.
-#' @export
-#' @examples
-#' modalOf(pbmc)
-#' ctrl <- dataset(pbmc, "ctrl")
-#' modalOf(ctrl)
-#' ctrl.atac <- as.ligerDataset(ctrl, modal = "atac")
-#' modalOf(ctrl.atac)
-modalOf <- function(object) {
-    if (inherits(object, "ligerDataset")) {
-        if (class(object) %in% names(.classModalDict))
-            return(.classModalDict[[class(object)]])
-        else {
-            warning("DEVELOPERS, please add this ligerDataset sub-class to ",
-                    "`.classModalDict`", immediate. = TRUE)
-            return("UNKNOWN")
-        }
-    } else if (inherits(object, "liger")) {
-        return(sapply(datasets(object), modalOf))
-    }
-}
-
-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-# Object validity ####
-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-.checkLigerDatasetBarcodes <- function(x) {
-    # cell barcodes all consistant
-    if (is.null(colnames(x))) {
-        return(paste0("No valid cell barcode detected for ligerDataset.\n",
-                      "Please create object with matrices with colnames."))
-    }
-    for (slot in c("rawData", "normData", "scaleData", "scaleUnsharedData",
-                   "H")) {
-        if (!slot %in% methods::slotNames(x)) next
-        data <- methods::slot(x, slot)
-        if (!is.null(data)) {
-            barcodes.slot <- colnames(data)
-            if (!identical(colnames(x), barcodes.slot)) {
-                return(paste0("Inconsistant cell identifiers in `", slot,
-                              "` slot."))
-            }
-        }
-    }
-
-    for (slot in c("scaleData", "V")) {
-        featuresToCheck <- rownames(methods::slot(x, slot))
-        check <- !featuresToCheck %in% rownames(x)
-        if (any(check)) {
-            msg <- paste0("Features in ", slot, " not found from dataset: ",
-                          paste(featuresToCheck[check], collapse = ", "))
-            return(msg)
-        }
-    }
-    TRUE
-}
-
-.checkH5LigerDatasetLink <- function(x) {
-    restoreGuide <- "Please try running `restoreH5Liger(object)`."
-    if (!"H5File" %in% names(h5fileInfo(x))) {
-        return(paste("`h5fileInfo` incomplete.", restoreGuide))
-    }
-    h5file <- getH5File(x)
-    if (is.null(h5file)) {
-        return(paste("`H5File` is NULL in `h5fileInfo` slot.", restoreGuide))
-    }
-    if (!h5file$is_valid) {
-        return(paste("`H5File` is invalid in `h5fileInfo` slot.", restoreGuide))
-    }
-    if (!is.null(rawData(x))) {
-        if (!rawData(x)$is_valid) {
-            return(paste("`rawData` slot is invalid.", restoreGuide))
-        }
-    }
-    if (!is.null(normData(x))) {
-        if (!normData(x)$is_valid) {
-            return(paste("`normData` slot is invalid.", restoreGuide))
-        }
-    }
-    if (!is.null(scaleData(x))) {
-        if (!scaleData(x)$is_valid) {
-            return(paste("`scaleData` slot is invalid.", restoreGuide))
-        }
-    }
-    TRUE
-}
-
-.valid.ligerDataset <- function(object) {
-    if (isH5Liger(object)) {
-        # message("Checking h5 ligerDataset validity")
-        .checkH5LigerDatasetLink(object)
-    } else {
-        # message("Checking in memory ligerDataset validity")
-        .checkLigerDatasetBarcodes(object)
-    }
-    # TODO more checks
-    # TODO debating on whether to have check of the matching between scaleData
-    # features and selected variable features.
-}
-
-setValidity("ligerDataset", .valid.ligerDataset)
-
-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-# S4 Methods ####
-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#' @param x,object A \code{ligerDataset} object.
-#' @param dataset Not applicable for \code{ligerDataset} methods.
-#' @param value See detail sections for requirements
-#' @param check Whether to perform object validity check on setting new value.
-#' @param info Name of the entry in \code{h5fileInfo} slot.
-#' @param slot The slot name when using \code{getMatrix}.
-#' @param returnList Not applicable for \code{ligerDataset} methods.
-#' @param ... See detailed sections for explanation.
-#' @rdname ligerDataset-class
-#' @export
-#' @examples
-#' ctrl <- dataset(pbmc, "ctrl")
-#'
-#' # Methods for base generics
-#' ctrl
-#' print(ctrl)
-#' dim(ctrl)
-#' ncol(ctrl)
-#' nrow(ctrl)
-#' colnames(ctrl)[1:5]
-#' rownames(ctrl)[1:5]
-#' ctrl[1:5, 1:5]
-#'
-#' # rliger generics
-#' ## raw data
-#' m <- rawData(ctrl)
-#' class(m)
-#' dim(m)
-#' ## normalized data
-#' pbmc <- normalize(pbmc)
-#' ctrl <- dataset(pbmc, "ctrl")
-#' m <- normData(ctrl)
-#' class(m)
-#' dim(m)
-#' ## scaled data
-#' pbmc <- selectGenes(pbmc)
-#' pbmc <- scaleNotCenter(pbmc)
-#' ctrl <- dataset(pbmc, "ctrl")
-#' m <- scaleData(ctrl)
-#' class(m)
-#' dim(m)
-#' n <- scaleData(pbmc, "ctrl")
-#' identical(m, n)
-#' ## Any other matrices
-#' if (requireNamespace("RcppPlanc", quietly = TRUE)) {
-#'     pbmc <- runOnlineINMF(pbmc, k = 20, minibatchSize = 100)
-#'     ctrl <- dataset(pbmc, "ctrl")
-#'     V <- getMatrix(ctrl, "V")
-#'     V[1:5, 1:5]
-#'     Vs <- getMatrix(pbmc, "V")
-#'     length(Vs)
-#'     names(Vs)
-#'     identical(Vs$ctrl, V)
-#' }
-setMethod(
-    f = "show",
-    signature(object = "ligerDataset"),
-    definition = function(object) {
-        # Use class(object) so that the inheriting classes can be shown properly
-        cat("An object of class", class(object), "with",
-            ncol(object), "cells\n")
-        if (isH5Liger(object) &
-            !isTRUE(methods::validObject(object, test = TRUE))) {
-            warning("Link to HDF5 file fails. Please try running ",
-                    "`restoreH5Liger(object)`.")
-            return()
-        }
-        for (slot in c("rawData", "normData", "scaleData",
-                       "scaleUnsharedData")) {
-            data <- methods::slot(object, slot)
-            if (!is.null(data)) {
-                if (inherits(data, c("matrix", "dgCMatrix",
-                                     "dgTMatrix", "dgeMatrix"))) {
-                    cat(paste0(slot, ":"), nrow(data), "features\n")
-                }
-                if (inherits(data, "H5D")) {
-                    if (length(data$dims) == 1) {
-                        cat(paste0(slot, ":"), data$dims,
-                            "non-zero values in H5D object\n")
-                    } else {
-                        cat(paste0(slot, ":"),
-                            paste(data$dims, collapse = " x "),
-                            "values in H5D object\n")
-                    }
-                }
-                if (inherits(data, "H5Group")) {
-                    cat(paste0(slot, ":"), data[["data"]]$dims,
-                        "non-zero values in H5Group object\n")
-                }
-            }
-        }
-        # Information for sub-classes added below, in condition statements
-        if ("rawPeak" %in% methods::slotNames(object)) {
-            if (!is.null(rawPeak(object)))
-                cat("rawPeak:", nrow(rawPeak(object)), "regions\n")
-            if (!is.null(normPeak(object)))
-                cat("normPeak:", nrow(normPeak(object)), "regions\n")
-        }
-
-        invisible(x = NULL)
-    }
-)
-
-#' @section Dimensionality:
-#' For a \code{ligerDataset} object, the column orientation is assigned for
-#' cells and rows are for features. Therefore, for \code{ligerDataset} objects,
-#' \code{dim()} returns a numeric vector of two numbers which are number of
-#' features and number of cells. \code{dimnames()} returns a list of two
-#' character vectors, which are the feature names and the cell barcodes.
-#'
-#' For direct call of \code{dimnames<-} method, \code{value} should be a list
-#' with a character vector of feature names as the first element and cell
-#' identifiers as the second element. For \code{colnames<-} method, the
-#' character vector of cell identifiers. For \code{rownames<-} method, the
-#' character vector of feature names.
-#' @section Subsetting:
-#' For more detail of subsetting a \code{liger} object or a
-#' \linkS4class{ligerDataset} object, please check out \code{\link{subsetLiger}}
-#' and \code{\link{subsetLigerDataset}}. Here, we set the S3 method
-#' "single-bracket" \code{[} as a quick wrapper to subset a \code{ligerDataset}
-#' object. \code{i} and \code{j} serves as feature and cell subscriptor,
-#' respectively, which can be any valid index refering the available features
-#' and cells in a dataset. \code{...} arugments are passed to
-#' \code{subsetLigerDataset} so that advanced options are allowed.
-#' @rdname ligerDataset-class
-#' @export
-setMethod("dim", "ligerDataset", function(x) {
-    nr <- length(x@rownames)
-    nc <- length(x@colnames)
-    c(nr, nc)
-})
-
-#' @rdname ligerDataset-class
-#' @export
-setMethod("dimnames", "ligerDataset", function(x) {
-    rn <- x@rownames
-    cn <- x@colnames
-    list(rn, cn)
-})
-
-#' @rdname ligerDataset-class
-#' @export
-setReplaceMethod("dimnames", c("ligerDataset", "list"), function(x, value) {
-    if (!isH5Liger(x)) {
-        if (!is.null(rawData(x))) {
-            rownames(x@rawData) <- value[[1L]]
-            colnames(x@rawData) <- value[[2L]]
-        }
-        if (!is.null(normData(x))) {
-            rownames(x@normData) <- value[[1L]]
-            colnames(x@normData) <- value[[2L]]
-        }
-        if (!is.null(scaleData(x))) {
-            colnames(x@scaleData) <- value[[2L]]
-            rownames(x@scaleData) <-
-                value[[1L]][.getVarFtIdx(x@rownames, rownames(x@scaleData))]
-        }
-        if (!is.null(x@scaleUnsharedData)) {
-            colnames(x@scaleUnsharedData) <- value[[2L]]
-            rownames(x@scaleUnsharedData) <-
-                value[[1L]][.getVarFtIdx(x@rownames,
-                                         rownames(x@scaleUnsharedData))]
-        }
-    }
-    if (!is.null(x@H))
-        colnames(x@H) <- value[[2L]]
-    if (!is.null(x@V))
-        rownames(x@V) <- value[[1L]][.getVarFtIdx(x@rownames, rownames(x@V))]
-    if (!is.null(x@B))
-        rownames(x@B) <- value[[1L]][.getVarFtIdx(x@rownames, rownames(x@B))]
-    if (!is.null(x@U)) colnames(x@U) <- value[[2L]]
-    if ("rawPeak" %in% methods::slotNames(x)) {
-        if (!is.null(rawPeak(x))) colnames(rawPeak(x)) <- value[[2L]]
-    }
-    if ("normPeak" %in% methods::slotNames(x)) {
-        if (!is.null(normPeak(x))) colnames(normPeak(x)) <- value[[2L]]
-    }
-    if ("coordinate" %in% methods::slotNames(x)) {
-        if (!is.null(coordinate(x))) rownames(coordinate(x)) <- value[[2L]]
-    }
-    x@rownames <- value[[1L]]
-    x@colnames <- value[[2L]]
-    return(x)
-})
-
-.getVarFtIdx <- function(full, var) {
-    # full - character vector of ligerDataset rownames
-    # var - character vector of var features (in scaleData, V), might not follow
-    # the original order of `full`
-    # return numeric value that select ordered corresponding replacement from
-    # `dimnames<-`'s value[[1]]
-    fullNamedIdx <- seq_along(full)
-    names(fullNamedIdx) <- full
-    varNumIdx <- fullNamedIdx[var]
-    names(varNumIdx) <- NULL
-    return(varNumIdx)
-}
-
-#' Subset ligerDataset object
-#' @name sub-ligerDataset
-#' @param x A \linkS4class{ligerDataset} object
-#' @param i Numeric, logical index or character vector of feature names to
-#' subscribe. Leave missing for all features.
-#' @param j Numeric, logical index or character vector of cell IDs to subscribe.
-#' Leave missing for all cells.
-#' @param ... Additional arguments passed to \code{\link{subsetLigerDataset}}.
-#' @export
-#' @method [ ligerDataset
-#' @return If \code{i} is given, the selected metadata will be returned; if it
-#' is missing, the whole cell metadata table in
-#' \code{S4Vectors::\link[S4Vectors]{DataFrame}} class will be returned.
-#' @examples
-#' ctrl <- dataset(pbmc, "ctrl")
-#' ctrl[1:5, 1:5]
-`[.ligerDataset` <- function(x, i, j, ...) {
-    if (missing(i) && missing(j)) {
-        return(x)
-    }
-    if (missing(i)) i <- NULL
-    if (missing(j)) j <- NULL
-    subsetLigerDataset(x, featureIdx = i, cellIdx = j, ...)
-}
-
-
-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-# Raw, norm, scale data access ####
-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-#' @section Matrix access:
-#' For \code{ligerDataset} object, \code{rawData()}, \code{normData},
-#' \code{scaleData()} and \code{scaleUnsharedData()} methods are exported for
-#' users to access the corresponding feature expression matrix. Replacement
-#' methods are also available to modify the slots.
-#'
-#' For other matrices, such as the \eqn{H} and \eqn{V}, which are dataset
-#' specific, please use \code{getMatrix()} method with specifying slot name.
-#' Directly accessing slot with \code{@} is generally not recommended.
-#' @export
-#' @rdname ligerDataset-class
-setGeneric("rawData", function(x, dataset = NULL) standardGeneric("rawData"))
-
-#' @export
-#' @rdname ligerDataset-class
-setGeneric(
-    "rawData<-",
-    function(x, dataset = NULL, check = TRUE, value) standardGeneric("rawData<-")
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setMethod("rawData", "ligerDataset",
-          function(x, dataset = NULL) x@rawData)
-
-#' @export
-#' @rdname liger-class
-setMethod("rawData", c("liger", "ANY"),
-          function(x, dataset = NULL) {
-              if (is.null(dataset)) {
-                  getMatrix(x, slot = "rawData", returnList = TRUE)
-              } else {
-                  getMatrix(x, "rawData", dataset = dataset)
-              }
-          }
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setReplaceMethod(
-    "rawData",
-    signature(x = "ligerDataset", dataset = "ANY", check = "ANY", value = "matrixLike_OR_NULL"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        if (isH5Liger(x))
-            stop("Cannot replace slot with in-memory data for H5 based object.")
-        x@rawData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setReplaceMethod(
-    "rawData",
-    signature(x = "ligerDataset", dataset = "ANY", check = "ANY", value = "H5D"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        if (!isH5Liger(x))
-            stop("Cannot replace slot with on-disk data for in-memory object.")
-        x@rawData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname liger-class
-setReplaceMethod(
-    "rawData",
-    signature(x = "liger", dataset = "ANY", check = "ANY", value = "matrixLike_OR_NULL"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        dataset <- .checkUseDatasets(x, dataset)
-        if (length(dataset) != 1) stop("Need to specify one dataset to insert.")
-        if (isH5Liger(x, dataset))
-            stop("Cannot replace slot with in-memory data for H5 based object.")
-        x@datasets[[dataset]]@rawData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname liger-class
-setReplaceMethod(
-    "rawData",
-    signature(x = "liger", dataset = "ANY", check = "ANY", value = "H5D"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        dataset <- .checkUseDatasets(x, dataset)
-        if (length(dataset) != 1) stop("Need to specify one dataset to insert.")
-        if (!isH5Liger(x, dataset))
-            stop("Cannot replace slot with on-disk data for in-memory object.")
-        x@datasets[[dataset]]@rawData <- value
-        if (isTRUE(check)) methods::validObject(x@datasets[[dataset]])
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setGeneric("normData", function(x, dataset = NULL) standardGeneric("normData"))
-
-#' @export
-#' @rdname ligerDataset-class
-setGeneric(
-    "normData<-",
-    function(x, dataset = NULL, check = TRUE, value) standardGeneric("normData<-")
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setMethod("normData", "ligerDataset",
-          function(x, dataset = NULL) x@normData)
-
-#' @export
-#' @rdname liger-class
-setMethod("normData", c("liger", "ANY"),
-          function(x, dataset = NULL) {
-              if (is.null(dataset)) {
-                  getMatrix(x, slot = "normData", returnList = TRUE)
-              } else {
-                  getMatrix(x, "normData", dataset = dataset)
-              }
-          }
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setReplaceMethod(
-    "normData",
-    signature(x = "ligerDataset", dataset = "ANY", check = "ANY", value = "matrixLike_OR_NULL"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        if (isH5Liger(x))
-            stop("Cannot replace slot with in-memory data for H5 based object.")
-        x@normData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setReplaceMethod(
-    "normData",
-    signature(x = "ligerDataset", dataset = "ANY", check = "ANY", value = "H5D"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        if (!isH5Liger(x))
-            stop("Cannot replace slot with on-disk data for in-memory object.")
-        x@normData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname liger-class
-setReplaceMethod(
-    "normData",
-    signature(x = "liger", dataset = "ANY", check = "ANY", value = "matrixLike_OR_NULL"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        dataset <- .checkUseDatasets(x, dataset)
-        if (length(dataset) != 1) stop("Need to specify one dataset to insert.")
-        if (isH5Liger(x, dataset))
-            stop("Cannot replace slot with in-memory data for H5 based object.")
-        x@datasets[[dataset]]@normData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname liger-class
-setReplaceMethod(
-    "normData",
-    signature(x = "liger", dataset = "ANY", check = "ANY", value = "H5D"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        dataset <- .checkUseDatasets(x, dataset)
-        if (length(dataset) != 1) stop("Need to specify one dataset to insert.")
-        if (!isH5Liger(x, dataset))
-            stop("Cannot replace slot with on-disk data for in-memory object.")
-        x@datasets[[dataset]]@normData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setGeneric(
-    "scaleData",
-    function(x, dataset = NULL) standardGeneric("scaleData")
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setGeneric(
-    "scaleData<-",
-    function(x, dataset = NULL, check = TRUE, value) standardGeneric("scaleData<-")
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setMethod("scaleData", c("ligerDataset", "missing"),
-          function(x, dataset = NULL) x@scaleData)
-
-#' @export
-#' @rdname liger-class
-setMethod(
-    "scaleData",
-    signature(x = "liger", dataset = "ANY"),
-    function(x, dataset = NULL) {
-        if (is.null(dataset)) {
-            getMatrix(x, slot = "scaleData", returnList = TRUE)
-        } else {
-            getMatrix(x, "scaleData", dataset = dataset)
-        }
-    }
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setReplaceMethod(
-    "scaleData",
-    signature(x = "ligerDataset", dataset = "ANY", check = "ANY", value = "matrixLike_OR_NULL"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        if (isH5Liger(x))
-            stop("Cannot replace slot with in-memory data for H5 based object.")
-        x@scaleData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setReplaceMethod(
-    "scaleData",
-    signature(x = "ligerDataset", dataset = "ANY", check = "ANY", value = "H5D"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        if (!isH5Liger(x))
-            stop("Cannot replace slot with on-disk data for in-memory object.")
-        x@scaleData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setReplaceMethod(
-    "scaleData",
-    signature(x = "ligerDataset", dataset = "ANY", check = "ANY", value = "H5Group"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        if (!isH5Liger(x))
-            stop("Cannot replace slot with on-disk data for in-memory object.")
-        x@scaleData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname liger-class
-setReplaceMethod(
-    "scaleData",
-    signature(x = "liger", dataset = "ANY", check = "ANY", value = "matrixLike_OR_NULL"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        dataset <- .checkUseDatasets(x, dataset)
-        if (length(dataset) != 1) stop("Need to specify one dataset to insert.")
-        if (isH5Liger(x, dataset))
-            stop("Cannot replace slot with in-memory data for H5 based object.")
-        x@datasets[[dataset]]@scaleData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname liger-class
-setReplaceMethod(
-    "scaleData",
-    signature(x = "liger", dataset = "ANY", check = "ANY", value = "H5D"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        dataset <- .checkUseDatasets(x, dataset)
-        if (length(dataset) != 1) stop("Need to specify one dataset to insert.")
-        if (!isH5Liger(x, dataset))
-            stop("Cannot replace slot with on-disk data for in-memory object.")
-        x@datasets[[dataset]]@scaleData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname liger-class
-setReplaceMethod(
-    "scaleData",
-    signature(x = "liger", dataset = "ANY", check = "ANY", value = "H5Group"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        dataset <- .checkUseDatasets(x, dataset)
-        if (length(dataset) != 1) stop("Need to specify one dataset to insert.")
-        if (!isH5Liger(x, dataset))
-            stop("Cannot replace slot with on-disk data for in-memory object.")
-        x@datasets[[dataset]]@scaleData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setGeneric(
-    "scaleUnsharedData",
-    function(x, dataset = NULL) standardGeneric("scaleUnsharedData")
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setGeneric(
-    "scaleUnsharedData<-",
-    function(x, dataset = NULL, check = TRUE, value) standardGeneric("scaleUnsharedData<-")
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setMethod("scaleUnsharedData", c("ligerDataset", "missing"),
-          function(x, dataset = NULL) x@scaleUnsharedData)
-
-#' @export
-#' @rdname liger-class
-setMethod(
-    "scaleUnsharedData",
-    signature(x = "liger", dataset = "character"),
-    function(x, dataset) {
-        scaleUnsharedData(dataset(x, dataset))
-    }
-)
-
-#' @export
-#' @rdname liger-class
-setMethod(
-    "scaleUnsharedData",
-    signature(x = "liger", dataset = "numeric"),
-    function(x, dataset) {
-        scaleUnsharedData(dataset(x, dataset))
-    }
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setReplaceMethod(
-    "scaleUnsharedData",
-    signature(x = "ligerDataset", dataset = "missing", check = "ANY", value = "matrixLike_OR_NULL"),
-    function(x, check = TRUE, value) {
-        if (isH5Liger(x))
-            stop("Cannot replace slot with in-memory data for H5 based object.")
-        x@scaleUnsharedData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setReplaceMethod(
-    "scaleUnsharedData",
-    signature(x = "ligerDataset", dataset = "missing", check = "ANY", value = "H5D"),
-    function(x, check = TRUE, value) {
-        if (!isH5Liger(x))
-            stop("Cannot replace slot with on-disk data for in-memory object.")
-        x@scaleUnsharedData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setReplaceMethod(
-    "scaleUnsharedData",
-    signature(x = "ligerDataset", dataset = "missing", check = "ANY", value = "H5Group"),
-    function(x, check = TRUE, value) {
-        if (!isH5Liger(x))
-            stop("Cannot replace slot with on-disk data for in-memory object.")
-        x@scaleUnsharedData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname liger-class
-setReplaceMethod(
-    "scaleUnsharedData",
-    signature(x = "liger", dataset = "ANY", check = "ANY", value = "matrixLike_OR_NULL"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        dataset <- .checkUseDatasets(x, dataset)
-        if (length(dataset) != 1) stop("Need to specify one dataset to insert.")
-        if (isH5Liger(x, dataset))
-            stop("Cannot replace slot with in-memory data for H5 based object.")
-        x@datasets[[dataset]]@scaleUnsharedData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname liger-class
-setReplaceMethod(
-    "scaleUnsharedData",
-    signature(x = "liger", dataset = "ANY", check = "ANY", value = "H5D"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        dataset <- .checkUseDatasets(x, dataset)
-        if (length(dataset) != 1) stop("Need to specify one dataset to insert.")
-        if (!isH5Liger(x, dataset))
-            stop("Cannot replace slot with on-disk data for in-memory object.")
-        x@datasets[[dataset]]@scaleUnsharedData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname liger-class
-setReplaceMethod(
-    "scaleUnsharedData",
-    signature(x = "liger", dataset = "ANY", check = "ANY", value = "H5Group"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        dataset <- .checkUseDatasets(x, dataset)
-        if (length(dataset) != 1) stop("Need to specify one dataset to insert.")
-        if (!isH5Liger(x, dataset))
-            stop("Cannot replace slot with on-disk data for in-memory object.")
-        x@datasets[[dataset]]@scaleUnsharedData <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-
-
-#' @export
-#' @rdname ligerDataset-class
-setGeneric(
-    "getMatrix",
-    function(x, slot = "rawData", dataset = NULL, returnList = FALSE) {
-        standardGeneric("getMatrix")
-    }
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setMethod(
-    "getMatrix", signature(x = "ligerDataset", dataset = "missing",
-                           returnList = "missing"),
-    function(x,
-             slot = c("rawData", "normData", "scaleData",
-                      "scaleUnsharedData", "H", "V", "U", "A", "B"),
-             dataset = NULL) {
-        # TODO: Currently directly find the data with slot, but need to
-        # think about maintainability when we need to change slot name.
-        slot <- match.arg(slot)
-        methods::slot(x, slot)
-    })
-
-#' @export
-#' @rdname liger-class
-setMethod(
-    "getMatrix", signature(x = "liger"),
-    function(x,
-             slot = c("rawData", "normData", "scaleData",
-                      "scaleUnsharedData", "H", "V", "U", "A", "B",
-                      "W", "H.norm"),
-             dataset = NULL,
-             returnList = FALSE) {
-        slot <- match.arg(slot)
-        if (slot == "W") return(x@W)
-        if (slot == "H.norm") return(x@H.norm)
-        if (is.null(dataset)) {
-            return(lapply(datasets(x), function(ld) getMatrix(ld, slot)))
-        } else {
-            if (length(dataset) == 1) {
-                if (isTRUE(returnList)) {
-                    result <- list(getMatrix(dataset(x, dataset), slot))
-                    names(result) <- dataset
-                    return(result)
-                } else if (isFALSE(returnList))
-                    return(getMatrix(dataset(x, dataset), slot))
-            } else {
-                lds <- datasets(x)[dataset]
-                return(lapply(lds, function(ld) getMatrix(ld, slot)))
-            }
-        }
-    })
-
-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-# H5 related ####
-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-#' @section H5 file and information access:
-#' A \code{ligerDataset} object has a slot called \code{h5fileInfo}, which is a
-#' list object. The first element is called \code{$H5File}, which is an
-#' \code{H5File} class object and is the connection to the input file. The
-#' second element is \code{$filename} which stores the absolute path of the H5
-#' file in the current machine. The third element \code{$formatType} stores the
-#' name of preset being used, if applicable. The other following keys pair with
-#' paths in the H5 file that point to specific data for constructing a feature
-#' expression matrix.
-#'
-#' \code{h5fileInfo()} method access the list described above and simply
-#' retrieves the corresponding value. When \code{info = NULL}, returns the whole
-#' list. When \code{length(info) == 1}, returns the requested list value. When
-#' more info requested, returns a subset list.
-#'
-#' The replacement method modifies the list elements and corresponding slot
-#' value (if applicable) at the same time. For example, running
-#' \code{h5fileInfo(obj, "rawData") <- newPath} not only updates the list, but
-#' also updates the \code{rawData} slot with the \code{H5D} class data at
-#' "newPath" in the \code{H5File} object.
-#'
-#' \code{getH5File()} is a wrapper and is equivalent to
-#' \code{h5fileInfo(obj, "H5File")}.
-#' @export
-#' @rdname ligerDataset-class
-setGeneric("h5fileInfo", function(x, info = NULL) standardGeneric("h5fileInfo"))
-
-#' @export
-#' @rdname ligerDataset-class
-setGeneric(
-    "h5fileInfo<-",
-    function(x, info = NULL, check = TRUE, value) {
-        standardGeneric("h5fileInfo<-")
-    }
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setMethod(
-    "h5fileInfo",
-    signature = signature(x = "ligerDataset", info = "ANY"),
-    function(x, info = NULL) {
-        if (is.null(info)) result <- x@h5fileInfo
-        else {
-            if (length(info) == 1) result <- x@h5fileInfo[[info]]
-            else {
-                if (any(!info %in% names(x@h5fileInfo))) {
-                    stop("Specified h5file info not found: ",
-                         paste(info[!info %in% names(x@h5fileInfo)],
-                               collapse = ", "))
-                }
-                result <- x@h5fileInfo[info]
-                names(result) <- info
-            }
-        }
-        return(result)
-    })
-
-#' @export
-#' @rdname ligerDataset-class
-setReplaceMethod(
-    "h5fileInfo",
-    signature = signature(
-        x = "ligerDataset",
-        info = "ANY",
-        check = "ANY",
-        value = "ANY"
-    ),
-    function(x, info = NULL, check = TRUE, value) {
-        if (is.null(info)) {
-            x@h5fileInfo <- value
-        } else {
-            if (!is.character(info) | length(info) != 1)
-                stop("`info` has to be a single character.")
-            if (info %in% c("indicesName", "indptrName", "barcodesName",
-                            "genesName", "rawData", "normData",
-                            "scaleData")) {
-                if (!getH5File(x)$exists(value)) {
-                    stop("Specified info is invalid, '", info,
-                         "' does not exists in the HDF5 file.")
-                }
-            }
-            x@h5fileInfo[[info]] <- value
-            if (info %in% c("rawData", "normData", "scaleData",
-                            "scaleUnsharedData")) {
-                x <- do.call(paste0(info, "<-"),
-                             list(x = x,
-                                  value = getH5File(x)[[h5fileInfo(x, info)]],
-                                  check = check))
-            }
-        }
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#' @export
-#' @rdname ligerDataset-class
-setGeneric("getH5File", function(x, dataset = NULL) standardGeneric("getH5File"))
-
-#' @export
-#' @rdname ligerDataset-class
-setMethod("getH5File",
-          signature = signature(x = "ligerDataset", dataset = "missing"),
-          function(x, dataset = NULL) h5fileInfo(x, "H5File"))
-
-#' @export
-#' @rdname liger-class
-setMethod("getH5File",
-          signature = signature(x = "liger", dataset = "ANY"),
-          function(x, dataset = NULL) {
-              if (is.null(dataset)) dataset <- names(x)
-              dataset <- .checkUseDatasets(x, dataset)
-              results <- lapply(datasets(x)[dataset],
-                                function(ld) h5fileInfo(ld, "H5File"))
-              if (length(results) == 1) results <- results[[1]]
-              results
-          })
-
-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-# Feature metadata ####
-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-#' @section Feature metadata access:
-#' A slot \code{featureMeta} is included for each \code{ligerDataset} object.
-#' This slot requires a \code{\link[S4Vectors]{DataFrame-class}} object, which
-#' is the same as \code{cellMeta} slot of a \linkS4class{liger} object. However,
-#' the associated S4 methods only include access to the whole table for now.
-#' Internal information access follows the same way as data.frame operation.
-#' For example, \code{featureMeta(ligerD)$nCell} or
-#' \code{featureMeta(ligerD)[varFeatures(ligerObj), "gene_var"]}.
-#' @export
-#' @rdname ligerDataset-class
-setGeneric("featureMeta", function(x, check = NULL) {
-    standardGeneric("featureMeta")
-})
-
-#' @export
-#' @rdname ligerDataset-class
-setGeneric("featureMeta<-", function(x, check = TRUE, value) {
-    standardGeneric("featureMeta<-")
-})
-
-#' @export
-#' @rdname ligerDataset-class
-setMethod("featureMeta", signature(x = "ligerDataset", check = "ANY"),
-          function(x, check = NULL) {
-    x@featureMeta
-})
-
-#' @export
-#' @rdname ligerDataset-class
-setReplaceMethod(
-    "featureMeta",
-    signature(x = "ligerDataset", check = "ANY"),
-    function(x, check = TRUE, value) {
-        if (!inherits(value, "DFrame"))
-            value <- S4Vectors::DataFrame(value)
-        x@featureMeta <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    }
-)
-
-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-# S3 Method ####
-#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-#' @section Concatenate ligerDataset:
-#' \code{cbind()} method is implemented for concatenating \code{ligerDataset}
-#' objects by cells. When applying, all feature expression matrix will be merged
-#' with taking a union of all features for the rows.
-#' @param deparse.level Not used here.
-#' @rdname ligerDataset-class
-#' @export
-#' @method cbind ligerDataset
-cbind.ligerDataset <- function(x, ...,
-                               deparse.level = 1) {
-    args <- list(...)
-    isLD <- sapply(args, function(x) inherits(x, "ligerDataset"))
-    if (any(!isLD)) {
-        warning("Discarding arguments that are not of ligerDataset class")
-        args <- args[isLD]
-    }
-    if (!missing(x)) args <- c(list(x), args)
-    isH5 <- sapply(args, isH5Liger)
-    # See mergeObject.R
-    if (all(isH5)) .cbind.ligerDataset.h5(args)
-    else if (!any(isH5)) .cbind.ligerDataset.mem(args)
-    else
-        stop("Cannot `cbind` a hybrid of H5 ligerDatasets and ",
-             "in-memory ligerDatasets for now.")
-}
diff --git a/R/ligerDataset-methods.R b/R/ligerDataset-methods.R
new file mode 100644
index 00000000..7ee9d8c2
--- /dev/null
+++ b/R/ligerDataset-methods.R
@@ -0,0 +1,598 @@
+
+
+#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+# Dataset creatinfg function ####
+#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+#' Check if a liger or ligerDataset object is made of HDF5 file
+#' @param object A liger or ligerDataset object.
+#' @param dataset If \code{object} is of liger class, check a specific dataset.
+#' If \code{NULL}, Check if all datasets are made of HDF5 file. Default
+#' \code{NULL}.
+#' @return \code{TRUE} or \code{FALSE} for the specified check.
+#' @export
+#' @examples
+#' isH5Liger(pbmc)
+#' isH5Liger(pbmc, "ctrl")
+#' ctrl <- dataset(pbmc, "ctrl")
+#' isH5Liger(ctrl)
+isH5Liger <- function(object, dataset = NULL) {
+    if (inherits(object, "ligerDataset")) {
+        if (length(object@h5fileInfo) == 0) {
+            return(FALSE)
+        } else {
+            return(TRUE)
+        }
+    } else if (inherits(object, "liger")) {
+        dataset <- .checkUseDatasets(object, dataset)
+        if (length(dataset) == 0) return(FALSE)
+        allCheck <- unlist(lapply(datasets(object)[dataset], isH5Liger))
+        return(all(allCheck))
+    } else {
+        cli::cli_alert_danger("Given object is not of {.cls liger} or {.cls ligerDataset} class.")
+        return(FALSE)
+    }
+}
+
+#' Return preset modality of a ligerDataset object or that of all datasets in a
+#' liger object
+#' @param object a \linkS4class{ligerDataset} object or a \linkS4class{liger}
+#' object
+#' @return A single character of modality setting value for
+#' \linkS4class{ligerDataset} \code{object}, or a named vector for
+#' \linkS4class{liger} object, where the names are dataset names.
+#' @export
+#' @examples
+#' modalOf(pbmc)
+#' ctrl <- dataset(pbmc, "ctrl")
+#' modalOf(ctrl)
+#' ctrl.atac <- as.ligerDataset(ctrl, modal = "atac")
+#' modalOf(ctrl.atac)
+modalOf <- function(object) {
+    if (inherits(object, "ligerDataset")) {
+        if (class(object) %in% names(.classModalDict))
+            return(.classModalDict[[class(object)]])
+        else {
+            warning("DEVELOPERS, please add this ligerDataset sub-class to ",
+                    "`.classModalDict`", immediate. = TRUE)
+            return("UNKNOWN")
+        }
+    } else if (inherits(object, "liger")) {
+        return(sapply(datasets(object), modalOf))
+    }
+}
+
+#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+# S4 Methods ####
+#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#' @param x,object A \code{ligerDataset} object.
+#' @param dataset Not applicable for \code{ligerDataset} methods.
+#' @param value See detail sections for requirements
+#' @param check Whether to perform object validity check on setting new value.
+#' @param info Name of the entry in \code{h5fileInfo} slot.
+#' @param slot The slot name when using \code{getMatrix}.
+#' @param returnList Not applicable for \code{ligerDataset} methods.
+#' @param ... See detailed sections for explanation.
+#' @rdname ligerDataset-class
+#' @export
+#' @examples
+#' ctrl <- dataset(pbmc, "ctrl")
+#'
+#' # Methods for base generics
+#' ctrl
+#' print(ctrl)
+#' dim(ctrl)
+#' ncol(ctrl)
+#' nrow(ctrl)
+#' colnames(ctrl)[1:5]
+#' rownames(ctrl)[1:5]
+#' ctrl[1:5, 1:5]
+#'
+#' # rliger generics
+#' ## raw data
+#' m <- rawData(ctrl)
+#' class(m)
+#' dim(m)
+#' ## normalized data
+#' pbmc <- normalize(pbmc)
+#' ctrl <- dataset(pbmc, "ctrl")
+#' m <- normData(ctrl)
+#' class(m)
+#' dim(m)
+#' ## scaled data
+#' pbmc <- selectGenes(pbmc)
+#' pbmc <- scaleNotCenter(pbmc)
+#' ctrl <- dataset(pbmc, "ctrl")
+#' m <- scaleData(ctrl)
+#' class(m)
+#' dim(m)
+#' n <- scaleData(pbmc, "ctrl")
+#' identical(m, n)
+#' ## Any other matrices
+#' if (requireNamespace("RcppPlanc", quietly = TRUE)) {
+#'     pbmc <- runOnlineINMF(pbmc, k = 20, minibatchSize = 100)
+#'     ctrl <- dataset(pbmc, "ctrl")
+#'     V <- getMatrix(ctrl, "V")
+#'     V[1:5, 1:5]
+#'     Vs <- getMatrix(pbmc, "V")
+#'     length(Vs)
+#'     names(Vs)
+#'     identical(Vs$ctrl, V)
+#' }
+setMethod(
+    f = "show",
+    signature(object = "ligerDataset"),
+    definition = function(object) {
+        # Use class(object) so that the inheriting classes can be shown properly
+        cat("An object of class", class(object), "with",
+            ncol(object), "cells\n")
+        if (isH5Liger(object) &
+            !isTRUE(methods::validObject(object, test = TRUE))) {
+            cli::cli_alert_danger("Link to HDF5 file fails. Please try running {.code restoreH5Liger(object)}.")
+            return()
+        }
+        for (slot in c("rawData", "normData", "scaleData",
+                       "scaleUnsharedData")) {
+            data <- methods::slot(object, slot)
+            if (!is.null(data)) {
+                if (inherits(data, c("matrix", "dgCMatrix",
+                                     "dgTMatrix", "dgeMatrix"))) {
+                    cat(paste0(slot, ":"), nrow(data), "features\n")
+                }
+                if (inherits(data, "H5D")) {
+                    if (length(data$dims) == 1) {
+                        cat(paste0(slot, ":"), data$dims,
+                            "non-zero values in H5D object\n")
+                    } else {
+                        cat(paste0(slot, ":"),
+                            paste(data$dims, collapse = " x "),
+                            "values in H5D object\n")
+                    }
+                }
+                if (inherits(data, "H5Group")) {
+                    cat(paste0(slot, ":"), data[["data"]]$dims,
+                        "non-zero values in H5Group object\n")
+                }
+            }
+        }
+        # Information for sub-classes added below, in condition statements
+        if ("rawPeak" %in% methods::slotNames(object)) {
+            if (!is.null(rawPeak(object)))
+                cat("rawPeak:", nrow(rawPeak(object)), "regions\n")
+            if (!is.null(normPeak(object)))
+                cat("normPeak:", nrow(normPeak(object)), "regions\n")
+        }
+
+        invisible(x = NULL)
+    }
+)
+
+#' @section Dimensionality:
+#' For a \code{ligerDataset} object, the column orientation is assigned for
+#' cells and rows are for features. Therefore, for \code{ligerDataset} objects,
+#' \code{dim()} returns a numeric vector of two numbers which are number of
+#' features and number of cells. \code{dimnames()} returns a list of two
+#' character vectors, which are the feature names and the cell barcodes.
+#'
+#' For direct call of \code{dimnames<-} method, \code{value} should be a list
+#' with a character vector of feature names as the first element and cell
+#' identifiers as the second element. For \code{colnames<-} method, the
+#' character vector of cell identifiers. For \code{rownames<-} method, the
+#' character vector of feature names.
+#' @section Subsetting:
+#' For more detail of subsetting a \code{liger} object or a
+#' \linkS4class{ligerDataset} object, please check out \code{\link{subsetLiger}}
+#' and \code{\link{subsetLigerDataset}}. Here, we set the S3 method
+#' "single-bracket" \code{[} as a quick wrapper to subset a \code{ligerDataset}
+#' object. \code{i} and \code{j} serves as feature and cell subscriptor,
+#' respectively, which can be any valid index refering the available features
+#' and cells in a dataset. \code{...} arugments are passed to
+#' \code{subsetLigerDataset} so that advanced options are allowed.
+#' @rdname ligerDataset-class
+#' @export
+setMethod("dim", "ligerDataset", function(x) {
+    nr <- length(x@rownames)
+    nc <- length(x@colnames)
+    c(nr, nc)
+})
+
+#' @rdname ligerDataset-class
+#' @export
+setMethod("dimnames", "ligerDataset", function(x) {
+    rn <- x@rownames
+    cn <- x@colnames
+    list(rn, cn)
+})
+
+#' @rdname ligerDataset-class
+#' @export
+setReplaceMethod("dimnames", c("ligerDataset", "list"), function(x, value) {
+    if (!isH5Liger(x)) {
+        if (!is.null(rawData(x))) {
+            rownames(x@rawData) <- value[[1L]]
+            colnames(x@rawData) <- value[[2L]]
+        }
+        if (!is.null(normData(x))) {
+            rownames(x@normData) <- value[[1L]]
+            colnames(x@normData) <- value[[2L]]
+        }
+        if (!is.null(scaleData(x))) {
+            colnames(x@scaleData) <- value[[2L]]
+            rownames(x@scaleData) <-
+                value[[1L]][match(rownames(x@scaleData), x@rownames)]
+        }
+        if (!is.null(x@scaleUnsharedData)) {
+            colnames(x@scaleUnsharedData) <- value[[2L]]
+            rownames(x@scaleUnsharedData) <-
+                value[[1L]][match(rownames(x@scaleUnsharedData), x@rownames)]
+        }
+    }
+    if (!is.null(x@H))
+        colnames(x@H) <- value[[2L]]
+    if (!is.null(x@V))
+        rownames(x@V) <- value[[1L]][match(rownames(x@V), x@rownames)]
+    if (!is.null(x@B))
+        rownames(x@B) <- value[[1L]][match(rownames(x@B), x@rownames)]
+    if (!is.null(x@U)) colnames(x@U) <- value[[2L]]
+    if ("rawPeak" %in% methods::slotNames(x)) {
+        if (!is.null(rawPeak(x))) colnames(rawPeak(x)) <- value[[2L]]
+    }
+    if ("normPeak" %in% methods::slotNames(x)) {
+        if (!is.null(normPeak(x))) colnames(normPeak(x)) <- value[[2L]]
+    }
+    if ("coordinate" %in% methods::slotNames(x)) {
+        if (!is.null(coordinate(x))) rownames(coordinate(x)) <- value[[2L]]
+    }
+    x@rownames <- value[[1L]]
+    x@colnames <- value[[2L]]
+    return(x)
+})
+
+
+#' Subset ligerDataset object
+#' @name sub-ligerDataset
+#' @param x A \linkS4class{ligerDataset} object
+#' @param i Numeric, logical index or character vector of feature names to
+#' subscribe. Leave missing for all features.
+#' @param j Numeric, logical index or character vector of cell IDs to subscribe.
+#' Leave missing for all cells.
+#' @param ... Additional arguments passed to \code{\link{subsetLigerDataset}}.
+#' @export
+#' @method [ ligerDataset
+#' @return If \code{i} is given, the selected metadata will be returned; if it
+#' is missing, the whole cell metadata table in
+#' \code{S4Vectors::\link[S4Vectors]{DataFrame}} class will be returned.
+#' @examples
+#' ctrl <- dataset(pbmc, "ctrl")
+#' ctrl[1:5, 1:5]
+`[.ligerDataset` <- function(x, i, j, ...) {
+    if (missing(i) && missing(j)) {
+        return(x)
+    }
+    if (missing(i)) i <- NULL
+    if (missing(j)) j <- NULL
+    subsetLigerDataset(x, featureIdx = i, cellIdx = j, ...)
+}
+
+
+#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+# Raw, norm, scale data access ####
+#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+
+
+#' @export
+#' @rdname ligerDataset-class
+setMethod("rawData", "ligerDataset",
+          function(x, dataset = NULL) x@rawData)
+
+#' @export
+#' @rdname ligerDataset-class
+setReplaceMethod(
+    "rawData",
+    signature(x = "ligerDataset", dataset = "ANY", check = "ANY", value = "matrixLike_OR_NULL"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        if (isH5Liger(x))
+            cli::cli_abort("Cannot replace slot with in-memory data for H5 based object.")
+        x@rawData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname ligerDataset-class
+setReplaceMethod(
+    "rawData",
+    signature(x = "ligerDataset", dataset = "ANY", check = "ANY", value = "H5D"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        if (!isH5Liger(x))
+            cli::cli_abort("Cannot replace slot with on-disk data for in-memory object.")
+        x@rawData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+
+#' @export
+#' @rdname ligerDataset-class
+setMethod("normData", "ligerDataset",
+          function(x, dataset = NULL) x@normData)
+
+#' @export
+#' @rdname ligerDataset-class
+setReplaceMethod(
+    "normData",
+    signature(x = "ligerDataset", dataset = "ANY", check = "ANY", value = "matrixLike_OR_NULL"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        if (isH5Liger(x))
+            cli::cli_abort("Cannot replace slot with in-memory data for H5 based object.")
+        x@normData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname ligerDataset-class
+setReplaceMethod(
+    "normData",
+    signature(x = "ligerDataset", dataset = "ANY", check = "ANY", value = "H5D"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        if (!isH5Liger(x))
+            cli::cli_abort("Cannot replace slot with on-disk data for in-memory object.")
+        x@normData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname ligerDataset-class
+setMethod("scaleData", c("ligerDataset", "missing"),
+          function(x, dataset = NULL) x@scaleData)
+
+#' @export
+#' @rdname ligerDataset-class
+setReplaceMethod(
+    "scaleData",
+    signature(x = "ligerDataset", dataset = "ANY", check = "ANY", value = "matrixLike_OR_NULL"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        if (isH5Liger(x))
+            cli::cli_abort("Cannot replace slot with in-memory data for H5 based object.")
+        x@scaleData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname ligerDataset-class
+setReplaceMethod(
+    "scaleData",
+    signature(x = "ligerDataset", dataset = "ANY", check = "ANY", value = "H5D"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        if (!isH5Liger(x))
+            cli::cli_abort("Cannot replace slot with on-disk data for in-memory object.")
+        x@scaleData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname ligerDataset-class
+setReplaceMethod(
+    "scaleData",
+    signature(x = "ligerDataset", dataset = "ANY", check = "ANY", value = "H5Group"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        if (!isH5Liger(x))
+            cli::cli_abort("Cannot replace slot with on-disk data for in-memory object.")
+        x@scaleData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname ligerDataset-class
+setMethod("scaleUnsharedData", c("ligerDataset", "missing"),
+          function(x, dataset = NULL) x@scaleUnsharedData)
+
+#' @export
+#' @rdname ligerDataset-class
+setReplaceMethod(
+    "scaleUnsharedData",
+    signature(x = "ligerDataset", dataset = "missing", check = "ANY", value = "matrixLike_OR_NULL"),
+    function(x, check = TRUE, value) {
+        if (isH5Liger(x))
+            cli::cli_abort("Cannot replace slot with in-memory data for H5 based object.")
+        x@scaleUnsharedData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname ligerDataset-class
+setReplaceMethod(
+    "scaleUnsharedData",
+    signature(x = "ligerDataset", dataset = "missing", check = "ANY", value = "H5D"),
+    function(x, check = TRUE, value) {
+        if (!isH5Liger(x))
+            cli::cli_abort("Cannot replace slot with on-disk data for in-memory object.")
+        x@scaleUnsharedData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname ligerDataset-class
+setReplaceMethod(
+    "scaleUnsharedData",
+    signature(x = "ligerDataset", dataset = "missing", check = "ANY", value = "H5Group"),
+    function(x, check = TRUE, value) {
+        if (!isH5Liger(x))
+            cli::cli_abort("Cannot replace slot with on-disk data for in-memory object.")
+        x@scaleUnsharedData <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname ligerDataset-class
+setMethod(
+    "getMatrix", signature(x = "ligerDataset", dataset = "missing",
+                           returnList = "missing"),
+    function(x,
+             slot = c("rawData", "normData", "scaleData",
+                      "scaleUnsharedData", "H", "V", "U", "A", "B"),
+             dataset = NULL) {
+        # TODO: Currently directly find the data with slot, but need to
+        # think about maintainability when we need to change slot name.
+        slot <- match.arg(slot)
+        methods::slot(x, slot)
+    })
+
+#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+# H5 related ####
+#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+#' @export
+#' @rdname ligerDataset-class
+setMethod(
+    "h5fileInfo",
+    signature = signature(x = "ligerDataset", info = "ANY"),
+    function(x, info = NULL) {
+        if (is.null(info)) result <- x@h5fileInfo
+        else {
+            if (length(info) == 1) result <- x@h5fileInfo[[info]]
+            else {
+                if (any(!info %in% names(x@h5fileInfo))) {
+                    cli::cli_abort(
+                        "Specified {.code info} not found: {.val {info[!info %in% names(x@h5fileInfo)]}}"
+                    )
+                }
+                result <- x@h5fileInfo[info]
+                names(result) <- info
+            }
+        }
+        return(result)
+    })
+
+#' @export
+#' @rdname ligerDataset-class
+setReplaceMethod(
+    "h5fileInfo",
+    signature = signature(
+        x = "ligerDataset",
+        info = "ANY",
+        check = "ANY",
+        value = "ANY"
+    ),
+    function(x, info = NULL, check = TRUE, value) {
+        if (is.null(info)) {
+            x@h5fileInfo <- value
+        } else {
+            if (!is.character(info) | length(info) != 1)
+                cli::cli_abort("{.var info} has to be a single character.")
+            if (info %in% c("indicesName", "indptrName", "barcodesName",
+                            "genesName", "rawData", "normData",
+                            "scaleData")) {
+                if (!getH5File(x)$exists(value)) {
+                    cli::cli_abort("Specified {.var info} is invalid, {.field info} does not exist in the HDF5 file.")
+                }
+            }
+            x@h5fileInfo[[info]] <- value
+            if (info %in% c("rawData", "normData", "scaleData",
+                            "scaleUnsharedData")) {
+                x <- do.call(paste0(info, "<-"),
+                             list(x = x,
+                                  value = getH5File(x)[[h5fileInfo(x, info)]],
+                                  check = check))
+            }
+        }
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+
+#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+# Feature metadata ####
+#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+#' @export
+#' @rdname ligerDataset-class
+setMethod("featureMeta", signature(x = "ligerDataset", check = "ANY"),
+          function(x, check = NULL) {
+    x@featureMeta
+})
+
+#' @export
+#' @rdname ligerDataset-class
+setReplaceMethod(
+    "featureMeta",
+    signature(x = "ligerDataset", check = "ANY"),
+    function(x, check = TRUE, value) {
+        if (!inherits(value, "DFrame"))
+            value <- S4Vectors::DataFrame(value)
+        x@featureMeta <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    }
+)
+
+#' @export
+#' @rdname liger-class
+setMethod("varUnsharedFeatures",
+          signature(x = "ligerDataset", dataset = "missing"),
+          function(x, dataset = NULL) x@varUnsharedFeatures)
+
+#' @export
+#' @rdname liger-class
+setReplaceMethod(
+    "varUnsharedFeatures",
+    signature(x = "ligerDataset", dataset = "missing", check = "ANY", value = "character"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        x@varUnsharedFeatures <- value
+        if (isTRUE(check)) {
+            if (!all(value %in% rownames(x))) {
+                cli::cli_alert_warning("Not all features passed are found.")
+            }
+        }
+        return(x)
+    }
+)
+
+#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+# S3 Method ####
+#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+#' @section Concatenate ligerDataset:
+#' \code{cbind()} method is implemented for concatenating \code{ligerDataset}
+#' objects by cells. When applying, all feature expression matrix will be merged
+#' with taking a union of all features for the rows.
+#' @param deparse.level Not used here.
+#' @rdname ligerDataset-class
+#' @export
+#' @method cbind ligerDataset
+cbind.ligerDataset <- function(x, ...,
+                               deparse.level = 1) {
+    args <- list(...)
+    isLD <- sapply(args, function(x) inherits(x, "ligerDataset"))
+    if (any(!isLD)) {
+        cli::cli_alert_warning("Discarding arguments that are not of {.cls ligerDataset} class")
+        args <- args[isLD]
+    }
+    if (!missing(x)) args <- c(list(x), args)
+    isH5 <- sapply(args, isH5Liger)
+    # See mergeObject.R
+    if (all(isH5)) .cbind.ligerDataset.h5(args)
+    else if (!any(isH5)) .cbind.ligerDataset.mem(args)
+    else
+        cli::cli_abort("Cannot {.fn cbind} a hybrid of H5 and in-memory {.cls ligerDataset}s for now.")
+}
diff --git a/R/ligerDataset_subclass-methods.R b/R/ligerDataset_subclass-methods.R
new file mode 100644
index 00000000..502fb1c7
--- /dev/null
+++ b/R/ligerDataset_subclass-methods.R
@@ -0,0 +1,57 @@
+
+#' @rdname peak
+#' @export
+setMethod("rawPeak", signature(x = "ligerATACDataset", dataset = "missing"),
+          function(x, dataset = NULL) {
+              x@rawPeak
+          })
+
+#' @rdname peak
+#' @export
+setReplaceMethod(
+    "rawPeak",
+    signature(x = "ligerATACDataset", dataset = "missing"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        x@rawPeak <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    })
+
+
+#' @rdname peak
+#' @export
+setMethod("normPeak", signature(x = "ligerATACDataset", dataset = "missing"),
+          function(x, dataset = NULL) {
+              x@normPeak
+          })
+
+#' @rdname peak
+#' @export
+setReplaceMethod(
+    "normPeak",
+    signature(x = "ligerATACDataset", dataset = "missing"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        x@normPeak <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    })
+
+#' @rdname coordinate
+#' @export
+setMethod("coordinate", signature(x = "ligerSpatialDataset", dataset = "missing"),
+          function(x, dataset = NULL) {
+              x@coordinate
+          })
+
+#' @rdname coordinate
+#' @export
+setReplaceMethod(
+    "coordinate",
+    signature(x = "ligerSpatialDataset", dataset = "missing"),
+    function(x, dataset = NULL, check = TRUE, value) {
+        value <- .checkCoords(ld = x, value = value)
+        x@coordinate <- value
+        if (isTRUE(check)) methods::validObject(x)
+        x
+    })
+
diff --git a/R/ligerDataset_subclasses.R b/R/ligerDataset_subclasses.R
deleted file mode 100644
index 46c690a2..00000000
--- a/R/ligerDataset_subclasses.R
+++ /dev/null
@@ -1,336 +0,0 @@
-
-################################################################################
-# Developer guide for adding a new sub-class of `ligerDataset` for new modality
-################################################################################
-#
-# Below is a check-list of the TODOs when new sub-classes need to be added.
-# Please follow them carefully, and refer to existing code as examples.
-#
-# 1. Add `setClass` chunk for defining the new subclass, pay attention to:
-#   a. Naming convention should be `liger{Modal}Dataset`, in camelCase
-#   b. contains = "ligerDataset"
-#   c. add new slots for modality specific information with `representation`
-#   d. if the default new information could be empty, add `prototype`
-# 2. In files `zzz.R`, `import.R`, `classConversion.R`, search for
-#    text "modal". When seeing a multi-option vector argument, add a unique
-#    abbreviation of this new data type to the vector. Don't forget updating
-#    valid options in the manual documentaion as well.
-# 3. If the new slot(s) added is thought to be retrieved by future developers
-#    or users, getter and setter methods MUST be implemented.
-# 4. Please go through the implementation of the following functions in file
-#    `ligerDataset-class.R`, and make sure data in the new slot(s) is properly
-#    handled.
-#   a. .checkLigerDatasetBarcodes()
-#   b. `dimnames<-()` (search: `setReplaceMethod("dimnames"`)
-#   c. `[` (search: "[")
-#
-################################################################################
-
-setClassUnion("matrixLike_OR_NULL", c(
-    "matrix", "dgCMatrix", "dgTMatrix", "dgeMatrix", "NULL"
-))
-
-#' Subclass of ligerDataset for RNA modality
-#' @description Inherits from \linkS4class{ligerDataset} class. Contained slots
-#' can be referred with the link. This subclass does not have any different from
-#' the default \code{ligerDataset} class except the class name.
-#' @export
-#' @exportClass ligerRNADataset
-ligerRNADataset <- setClass(
-    "ligerRNADataset", contains = "ligerDataset"
-)
-
-#-------------------------------------------------------------------------------
-# Sub-class for ATAC data ####
-#-------------------------------------------------------------------------------
-
-#' Subclass of ligerDataset for ATAC modality
-#'
-#' @description Inherits from \linkS4class{ligerDataset} class. Contained slots
-#' can be referred with the link.
-#' @slot rawPeak sparse matrix
-#' @slot normPeak sparse matrix
-#' @exportClass ligerATACDataset
-#' @export
-ligerATACDataset <- setClass(
-    "ligerATACDataset",
-    contains = "ligerDataset",
-    representation = representation(rawPeak = "matrixLike_OR_NULL",
-                                    normPeak = "matrixLike_OR_NULL"),
-    prototype = prototype(rawPeak = NULL, normPeak = NULL)
-)
-
-#' Access ligerATACDataset peak data
-#' @description Similar as how default \linkS4class{ligerDataset} data is
-#' accessed.
-#' @param x \linkS4class{ligerATACDataset} object or a \linkS4class{liger}
-#' object.
-#' @param dataset Name or numeric index of an ATAC dataset.
-#' @param check Logical, whether to perform object validity check on setting new
-#' value.
-#' @param value \code{\link[Matrix]{dgCMatrix-class}} matrix.
-#' @return The retrieved peak count matrix or the updated \code{x} object.
-#' @rdname peak
-#' @export
-setGeneric("rawPeak", function(x, dataset) standardGeneric("rawPeak"))
-
-#' @rdname peak
-#' @export
-setGeneric("rawPeak<-", function(x, dataset, check = TRUE, value) standardGeneric("rawPeak<-"))
-
-#' @rdname peak
-#' @export
-setGeneric("normPeak", function(x, dataset) standardGeneric("normPeak"))
-
-#' @rdname peak
-#' @export
-setGeneric("normPeak<-", function(x, dataset, check = TRUE, value) standardGeneric("normPeak<-"))
-
-#' @rdname peak
-#' @export
-setMethod("rawPeak", signature(x = "liger", dataset = "character"),
-          function(x, dataset) {
-              atac <- dataset(x, dataset)
-              if (!inherits(atac, "ligerATACDataset")) {
-                  stop("Specified dataset is not of ligerATACDataset class.")
-              }
-              atac@rawPeak
-          })
-
-#' @rdname peak
-#' @export
-setReplaceMethod(
-    "rawPeak",
-    signature(x = "liger", dataset = "character"),
-    function(x, dataset, check = TRUE, value) {
-        if (!inherits(dataset(x, dataset), "ligerATACDataset"))
-            stop("Specified dataset is not of `ligerATACDataset` class.")
-        x@datasets[[dataset]]@rawPeak <- value
-        if (isTRUE(check)) methods::validObject(dataset(x, dataset))
-        x
-    })
-
-#' @rdname peak
-#' @export
-setMethod("rawPeak", signature(x = "ligerATACDataset", dataset = "missing"),
-          function(x, dataset = NULL) {
-              x@rawPeak
-          })
-
-#' @rdname peak
-#' @export
-setReplaceMethod(
-    "rawPeak",
-    signature(x = "ligerATACDataset", dataset = "missing"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        x@rawPeak <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    })
-
-#' @rdname peak
-#' @export
-setMethod("normPeak", signature(x = "liger", dataset = "character"),
-          function(x, dataset) {
-              atac <- dataset(x, dataset)
-              if (!inherits(atac, "ligerATACDataset")) {
-                  stop("Specified dataset is not of ligerATACDataset class.")
-              }
-              atac@normPeak
-          })
-
-#' @rdname peak
-#' @export
-setReplaceMethod(
-    "normPeak",
-    signature(x = "liger", dataset = "character"),
-    function(x, dataset, check = TRUE, value) {
-        if (!inherits(dataset(x, dataset), "ligerATACDataset"))
-            stop("Specified dataset is not of `ligerATACDataset` class.")
-        x@datasets[[dataset]]@normPeak <- value
-        if (isTRUE(check)) methods::validObject(dataset(x, dataset))
-        x
-    })
-
-#' @rdname peak
-#' @export
-setMethod("normPeak", signature(x = "ligerATACDataset", dataset = "missing"),
-          function(x, dataset = NULL) {
-              x@normPeak
-          })
-
-#' @rdname peak
-#' @export
-setReplaceMethod(
-    "normPeak",
-    signature(x = "ligerATACDataset", dataset = "missing"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        x@normPeak <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    })
-
-.valid.ligerATACDataset <- function(object) {
-    passSuperClassCheck <- .valid.ligerDataset(object)
-    if (!isTRUE(passSuperClassCheck)) return(passSuperClassCheck)
-    for (slot in c("rawPeak", "normPeak")) {
-        data <- methods::slot(object, slot)
-        if (!is.null(data)) {
-            barcodes.slot <- colnames(data)
-            if (!identical(object@colnames, barcodes.slot)) {
-                return(paste0("Inconsistant cell identifiers in `", slot,
-                              "` slot."))
-            }
-        }
-    }
-}
-
-setValidity("ligerATACDataset", .valid.ligerATACDataset)
-
-#-------------------------------------------------------------------------------
-# Sub-class for Spatial data ####
-#-------------------------------------------------------------------------------
-
-#' Subclass of ligerDataset for Spatial modality
-#'
-#' @description Inherits from \linkS4class{ligerDataset} class. Contained slots
-#' can be referred with the link.
-#' @slot coordinate dense matrix
-#' @exportClass ligerSpatialDataset
-#' @export
-ligerSpatialDataset <- setClass(
-    "ligerSpatialDataset",
-    contains = "ligerDataset",
-    representation = representation(coordinate = "matrix_OR_NULL"),
-    prototype = prototype(coordinate = NULL)
-)
-
-#' Access ligerSpatialDataset coordinate data
-#' @description Similar as how default \linkS4class{ligerDataset} data is
-#' accessed.
-#' @param x \linkS4class{ligerSpatialDataset} object or a \linkS4class{liger}
-#' object.
-#' @param dataset Name or numeric index of an spatial dataset.
-#' @param check Logical, whether to perform object validity check on setting new
-#' value.
-#' @param value \code{\link{matrix}}.
-#' @return The retrieved coordinate matrix or the updated \code{x} object.
-#' @rdname coordinate
-#' @export
-setGeneric("coordinate", function(x, dataset) standardGeneric("coordinate"))
-
-#' @rdname coordinate
-#' @export
-setGeneric("coordinate<-", function(x, dataset, check = TRUE, value) standardGeneric("coordinate<-"))
-
-
-#' @rdname coordinate
-#' @export
-setMethod("coordinate", signature(x = "liger", dataset = "character"),
-          function(x, dataset) {
-              spatial <- dataset(x, dataset)
-              if (!inherits(spatial, "ligerSpatialDataset")) {
-                  stop("Specified dataset is not of `ligerSpatialDataset` class.")
-              }
-              spatial@coordinate
-          })
-
-#' @rdname coordinate
-#' @export
-setReplaceMethod(
-    "coordinate",
-    signature(x = "liger", dataset = "character"),
-    function(x, dataset, check = TRUE, value) {
-        if (!inherits(dataset(x, dataset), "ligerSpatialDataset"))
-            stop("Specified dataset is not of `ligerSpatialDataset` class.")
-        value <- .checkCoords(ld = dataset(x, dataset), value = value)
-        x@datasets[[dataset]]@coordinate <- value
-        if (isTRUE(check)) methods::validObject(dataset(x, dataset))
-        x
-    })
-
-#' @rdname coordinate
-#' @export
-setMethod("coordinate", signature(x = "ligerSpatialDataset", dataset = "missing"),
-          function(x, dataset = NULL) {
-              x@coordinate
-          })
-
-#' @rdname coordinate
-#' @export
-setReplaceMethod(
-    "coordinate",
-    signature(x = "ligerSpatialDataset", dataset = "missing"),
-    function(x, dataset = NULL, check = TRUE, value) {
-        value <- .checkCoords(ld = x, value = value)
-        x@coordinate <- value
-        if (isTRUE(check)) methods::validObject(x)
-        x
-    })
-
-.checkCoords <- function(ld, value) {
-    if (is.null(rownames(value))) {
-        warning("No rownames with given spatial coordinate, ",
-                "assuming they match with the cells.")
-        rownames(value) <- colnames(ld)
-    }
-    if (is.null(colnames(value))) {
-        if (ncol(value) <= 3) {
-            colnames(value) <- c("x", "y", "z")[seq(ncol(value))]
-        } else {
-            stop("More than 3 dimensions for the coordinates but no ",
-                 "colnames are given.")
-        }
-        warning("No colnames with given spatial coordinate, ",
-                "setting to ", paste0(colnames(value), collapse = ", "))
-    }
-    full <- matrix(NA, nrow = ncol(ld), ncol = ncol(value),
-                   dimnames = list(colnames(ld), colnames(value)))
-    cellIsec <- intersect(rownames(value), colnames(ld))
-    full[cellIsec, colnames(value)] <- value[cellIsec,]
-    if (any(is.na(full))) {
-        warning("NA generated for missing cells.")
-    }
-    if (any(!rownames(value) %in% rownames(full))) {
-        warning("Cells in given coordinate not found in the dataset.")
-    }
-    return(full)
-}
-
-.valid.ligerSpatialDataset <- function(object) {
-    passSuperClassCheck <- .valid.ligerDataset(object)
-    if (!isTRUE(passSuperClassCheck)) return(passSuperClassCheck)
-    coord <- object@coordinate
-    if (!is.null(coord)) {
-        barcodes.slot <- rownames(coord)
-        if (!identical(object@colnames, barcodes.slot)) {
-            return(paste0("Inconsistant cell identifiers in `coordinate` slot."))
-        }
-    }
-}
-
-setValidity("ligerSpatialDataset", .valid.ligerSpatialDataset)
-
-
-
-#-------------------------------------------------------------------------------
-# Sub-class for Methylation data ####
-#-------------------------------------------------------------------------------
-
-#' Subclass of ligerDataset for Methylation modality
-#'
-#' @description Inherits from \linkS4class{ligerDataset} class. Contained slots
-#' can be referred with the link. \code{\link{scaleNotCenter}} applied on
-#' datasets of this class will automatically be taken by reversing the
-#' normalized data instead of scaling the variable features.
-#' @exportClass ligerMethDataset
-#' @export
-ligerMethDataset <- setClass(
-    "ligerMethDataset",
-    contains = "ligerDataset"
-)
-
-.valid.ligerMethDataset <- function(object) .valid.ligerDataset(object)
-
-setValidity("ligerMethDataset", .valid.ligerMethDataset)
-
diff --git a/R/preprocess.R b/R/preprocess.R
index 0faa6553..f2bbc703 100644
--- a/R/preprocess.R
+++ b/R/preprocess.R
@@ -20,7 +20,7 @@
 #' @param chunkSize Integer number of cells to include in a chunk when working
 #' on HDF5 based dataset. Default \code{1000}
 #' @param verbose Logical. Whether to show information of the progress. Default
-#' \code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.
+#' \code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.
 #' @return Updated \code{object} with \code{nUMI}, \code{nGene} updated
 #' in \code{cellMeta(object)}, as well as expression percentage value for each
 #' feature subset.
@@ -36,7 +36,7 @@ runGeneralQC <- function(
         pattern = NULL,
         useDatasets = NULL,
         chunkSize = 1000,
-        verbose = getOption("ligerVerbose")
+        verbose = getOption("ligerVerbose", TRUE)
 ) {
     .checkObjVersion(object)
     useDatasets <- .checkUseDatasets(object, useDatasets)
@@ -79,7 +79,8 @@ runGeneralQC <- function(
 
     for (d in useDatasets) {
         ld <- dataset(object, d)
-        if (isTRUE(verbose)) .log('calculating QC for dataset "', d, '"')
+        if (isTRUE(verbose))
+            cliID <- cli::cli_process_start("calculating QC for dataset {.val {d}}")
         if (isH5Liger(ld))
             results <- runGeneralQC.h5(
                 ld,
@@ -96,6 +97,7 @@ runGeneralQC <- function(
         object@cellMeta[object$dataset == d, newResultNames] <- results$cell
         featureMeta(ld, check = FALSE)$nCell <- results$feature
         datasets(object, check = FALSE)[[d]] <- ld
+        if (isTRUE(verbose)) cli::cli_process_done(id = cliID)
     }
 
     return(object)
@@ -111,7 +113,7 @@ runGeneralQC.h5 <- function(
         object,
         featureSubsets = NULL,
         chunkSize = 1000,
-        verbose = getOption("ligerVerbose")) {
+        verbose = getOption("ligerVerbose", TRUE)) {
     allFeatures <- rownames(object)
     # Initialize results
     cell <- data.frame(row.names = colnames(object))
@@ -154,7 +156,7 @@ runGeneralQC.h5 <- function(
 runGeneralQC.Matrix <- function(
         object,
         featureSubsets = NULL,
-        verbose = getOption("ligerVerbose")) {
+        verbose = getOption("ligerVerbose", TRUE)) {
     nUMI <- Matrix::colSums(rawData(object))
     # Instead of using `nonzero <- rawData > 0` which generates dense logical
     # matrix, keep it sparse with 1 for TRUE
@@ -216,7 +218,7 @@ getProportionMito <- function(object, use.norm = FALSE, pattern = "^mt-") {
         result <- c(result, pctMT)
     }
     if (all(result == 0)) {
-        message("Zero proportion detected in all cells")
+        cli::cli_alert_warning("Zero proportion detected in all cells")
     }
     return(result)
 }
@@ -241,7 +243,7 @@ getProportionMito <- function(object, use.norm = FALSE, pattern = "^mt-") {
 #' @param filenameSuffix When subsetting H5-based datasets to new H5 files, this
 #' suffix will be added to all the filenames. Default \code{"removeMissing"}.
 #' @param verbose Logical. Whether to show information of the progress. Default
-#' \code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.
+#' \code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.
 #' @param ... Arguments passed to \code{\link{subsetLigerDataset}}
 #' @return Updated (subset) \code{object}.
 #' @export
@@ -257,19 +259,16 @@ removeMissing <- function(
         useDatasets = NULL,
         newH5 = TRUE,
         filenameSuffix = "removeMissing",
-        verbose = getOption("ligerVerbose"),
+        verbose = getOption("ligerVerbose", TRUE),
         ...
 ) {
-    if (!inherits(object, "liger")) {
-        stop("Please use a `liger` object.")
-    }
     orient <- match.arg(orient)
     useDatasets <- .checkUseDatasets(object, useDatasets)
     minCells <- minCells %||% rep(0, length(useDatasets))
-    minCells <- .checkArgLen(minCells, length(useDatasets))
+    minCells <- .checkArgLen(minCells, length(useDatasets), class = "numeric")
     names(minCells) <- useDatasets
     minFeatures <- minFeatures %||% rep(0, length(useDatasets))
-    minFeatures <- .checkArgLen(minFeatures, length(useDatasets))
+    minFeatures <- .checkArgLen(minFeatures, length(useDatasets), class = "numeric")
     names(minFeatures) <- useDatasets
     rmFeature <- ifelse(orient %in% c("both", "feature"), TRUE, FALSE)
     rmCell <- ifelse(orient %in% c("both", "cell"), TRUE, FALSE)
@@ -293,7 +292,8 @@ removeMissing <- function(
         rmCellDataset <- length(cellIdx) != ncol(ld)
         subsetted <- c(subsetted, any(c(rmFeatureDataset, rmCellDataset)))
         if (any(c(rmFeatureDataset, rmCellDataset))) {
-            if (isTRUE(verbose)) .log("Removing missing in dataset: ", d)
+            if (isTRUE(verbose))
+                cli::cli_alert_info("Removing missing in dataset: {.val {d}}")
             datasets.new[[d]] <- subsetLigerDataset(
                 ld,
                 featureIdx = featureIdx,
@@ -335,11 +335,11 @@ removeMissingObs <- function(
         object,
         slot.use = NULL,
         use.cols = TRUE,
-        verbose = getOption("ligerVerbose")) {
+        verbose = getOption("ligerVerbose", TRUE)) {
     lifecycle::deprecate_warn("1.99.0", "removeMissingObs()",
                               "removeMissing()")
     if (!missing(slot.use)) {
-        warning("Argument `slot.use` is ignored. ")
+        cli::cli_alert_warning("Argument {.code slot.use} is deprecated and ignored.")
     }
     orient <- ifelse(isTRUE(use.cols), "cell", "gene")
     object <- removeMissing(object, orient, verbose = verbose)
@@ -348,10 +348,6 @@ removeMissingObs <- function(
 
 
 
-
-
-
-
 ################################ Normalize #####################################
 
 #' Normalize raw counts data
@@ -399,9 +395,9 @@ normalize.dgCMatrix <- function(
         scaleFactor = NULL,
         ...
 ) {
-    if (!is.null(scaleFactor) && scaleFactor <= 0) {
-        scaleFactor <- .checkArgLen(scaleFactor, ncol(object), repN = TRUE)
-        warning("Invalid `scaleDactor` given. Setting to `NULL`.")
+    scaleFactor <- .checkArgLen(scaleFactor, ncol(object), repN = TRUE, class = "numeric")
+    if (!is.null(scaleFactor) && any(scaleFactor <= 0)) {
+        cli::cli_alert_danger("Invalid {.code scaleFactor} given. Setting to {.code NULL}.")
         scaleFactor <- NULL
     }
     normed <- object
@@ -416,12 +412,12 @@ normalize.dgCMatrix <- function(
 #' @param chunk Integer. Number of maximum number of cells in each chunk when
 #' working on HDF5 file based ligerDataset. Default \code{1000}.
 #' @param verbose Logical. Whether to show information of the progress. Default
-#' \code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.
+#' \code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.
 #' @method normalize ligerDataset
 normalize.ligerDataset <- function(
         object,
         chunk = 1000,
-        verbose = getOption("ligerVerbose"),
+        verbose = getOption("ligerVerbose", TRUE),
         ...
 ) {
     if (!isH5Liger(object)) {
@@ -483,7 +479,7 @@ normalize.ligerDataset <- function(
 normalize.liger <- function(
         object,
         useDatasets = NULL,
-        verbose = getOption("ligerVerbose"),
+        verbose = getOption("ligerVerbose", TRUE),
         format.type = NULL,
         remove.missing = NULL,
         ...
@@ -493,12 +489,13 @@ normalize.liger <- function(
     useDatasets <- .checkUseDatasets(object, useDatasets)
     object <- recordCommand(object, ..., dependencies = "hdf5r")
     for (d in useDatasets) {
+        if (isTRUE(verbose)) cliID <- cli::cli_process_start("Normalizing datasets {.val {d}}")
         # `d` is the name of each dataset
-        if (isTRUE(verbose)) .log("Normalizing dataset: ", d)
         ld <- dataset(object, d)
         ld <- normalize(ld, verbose = verbose, ...)
         datasets(object, check = FALSE)[[d]] <- ld
     }
+    if (isTRUE(verbose)) cli::cli_process_done(id = cliID)
     object
 }
 
@@ -532,25 +529,22 @@ normalize.Seurat <- function(
 normalizePeak <- function(
         object,
         useDatasets = NULL,
-        verbose = getOption("ligerVerbose"),
+        verbose = getOption("ligerVerbose", TRUE),
         ...
 ) {
     useDatasets <- .checkUseDatasets(object, useDatasets, modal = "atac")
     object <- recordCommand(object, ..., dependencies = "hdf5r")
     for (d in useDatasets) {
+        if (isTRUE(verbose)) cliID <- cli::cli_process_start("Normalizing peak of dataset: {.val {d}}")
         # `d` is the name of each dataset
-        if (isTRUE(verbose)) .log("Normalizing rawPeak counts in dataset: ", d)
         ld <- dataset(object, d)
         normPeak(ld, check = FALSE) <- normalize(rawPeak(ld), ...)
         datasets(object, check = FALSE)[[d]] <- ld
+        if (isTRUE(verbose)) cli::cli_process_done(id = cliID)
     }
     object
 }
 
-
-
-
-
 ############################### Select Genes ###################################
 
 #' Select a subset of informative genes
@@ -580,7 +574,7 @@ normalizePeak <- function(
 #' @param combine How to combine variable genes selected from all datasets.
 #' Choose from \code{"union"} or \code{"intersection"}. Default \code{"union"}.
 #' @param verbose Logical. Whether to show information of the progress. Default
-#' \code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.
+#' \code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.
 #' @param ... Arguments passed to other methods.
 #' @return Updated object
 #' \itemize{
@@ -643,7 +637,7 @@ selectGenes.liger <- function(
         unsharedThresh = .1,
         combine = c("union", "intersection"),
         chunk = 1000,
-        verbose = getOption("ligerVerbose"),
+        verbose = getOption("ligerVerbose", TRUE),
         var.thresh = thresh,
         alpha.thresh = alpha,
         num.genes = nGenes,
@@ -670,14 +664,14 @@ selectGenes.liger <- function(
         datasetUnshared <- .checkUseDatasets(object, useUnsharedDatasets)
     else datasetUnshared <- NULL
     useDatasets <- union(datasetShared, datasetUnshared)
-    thresh <- .checkArgLen(thresh, length(datasetShared))
-    nGenes <- .checkArgLen(nGenes, length(datasetShared))
-    unsharedThresh <- .checkArgLen(unsharedThresh, length(datasetUnshared))
+    thresh <- .checkArgLen(thresh, length(datasetShared), class = "numeric")
+    nGenes <- .checkArgLen(nGenes, length(datasetShared), class = "numeric")
+    unsharedThresh <- .checkArgLen(unsharedThresh, length(datasetUnshared), class = "numeric")
     sharedFeature <- Reduce(intersect, lapply(datasets(object), rownames))
     selectList <- list()
     for (d in useDatasets) {
         if (isTRUE(verbose))
-            .log("Selecting variable features for dataset: ", d)
+            cli::cli_alert_info("Selecting variable features for dataset {.val {d}}")
         ld <- dataset(object, d)
         thresh_i <- thresh[datasetShared == d]
         nGenes_i <- nGenes[datasetShared == d]
@@ -695,12 +689,10 @@ selectGenes.liger <- function(
     if (combine == "union") selected <- Reduce(union, selectList)
     else selected <- Reduce(intersect, selectList)
     if (length(selected) == 0) {
-        warning("No genes were selected. Lower `thresh` values or set ",
-                '`combine = "union"`', immediate. = TRUE)
+        cli::cli_alert_danger("No genes were selected. Lower {.code thresh} values or set {.code combine = 'union'}")
     } else {
         if (isTRUE(verbose))
-            .log("Finally ", length(selected),
-                 " shared variable features selected.")
+            cli::cli_alert_success("Finally {length(selected)} shared variable feature{?s} are selected.")
     }
     varFeatures(object) <- selected
     for (d in names(object)) {
@@ -734,9 +726,9 @@ selectGenes.liger <- function(
         unsharedThresh = .1,
         alpha = .99,
         chunk = 1000,
-        verbose = getOption("ligerVerbose")
+        verbose = getOption("ligerVerbose", TRUE)
 ) {
-    if (is.null(normData(object))) stop("Normalized data not available.")
+    if (is.null(normData(object))) cli::cli_abort("Normalized data not available.")
     if (is.null(sharedFeature)) sharedFeature <- rownames(object)
     sharedFeature <- rownames(object) %in% sharedFeature
     unsharedFeature <- !sharedFeature
@@ -760,8 +752,7 @@ selectGenes.liger <- function(
     featureMeta(object, check = FALSE)$isVariable <-
         rownames(object) %in% selected.shared
     if (isTRUE(verbose)) {
-        .log(length(selected.shared), " features selected out of ",
-             sum(sharedFeature), " shared features", level = 2)
+        cli::cli_alert_success("... {length(selected.shared)} feature{?s} selected out of {sum(sharedFeature)} shared feature{?s}.")
     }
     if (isTRUE(unshared) && length(unsharedFeature) > 0) {
         selected.unshared <- .selectGenes.withMetric(
@@ -773,8 +764,7 @@ selectGenes.liger <- function(
         )
         object@varUnsharedFeatures <- selected.unshared
         if (isTRUE(verbose)) {
-            .log(length(selected.unshared), " features selected out of ",
-                 sum(unsharedFeature), " unshared features", level = 2)
+            cli::cli_alert_success("... {length(selected.unshared)} feature{?s} selected out of {sum(unsharedFeature)} unshared feature{?s}.")
         }
     }
     return(object)
@@ -785,11 +775,11 @@ selectGenes.liger <- function(
 #' @param chunkSize Integer for the maximum number of cells in each chunk.
 #' Default \code{1000}.
 #' @param verbose Logical. Whether to show a progress bar. Default
-#' \code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.
+#' \code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.
 #' @return The input \code{object} with calculated var updated in the H5 file.
 #' @noRd
 calcGeneVars.H5 <- function(object, chunkSize = 1000,
-                            verbose = getOption("ligerVerbose")) {
+                            verbose = getOption("ligerVerbose", TRUE)) {
     h5file <- getH5File(object)
     geneVars <- rep(0, nrow(object))
     geneMeans <- h5file[["gene_means"]][]
@@ -831,7 +821,7 @@ selectGenes.Seurat <- function(
         assay = NULL,
         datasetVar = "orig.ident",
         combine = c("union", "intersection"),
-        verbose = getOption("ligerVerbose"),
+        verbose = getOption("ligerVerbose", TRUE),
         ...
 ) {
     combine <- match.arg(combine)
@@ -852,7 +842,7 @@ selectGenes.Seurat <- function(
     featureList <- lapply(matList, rownames)
     allshared <- Reduce(intersect, featureList)
     allFeatures <- SeuratObject::Features(object, assay = assay)
-    thresh <- .checkArgLen(thresh, nlevels(datasetVar))
+    thresh <- .checkArgLen(thresh, nlevels(datasetVar), class = "numeric")
 
     # Get nUMI metric into list
     nUMIVar <- paste0("nCount_", assay)
@@ -863,7 +853,7 @@ selectGenes.Seurat <- function(
     hvg.info <- data.frame(row.names = allFeatures)
     for (d in levels(datasetVar)) {
         if (isTRUE(verbose))
-            .log("Selecting variable features for dataset: ", d)
+            cli::cli_alert_info("Selecting variable features for dataset: {.val {d}}")
         submat <- matList[[d]]
         # submat <- mat[, datasetVar == d, drop = FALSE]
         # submat <- submat[sort(expressed), , drop = FALSE]
@@ -885,20 +875,17 @@ selectGenes.Seurat <- function(
             nGenes = nGenes
         )
         if (isTRUE(verbose)) {
-            .log(length(selected), " features selected out of ",
-                 length(allshared), " shared features", level = 2)
+            cli::cli_alert_success("... {length(selected)} features selected out of {length(allshared)} shared features")
         }
         selectList[[d]] <- selected
     }
     if (combine == "union") selected <- Reduce(union, selectList)
     else selected <- Reduce(intersect, selectList)
     if (length(selected) == 0) {
-        warning("No genes were selected. Lower `thresh` values or set ",
-                '`combine = "union"`', immediate. = TRUE)
+        cli::cli_alert_danger("No genes were selected. Lower {.code thresh} values or set {.code combine = 'union'}")
     } else {
         if (isTRUE(verbose))
-            .log("Finally ", length(selected),
-                 " shared variable features selected.")
+            cli::cli_alert_success("Finally {length(selected)} shared variable features selected.")
     }
     hvg.info$liger.variable <- allFeatures %in% selected
     assayObj <- Seurat::GetAssay(object, assay = assay)
@@ -1041,7 +1028,7 @@ plotVarFeatures <- function(
 #' @param useShared Logical. Whether to only select from genes shared by all
 #' dataset. Default \code{TRUE}.
 #' @param verbose Logical. Whether to show information of the progress. Default
-#' \code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.
+#' \code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.
 #' @references Seurat::FindVariableFeatures.default(selection.method = "vst")
 #' @export
 #' @examples
@@ -1053,13 +1040,12 @@ selectGenesVST <- function(
         loessSpan = 0.3,
         clipMax = "auto",
         useShared = TRUE,
-        verbose = getOption("ligerVerbose"))
+        verbose = getOption("ligerVerbose", TRUE))
 {
     useDataset <- .checkUseDatasets(object, useDataset)
     useDataset <- .checkArgLen(useDataset, 1)
     if (isTRUE(verbose)) {
-        .log("Selecting top ", n, " HVGs with VST method for dataset: ",
-             useDataset)
+        cli::cli_alert_info("Selecting top {n} HVG{?s} with VST method for dataset: {.val {useDataset}}")
     }
     ld <- dataset(object, useDataset)
     data <- rawData(ld)
@@ -1070,10 +1056,7 @@ selectGenesVST <- function(
         useGenes <- rownames(data)
     }
     if (isTRUE(verbose)) {
-        .log("Totally ", length(useGenes),
-             ifelse(useShared, " shared ", " dataset specific "),
-             "genes to be selected from.",
-             level = 2)
+        cli::cli_alert_info("... Totally {length(useGenes)} {ifelse(useShared, 'shared', 'dataset specific')} genes to be selected from.")
     }
     if (clipMax == "auto") {
         clipMax <- sqrt(ncol(data))
@@ -1202,12 +1185,12 @@ scaleNotCenter.dgCMatrix <- function(
 #' @param chunk Integer. Number of maximum number of cells in each chunk, when
 #' scaling is applied to any HDF5 based dataset. Default \code{1000}.
 #' @param verbose Logical. Whether to show information of the progress. Default
-#' \code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.
+#' \code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.
 scaleNotCenter.ligerDataset <- function(
         object,
         features = NULL,
         chunk = 1000,
-        verbose = getOption("ligerVerbose"),
+        verbose = getOption("ligerVerbose", TRUE),
         ...
 ) {
     features <- .idxCheck(object, features, "feature")
@@ -1238,7 +1221,7 @@ scaleNotCenter.ligerDataset <- function(
 scaleNotCenter.ligerMethDataset <- function(
         object,
         features = NULL,
-        verbose = getOption("ligerVerbose"),
+        verbose = getOption("ligerVerbose", TRUE),
         ...
 ) {
     raw <- rawData(object)
@@ -1262,23 +1245,25 @@ scaleNotCenter.liger <- function(
         object,
         useDatasets = NULL,
         features = varFeatures(object),
-        verbose = getOption("ligerVerbose"),
+        verbose = getOption("ligerVerbose", TRUE),
         remove.missing = NULL,
         ...
 ) {
     .deprecateArgs(defunct = "remove.missing")
     .checkObjVersion(object)
     if (is.null(features) || length(features) == 0) {
-        stop("No variable feature specified. Run `selectGenes()` first")
+        cli::cli_abort("No variable feature specified. Run {.fn selectGenes} first.")
     }
     useDatasets <- .checkUseDatasets(object, useDatasets)
     object <- recordCommand(object, ...,
                             dependencies = c("RcppArmadillo", "Rcpp"))
+
     for (d in useDatasets) {
-        if (isTRUE(verbose)) .log("Scaling dataset: ", d)
+        if (isTRUE(verbose)) cliID <- cli::cli_process_start("Scaling dataset {.val {d}}")
         ld <- dataset(object, d)
         ld <- scaleNotCenter(ld, features = features, verbose = verbose, ...)
         datasets(object, check = FALSE)[[d]] <- ld
+        if (isTRUE(verbose)) cli::cli_process_done(id = cliID)
     }
     return(object)
 }
@@ -1310,7 +1295,7 @@ scaleNotCenter.Seurat <- function(
 
     features <- features %||% SeuratObject::VariableFeatures(object)
     if (!length(features)) {
-        stop("No variable feature specified. Run `selectGenes()` first")
+        cli::cli_abort("No variable feature specified. Run {.fn selectGenes} first")
     }
 
     if (is.list(normed)) {
@@ -1346,10 +1331,9 @@ scaleNotCenter.Seurat <- function(
     geneRootMeanSumSq = sqrt(geneSumSq / (nCells - 1))
     h5file <- getH5File(ld)
     # Count the subset nnz first before creating data space
-    if (isTRUE(verbose)) .log("Counting number of non-zero values...")
     nnz <- 0
     nnz <- H5Apply(
-        ld, useData = "normData", chunkSize = chunk, verbose = verbose,
+        ld, useData = "normData", chunkSize = chunk, verbose = FALSE,
         FUN = function(chunk, sparseXIdx, cellIdx, values) {
             chunk <- chunk[featureIdx, , drop = FALSE]
             values <- values + length(chunk@x)
@@ -1413,7 +1397,7 @@ scaleNotCenter.Seurat <- function(
 #' logical vector of the index of the datasets that should be identified as
 #' methylation data where the reversed data will be created.
 #' @param verbose Logical. Whether to show information of the progress. Default
-#' \code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.
+#' \code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.
 #' @return The input \linkS4class{liger} object, where the \code{scaleData} slot
 #' of the specified datasets will be updated with value as described in
 #' Description.
@@ -1425,16 +1409,15 @@ scaleNotCenter.Seurat <- function(
 #' pbmc <- scaleNotCenter(pbmc, useDatasets = 1)
 #' pbmc <- reverseMethData(pbmc, useDatasets = 2)
 reverseMethData <- function(object, useDatasets,
-                            verbose = getOption("ligerVerbose")) {
+                            verbose = getOption("ligerVerbose", TRUE)) {
     useDatasets <- .checkUseDatasets(object, useDatasets)
     if (is.null(varFeatures(object)) || length(varFeatures(object)) == 0) {
-        stop("Variable genes have to be identified first. ",
-             "Please run `selectGenes(object)`.")
+        cli::cli_abort("No variable feature available. Run {.fn selectGenes} first.")
     }
     for (d in useDatasets) {
         ld <- dataset(object, d)
         raw <- rawData(ld)
-        if (isTRUE(verbose)) .log("Substracting methylation data: ", d)
+        if (isTRUE(verbose)) cli::cli_alert_info("Substracting methylation data: {.val {d}}")
         scaleData(ld, check = FALSE) <- methods::as(
             max(raw) - raw[varFeatures(object), , drop = FALSE],
             "CsparseMatrix"
diff --git a/R/subsetObject.R b/R/subsetObject.R
index 9cafc4f5..ad09cba1 100644
--- a/R/subsetObject.R
+++ b/R/subsetObject.R
@@ -22,7 +22,7 @@
 #' @param chunkSize Integer. Number of maximum number of cells in each chunk,
 #' Default \code{1000}.
 #' @param verbose Logical. Whether to show information of the progress. Default
-#' \code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.
+#' \code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.
 #' @param returnObject Logical, whether to return a \linkS4class{liger} object
 #' for result. Default \code{TRUE}. \code{FALSE} returns a list containing
 #' requested values.
@@ -40,7 +40,7 @@ subsetLiger <- function(
         cellIdx = NULL,
         useSlot = NULL,
         chunkSize = 1000,
-        verbose = getOption("ligerVerbose"),
+        verbose = getOption("ligerVerbose", TRUE),
         newH5 = TRUE,
         returnObject = TRUE,
         ...
@@ -53,7 +53,8 @@ subsetLiger <- function(
         return(object)
     }
     if (!inherits(object, "liger")) {
-        warning("`object` is not a liger obejct. Nothing to be done.")
+        cli::cli_alert_danger("{.var object} is not a {.cls liger} object.")
+        cli::cli_alert_info("Nothing to be done.")
         return(object)
     }
     # Check subscription parameters ####
@@ -65,26 +66,28 @@ subsetLiger <- function(
     # feature idx need different check from ligerDataset's .idxCheck
     if (!is.null(featureIdx)) {
         if (!is.character(featureIdx)) {
-            stop("Feature subscription from liger object can only take ",
-                 "character vector.")
+            cli::cli_abort(
+                "Feature subscription from a {.cls liger} object can only take {.cls character} vector (e.g. gene names)."
+            )
         }
         genesList <- lapply(datasets(object)[useDatasets], rownames)
         allGenes <- unique(unlist(genesList, use.names = FALSE))
         if (!all(featureIdx %in% allGenes)) {
             notFound <- featureIdx[!featureIdx %in% allGenes]
-            warning(length(notFound), " out of ", length(featureIdx),
-                    " given features were not found in the union of all ",
-                    "features of used datasets")
+            cli::cli_alert_warning(
+                c("{length(notFound)} out of {length(featureIdx)} given ",
+                  "features were not found in the union of all features of ",
+                  "used datasets: {.val {notFound}}")
+            )
         }
         featureIdx <- featureIdx[featureIdx %in% allGenes]
-        if (length(featureIdx) == 0)
-            stop("No feature can be retrieved")
+        if (length(featureIdx) == 0) cli::cli_abort("No feature can be retrieved")
     }
     # Subset each involved dataset and create new liger object
 
     datasets.new <- list()
     for (d in useDatasets) {
-        if (isTRUE(verbose)) .log("Subsetting dataset: ",  d)
+        if (isTRUE(verbose)) cli::cli_process_start("Subsetting dataset: {.val {d}}")
         ld <- dataset(object, d)
         featureIdxDataset <- featureIdx
         if (isFALSE(returnObject))
@@ -194,16 +197,19 @@ retrieveCellFeature <- function(
             value <- data.frame(value, row.names = colnames(ld))
             colnames(value) <- feature
             if (!inherits(ld, "ligerATACDataset")) {
-                warning("Dataset ", d, " is not of ATAC modality, returning ",
-                        "NAs for cells belonging to this dataset.",
-                        immediate. = TRUE)
+                cli::cli_alert_warning(
+                    c("Dataset {.val {d}} is not of ATAC modality, returning ",
+                      "NAs for cells belonging to this dataset")
+                )
                 return(value)
             } else {
                 peak <- methods::slot(ld, slot)
                 if (any(!feature %in% rownames(peak))) {
                     nf <- feature[!feature %in% rownames(peak)]
-                    warning("Specified feature not found in dataset ", d,
-                            ", returning NAs.", immediate. = TRUE)
+                    cli::cli_alert_warning(
+                        c("Specified features are not found in dataset ",
+                          "{.val {d}}, returning NAs.")
+                    )
                     feature <- feature[feature %in% rownames(peak)]
                 }
                 value[,feature] <- peak[feature, ]
@@ -247,7 +253,7 @@ retrieveCellFeature <- function(
 #' @param chunkSize Integer. Number of maximum number of cells in each chunk,
 #' Default \code{1000}.
 #' @param verbose Logical. Whether to show information of the progress. Default
-#' \code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.
+#' \code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.
 #' @param returnObject Logical, whether to return a \linkS4class{ligerDataset}
 #' object for result. Default \code{TRUE}. \code{FALSE} returns a list
 #' containing requested values.
@@ -268,7 +274,7 @@ subsetLigerDataset <- function(
         filename = NULL,
         filenameSuffix = NULL,
         chunkSize = 1000,
-        verbose = getOption("ligerVerbose"),
+        verbose = getOption("ligerVerbose", TRUE),
         returnObject = TRUE,
         ...
 ) {
@@ -295,13 +301,15 @@ subsetH5LigerDataset <- function(
         filename = NULL,
         filenameSuffix = NULL,
         chunkSize = 1000,
-        verbose = getOption("ligerVerbose"),
+        verbose = getOption("ligerVerbose", TRUE),
         returnObject = TRUE
 ) {
     if (isTRUE(newH5)) {
         if (isFALSE(returnObject))
-            warning("Cannot set `returnObject = FALSE` when subsetting",
-                    "H5 based ligerDataset to new H5 file.")
+            cli::cli_alert_danger(
+                c("Cannot set {.code returnObject = FALSE} when subsetting H5 based {.cls ligerDataset} to new H5 file.",
+                  "i" = "Will return subset to new object.")
+            )
         if (is.null(filename) && is.null(filenameSuffix)) {
             oldFN <- h5fileInfo(object, "filename")
             bn <- basename(oldFN)
@@ -323,7 +331,10 @@ subsetH5LigerDataset <- function(
                     useSlot = useSlot, chunkSize = chunkSize, verbose = verbose
                 )
             }, error=function(e) {
-                message('An error occurred during subseting from H5 to H5.')
+                cli::cli_alert_danger(
+                    "An error occurred during subseting from H5 to H5."
+                )
+                cli::cli_alert_warning("The new H5 file will be removed.")
                 unlink(filename)
                 stop(e)
             }
@@ -345,14 +356,16 @@ subsetH5LigerDatasetToMem <- function(
         useSlot = NULL,
         returnObject = TRUE,
         chunkSize = 1000,
-        verbose = getOption("ligerVerbose")
+        verbose = getOption("ligerVerbose", TRUE)
 ) {
     if (!inherits(object, "ligerDataset")) {
-        warning("`object` is not a ligerDataset obejct. Nothing to be done.")
+        cli::cli_alert_danger("{.var object} is not a {.cls ligerDataset} object.")
+        cli::cli_alert_info("Nothing to be done.")
         return(object)
     }
     if (!isH5Liger(object)) {
-        warning("`object` is not HDF5 based. Nothing to be done.")
+        cli::cli_alert_info("{.var object} is not HDF5 based.")
+        cli::cli_alert_info("Nothing to be done.")
         return(object)
     }
     modal <- modalOf(object)
@@ -364,7 +377,8 @@ subsetH5LigerDatasetToMem <- function(
     value <- list()
     # Process rawData ####
     if ("rawData" %in% slotInvolved & !is.null(rawData(object))) {
-        if (isTRUE(verbose)) .log("Subsetting `rawData`", level = 2)
+        if (isTRUE(verbose))
+            cli::cli_process_start("... Subsetting {.field rawData}")
         rawData <- H5Apply(
             object, init = NULL, useData = "rawData", chunkSize = chunkSize,
             verbose = verbose,
@@ -376,11 +390,13 @@ subsetH5LigerDatasetToMem <- function(
         rownames(rawData) <- rownames(object)[featureIdx]
         colnames(rawData) <- colnames(object)[cellIdx]
         value$rawData <- rawData
+        if (isTRUE(verbose)) cli::cli_process_done()
     }
 
     # Process normData ####
     if ("normData" %in% slotInvolved & !is.null(normData(object))) {
-        if (isTRUE(verbose)) .log("Subsetting `normData`", level = 2)
+        if (isTRUE(verbose))
+            cli::cli_process_start("... Subsetting {.field normData}")
         normData <- H5Apply(
             object, init = NULL, useData = "normData", chunkSize = chunkSize,
             verbose = verbose,
@@ -392,6 +408,7 @@ subsetH5LigerDatasetToMem <- function(
         rownames(normData) <- rownames(object)[featureIdx]
         colnames(normData) <- colnames(object)[cellIdx]
         value$normData <- normData
+        if (isTRUE(verbose)) cli::cli_process_done()
     }
 
     # Process scaled data ####
@@ -402,7 +419,8 @@ subsetH5LigerDatasetToMem <- function(
         secondIdx <- as.numeric(stats::na.omit(match(featureIdx, scaledFeatureIdx)))
     }
     if ("scaleData" %in% slotInvolved & !is.null(scaleData(object))) {
-        if (isTRUE(verbose)) .log("Subsetting `scaleData`", level = 2)
+        if (isTRUE(verbose))
+            cli::cli_process_start("... Subsetting {.field scaleData}")
         # scaledFeatureIdx <- NULL
         # if (getH5File(object)$exists("scaleData.featureIdx")) {
         #     scaledFeatureIdx <- getH5File(object)[["scaleData.featureIdx"]][]
@@ -463,6 +481,7 @@ subsetH5LigerDatasetToMem <- function(
         #     }
         # }
         value$scaleData <- scaleDataSubset
+        if (isTRUE(verbose)) cli::cli_process_done()
     }
     # `NULL[idx1, idx2]` returns `NULL`
     # V: k x genes
@@ -500,15 +519,17 @@ subsetH5LigerDatasetToH5 <- function(
         filename = NULL,
         filenameSuffix = NULL,
         chunkSize = 1000,
-        verbose = getOption("ligerVerbose")
+        verbose = getOption("ligerVerbose", TRUE)
 ) {
     # Input checks ####
     if (!inherits(object, "ligerDataset")) {
-        warning("`object` is not a ligerDataset obejct. Nothing to be done.")
+        cli::cli_alert_danger("{.var object} is not a {.cls ligerDataset} object.")
+        cli::cli_alert_info("Nothing to be done.")
         return(object)
     }
     if (!isH5Liger(object)) {
-        warning("`object` is not HDF5 based. Nothing to be done.")
+        cli::cli_alert_info("{.var object} is not HDF5 based.")
+        cli::cli_alert_info("Nothing to be done.")
         return(object)
     }
     modal <- modalOf(object)
@@ -522,7 +543,7 @@ subsetH5LigerDatasetToH5 <- function(
     } else {
         newH5File <- hdf5r::H5File$new(filename, mode = "w")
     }
-    if (isTRUE(verbose)) .log("New H5 file at: ", filename)
+    if (isTRUE(verbose)) cli::cli_alert_info("New H5 file at: {.file {filename}}")
     newH5Meta <- h5fileInfo(object)
     newH5Meta$H5File <- newH5File
     newH5Meta$filename <- filename
@@ -532,6 +553,10 @@ subsetH5LigerDatasetToH5 <- function(
         newH5File[[newH5Meta$barcodesName]][1:length(cellIdx)] <-
             colnames(object)[cellIdx]
     } else {
+        cli::cli_abort(
+            c("AnnData (H5AD) format not supported yet.",
+              "i" = "Please submit an issue on GitHub if this is highly desired.")
+        )
         # TODO: AnnData style barcodes storage.
     }
 
@@ -542,7 +567,8 @@ subsetH5LigerDatasetToH5 <- function(
     # Process Raw Data ####
     if ("rawData" %in% useSlot & !is.null(rawData(object))) {
         # 1. Create paths to store i, p, x of sparse matrix
-        if (isTRUE(verbose)) .log("Subsetting `rawData`", level = 2)
+        if (isTRUE(verbose))
+            cli::cli_process_start("... Subsetting {.field rawData}")
         safeH5Create(newH5File, newH5Meta$indicesName, dims = 1,
                      chunkSize = 4096, dtype = "int")
         i.h5d <- newH5File[[newH5Meta$indicesName]]
@@ -590,10 +616,12 @@ subsetH5LigerDatasetToH5 <- function(
                 return(values)
             }
         )
+        if (isTRUE(verbose)) cli::cli_process_done()
     }
     # Process Normalized Data ####
     if ("normData" %in% useSlot & !is.null(normData(object))) {
-        if (isTRUE(verbose)) .log("Subsetting `normData`", level = 2)
+        if (isTRUE(verbose))
+            cli::cli_process_start("... Subsetting {.field normData}")
         safeH5Create(newH5File, newH5Meta$normData, dims = 1,
                      chunkSize = 4096, dtype = "double")
         x.h5d <- newH5File[[newH5Meta$normData]]
@@ -636,6 +664,7 @@ subsetH5LigerDatasetToH5 <- function(
                 return(values)
             }
         )
+        if (isTRUE(verbose)) cli::cli_process_done()
     }
     # Process Scaled Data ####
     secondIdx <- NULL
@@ -663,8 +692,7 @@ subsetH5LigerDatasetToH5 <- function(
     if ("scaleData" %in% useSlot & !is.null(scaleData(object))) {
         scaledFeatureIdxNew <- which(featureIdx %in% scaledFeatureIdx)
         if (isTRUE(verbose))
-            .log(length(secondIdx),
-                 " features used in scaleData were selected. ", level = 3)
+            cli::cli_process_start("... Subsetting {.field scaleData}")
         newH5File$create_group(newH5Meta$scaleData)
         safeH5Create(
             newH5File,
@@ -752,6 +780,12 @@ subsetH5LigerDatasetToH5 <- function(
         #                 "feature selection. Unable to subset from H5.")
         #     }
         # }
+        if (isTRUE(verbose)) {
+            cli::cli_process_done()
+            cli::cli_alert_info(
+                "...... {length(secondIdx)} features used in {.field scaleData} were selected."
+            )
+        }
     }
     newH5File$close()
     if (!"rawData" %in% useSlot) newH5Meta$rawData <- NULL
@@ -788,11 +822,12 @@ subsetH5LigerDatasetToH5 <- function(
 subsetMemLigerDataset <- function(object, featureIdx = NULL, cellIdx = NULL,
                                   useSlot = NULL, returnObject = TRUE) {
     if (!inherits(object, "ligerDataset")) {
-        warning("`object` is not a ligerDataset obejct. Nothing to be done.")
+        cli::cli_alert_danger("{.var object} is not a {.cls ligerDataset} object.")
+        cli::cli_alert_info("Nothing to be done.")
         return(object)
     }
     if (isH5Liger(object)) {
-        stop("`object` is HDF5 based. Use `subsetH5LigerDataset()` instead.")
+        cli::cli_abort("{.var object} is HDF5 based. Use {.fn subsetH5LigerDataset} instead.")
     }
     if (is.null(cellIdx) && is.null(featureIdx)) return(object)
     modal <- modalOf(object)
@@ -858,18 +893,18 @@ subsetMemLigerDataset <- function(object, featureIdx = NULL, cellIdx = NULL,
     else return(subsetData)
 }
 
-.getOrderedSubsetIdx <- function(allNames, subsetNames) {
-    # subsetNames must be real subset, but can be in a different order from
-    # original allNames
-
-    # Label the order of original allNames
-    idx <- seq_along(allNames)
-    names(idx) <- allNames
-    # Subscribe with named vector, so the value (label for original order) get
-    # ordered by subscription
-    subsetIdx <- idx[subsetNames]
-    subsetIdx <- subsetIdx[!is.na(subsetIdx)]
-    names(subsetIdx) <- NULL
-    subsetIdx
-}
+# .getOrderedSubsetIdx <- function(allNames, subsetNames) {
+#     # subsetNames must be real subset, but can be in a different order from
+#     # original allNames
+#
+#     # Label the order of original allNames
+#     idx <- seq_along(allNames)
+#     names(idx) <- allNames
+#     # Subscribe with named vector, so the value (label for original order) get
+#     # ordered by subscription
+#     subsetIdx <- idx[subsetNames]
+#     subsetIdx <- subsetIdx[!is.na(subsetIdx)]
+#     names(subsetIdx) <- NULL
+#     subsetIdx
+# }
 
diff --git a/R/util.R b/R/util.R
index 7eb82c43..1b1457d0 100644
--- a/R/util.R
+++ b/R/util.R
@@ -9,11 +9,15 @@
     message(pref, msg)
 }
 
+cli_or <- function(x) cli::cli_vec(x, list("vec-last" = " or "))
+
 .checkObjVersion <- function(object) {
     if (inherits(object, "liger")) {
         if (!is.newLiger(object))
-            stop("Old version of liger object detected. Please update the ",
-                 "object with command:\nobject <- convertOldLiger(object)")
+            cli::cli_abort(
+                "Old version of liger object is detected. Please run:
+                {.code object <- convertOldLiger(object)}"
+            )
     }
 }
 
@@ -31,7 +35,7 @@
 .checkUseDatasets <- function(object, useDatasets = NULL,
                               modal = NULL) {
     if (!inherits(object, "liger"))
-        stop("A liger object is required.")
+        cli::cli_abort("A liger object is required.")
     if (is.null(useDatasets)) {
         if (is.null(modal)) useDatasets <- names(object)
         else {
@@ -43,35 +47,41 @@
     } else {
         if (is.numeric(useDatasets)) {
             if (max(useDatasets) > length(object)) {
-                stop("Numeric dataset index out of bound. Only ",
-                     length(object), " datasets exist.")
+                cli::cli_abort(
+                    "Numeric dataset index out of bound. Only {length(object)}
+                    dataset{?s} exist.")
             }
             useDatasets <- unique(useDatasets)
             useDatasets <- names(object)[useDatasets]
         } else if (is.logical(useDatasets)) {
             if (length(useDatasets) != length(object)) {
-                stop("Logical dataset subscription does not match the number ",
-                     "of datasets (", length(object), ").")
+                cli::cli_abort(
+                "Logical dataset subscription does not match the number
+                of datasets ({length(object)}).")
             }
             useDatasets <- names(object)[useDatasets]
         } else if (is.character(useDatasets)) {
             if (any(!useDatasets %in% names(object))) {
-                notFound <- useDatasets[!useDatasets %in% names(object)]
-                stop("Specified dataset name(s) not found: ",
-                     paste(notFound, collapse = ", "))
+                cli::cli_abort(
+                    "Specified dataset name(s) not found:
+                    {.val {useDatasets[!useDatasets %in% names(object)]}}"
+                )
             }
         } else {
-            stop("Please use a proper numeric/logical/character vector to ",
-                 "select dataset to use.")
+            cli::cli_abort(
+                "Please use a proper numeric/logical/character vector to
+                 select dataset to use.")
         }
         if (!is.null(modal)) {
             passing <- sapply(useDatasets, function(d) {
                 inherits(dataset(object, d), .modalClassDict[[modal]])
             })
             if (!all(passing))
-                stop("Not all specified datasets are of `",
-                     .modalClassDict[[modal]], "` class: ",
-                     paste(useDatasets[!passing], collapse = ", "))
+                cli::cli_abort(
+                    "Not all specified datasets are of
+                    {(.modalClassDict[[modal]])} class:
+                    {.val {useDatasets[!passing]}}"
+                )
         }
     }
     useDatasets
@@ -88,8 +98,8 @@
         droplevels = TRUE,
         returnList = FALSE
 ) {
-    df <- cellMeta(object, columns = variables, cellIdx = cellIdx, as.data.frame = TRUE,
-                    drop = FALSE)
+    df <- cellMeta(object, columns = variables, cellIdx = cellIdx,
+                   as.data.frame = TRUE, drop = FALSE)
     if (isTRUE(checkCategorical)) {
         passing <- sapply(variables, function(v) {
             vec <- df[[v]]
@@ -97,25 +107,27 @@
             if (is.factor(vec)) return(TRUE)
             if (is.character(vec)) {
                 if (length(unique(vec)) > 50)
-                    warning("Categorical variable selection `", v,
-                            "' has more than 100 unique values.",
-                            immediate. = TRUE)
+                    cli::cli_alert_warning(
+                        "Categorical variable selection `{v}` has more than 50 unique values."
+                    )
                 return(TRUE)
             }
             if (is.numeric(vec)) {
                 if (length(unique(vec)) > 50)
-                    warning("Categorical variable selection `", v,
-                            "` has more than 100 unique values.",
-                            immediate. = TRUE)
+                    cli::cli_alert_warning(
+                        "Categorical variable selection `{v}` has more than 50 unique values."
+                    )
                 return(FALSE)
             }
         })
+        passing <- unlist(passing)
         if (!all(passing)) {
-            notPassed <- variables[!passing]
-            stop("The following selected variables are not considered as ",
-                 "categorical. Please use something else or try converting ",
-                 "them to factor class to force passing checks.\n",
-                 paste(notPassed, collapse = ", "))
+            cli::cli_abort(
+                "The following selected variables are not considered as
+                categorical. Please use something else or try converting
+                them to factor class to force passing checks.
+                {.val {variables[!passing]}}"
+            )
         }
     }
     for (v in colnames(df)) {
@@ -150,7 +162,9 @@
         if (any(!idx %in% getNames(object))) {
             notFound <- paste(idx[!idx %in% getNames(object)],
                               collapse = ", ")
-            stop(paramName, " not found in object: ", notFound)
+            cli::cli_abort(
+                "{paramName} not found in object: {notFound}"
+            )
         }
         name <- seq(getNumber(object))
         names(name) <- getNames(object)
@@ -158,47 +172,47 @@
         names(idx) <- NULL
     } else if (is.logical(idx)) {
         if (length(idx) != getNumber(object)) {
-            stop("Length of logical ", paramName, " does not match to ",
-                 "number of ", orient, "s in `object`.")
+            cli::cli_abort(
+                "Length of logical {paramName} does not match to number of {orient}s in `object`."
+            )
         }
         idx <- which(idx)
     } else if (is.numeric(idx)) {
         if (max(idx) > getNumber(object) || min(idx) < 1) {
-            stop("Numeric ", paramName, " subscription out of bound.")
+            cli::cli_abort(
+                "Numeric {paramName} subscription out of bound."
+            )
         }
     } else if (is.null(idx)) {
         idx <- seq(getNumber(object))
     } else {
-        stop("Please use character, logical or numeric subscription ",
-             "for ", paramName, ".")
+        cli::cli_abort(
+            "Please use character, logical or numeric subscription for {paramName}."
+        )
     }
     return(idx)
 }
 
 .checkLDSlot <- function(object, slot) {
-    if (!inherits(object, "ligerDataset"))
-        stop("Please use a ligerDataset object.")
     avail <- c("rawData", "normData", "scaleData")
     if (is.null(slot)) {
         slot <- avail
     } else {
         if (any(!slot %in% avail)) {
             notFound <- slot[!slot %in% avail]
-            stop("Specified slot not availalble: ",
-                 paste(notFound, collapse = ", "), ". Use one or more from ",
-                 '"rawData", "normData" or "scaleData"')
+            cli::cli_abort(
+                "Specified slot not availalble: {.val {notFound}}.
+                Use one or more from \"rawData\", \"normData\" or \"scaleData\""
+            )
         }
-        if ("rawData" %in% slot &&
-            is.null(rawData(object))) {
-            stop("`rawData` is not available for use.")
+        if ("rawData" %in% slot && is.null(rawData(object))) {
+            cli::cli_abort("`rawData` is not available for use.")
         }
-        if ("normData" %in% slot &&
-            is.null(normData(object))) {
-            stop("`normData` is not available for use.")
+        if ("normData" %in% slot && is.null(normData(object))) {
+            cli::cli_abort("`normData` is not available for use.")
         }
-        if ("scaleData" %in% slot &&
-            is.null(scaleData(object))) {
-            stop("`scaleData` is not available for use.")
+        if ("scaleData" %in% slot && is.null(scaleData(object))) {
+            cli::cli_abort("`scaleData` is not available for use.")
         }
     }
     slot
@@ -215,26 +229,27 @@
     if (type == "V") checklist <- c(1, 1, 1, 0, 0)
     if (checklist[1]) {
         if (!is.list(m))
-            stop("`", type, ".init` should be a list of matrices")
+            cli::cli_abort(
+                "{.var {type}Init} should be a list of {.cls matrix}."
+            )
         if (length(m) != length(nCells))
-            stop("Number of matrices in `", type, ".init` should match number",
-                 " of datasets in `object`")
+            cli::cli_abort(
+                "Number of matrices in {.var {type}Init} should match number of datasets in {.var object}."
+            )
         isMat <- sapply(m, is.matrix)
         if (!all(isMat)) {
-            stop(sum(!isMat), " elements in `", type, ".init` is not a matrix.")
+            cli::cli_abort("{sum(!isMat)} elements in {.var {type}Init} is not {.cls matrix}.")
         }
         isValid <- sapply(seq_along(m), function(i)
             .checkInit.mat(m[[i]], nCells[i], nGenes, k, checklist))
         if (!all(isValid))
-            stop("Not all matrices in `", type,
-                 ".init` has valid dimensionality.")
+            cli::cli_abort("Not all matrices in {.var {type}Init} has valid dimensionality.")
     } else {
         if (!is.matrix(m))
-            stop("`", type, ".init` should be a matrix")
+            cli::cli_abort("{.var {type}Init} should be a {.cls matrix}.")
         if (!.checkInit.mat(m, sum(nCells), nGenes, k, checklist))
-            stop("`", type, ".init` does not have valid dimensionality.")
+            cli::cli_abort("{.var {type}Init} does not have valid dimensionality.")
     }
-    m
 }
 
 .checkInit.mat <- function(m, nCells, nGenes, k, checklist) {
@@ -249,7 +264,7 @@
                                     checkV = TRUE) {
     result <- TRUE
     useDatasets <- .checkUseDatasets(object, useDatasets)
-    if (is.null(object@W)) stop("W matrix does not exist.")
+    if (is.null(object@W)) cli::cli_abort("W matrix does not exist.")
     k <- ncol(object@W)
 
     for (d in useDatasets) {
@@ -257,32 +272,38 @@
         nCells <- ncol(ld)
         if (isTRUE(checkV)) {
             if (is.null(ld@V)) {
-                warning("V matrix does not exist for dataset '", d, "'.")
+                cli::cli_alert_danger("V matrix does not exist for dataset {.val {d}}.")
                 result <- FALSE
             } else {
                 if (!identical(dim(ld@V), dim(object@W))) {
-                    warning("Dimensionality of V matrix for dataset '", d,
-                            "' does not match with W matrix.")
+                    cli::cli_alert_danger(
+                        "Dimensionality of V matrix for dataset {.val {d}} does not match with W matrix."
+                    )
                     result <- FALSE
                 }
             }
         }
         if (is.null(ld@H)) {
-            warning("H matrix does not exist for dataset '", d, "'.")
+            cli::cli_alert_danger("H matrix does not exist for dataset {.val {d}}.")
             result <- FALSE
         } else {
             if (!identical(dim(ld@H), c(k, nCells))) {
-                warning("Dimensionality of H matrix for dataset '", d,
-                        "' is not valid")
+                cli::cli_alert_danger(
+                    "Dimensionality of H matrix for dataset {.val {d}} is not valid."
+                )
                 result <- FALSE
             }
         }
     }
     if (k != object@uns$factorization$k)
-        warning("Number of factors does not match with object `k` slot. ")
+        cli::cli_alert_danger(
+            "Number of factors does not match with recorded parameter."
+        )
     if (isFALSE(result))
-        stop("Cannot detect valid existing factorization result. ",
-             "Please run factorization first. Check warnings.")
+        cli::cli_abort(
+            c(x = "Cannot detect valid existing factorization result. ",
+              i = "Please run factorization first. Check warnings.")
+        )
 }
 
 # !!!MaintainerDeveloperNOTE:
@@ -337,82 +358,107 @@
 .checkRaster <- function(n, raster = NULL) {
     pkgAvail <- requireNamespace("scattermore", quietly = TRUE)
     if (!is.null(raster) && !is.logical(raster)) {
-        stop("Please use `NULL` or logical value for `raster`.")
+        cli::cli_abort("Please use `NULL` or logical value for `raster`.")
     }
     if (is.null(raster)) {
         # Automatically decide whether to rasterize depending on number of cells
         if (n > 1e5) {
             if (pkgAvail) {
                 raster <- TRUE
-                .log("NOTE: Points are rasterized as number of cells/nuclei ",
-                     "plotted exceeds 100,000.\n",
-                     "Use `raster = FALSE` or `raster = TRUE` to force plot ",
-                     "in vector form or not.")
+                cli::cli_alert_info(
+                    "Points are rasterized since number of cells/nuclei exceeds
+                    100,000.
+                    Use {.code raster = FALSE} or {.code raster = TRUE} to force
+                    plot in vectorized form or not."
+                )
             } else {
                 raster <- FALSE
                 warning("Number of cells/nuclei plotted exceeds 100,000. ",
                         "Rasterizing the scatter plot is recommended but ",
-                        "package \"scattermore\" is not available. ")
+                        "package {.pkg scattermore} is not available. ")
             }
         } else {
             raster <- FALSE
         }
     } else if (isTRUE(raster)) {
         if (!pkgAvail) {
-            stop("Package \"scattermore\" needed for rasterizing the scatter ",
-                 "plot. Please install it by command:\n",
-                 "BiocManager::install('scattermore')",
-                 call. = FALSE)
+            cli::cli_abort(
+                "Package {.pkg scattermore} is needed for rasterizing the scatter
+                plot. Please install it by command:
+                {.code BiocManager::install('scattermore')}"
+            )
         }
     }
     return(raster)
 }
 
 .checkArgLen <- function(arg, n, repN = TRUE, class = NULL, .stop = TRUE) {
+    if (is.null(arg)) return(arg)
     argname <- deparse(substitute(arg))
-    if (!is.null(arg)) {
-        if (length(arg) == 1 && isTRUE(repN)) {
-            arg <- rep(arg, n)
-        }
-        if (length(arg) != n) {
-            if (isTRUE(.stop))
-                stop("`", argname, "` has to be a vector of length ", n)
-            else {
-                warning("`", argname, "` has to be a vector of length ", n)
+    if (length(arg) == 1 && isTRUE(repN)) {
+        arg <- rep(arg, n)
+    }
+    if (length(arg) != n) {
+        classTxt <- ifelse(is.null(class), "", " ")
+        if (isTRUE(.stop))
+            if (!is.null(class)) {
+                cli::cli_abort(
+                    c("{.var {argname}} has to be a length {ifelse(repN, paste0('1 or ', n), n)} object of class {.cls {class}}.",
+                      "i" = "length: {length(arg)}; class: {.cls {class(arg)}}")
+                )
+            } else {
+                cli::cli_abort(
+                    c("{.var {argname}} has to be a length {ifelse(repN, paste0('1 or ', n), n)} object.",
+                      "i" = "length: {length(arg)}; class: {.cls {class(arg)}}")
+                )
+            }
+        else {
+            if (!is.null(class)) {
+                cli::cli_alert_warning(
+                    c("{.var {argname}} has to be a length {ifelse(repN, paste0('1 or ', n), n)} object of class {.cls {class}}.",
+                      i = "Using it anyway.")
+                )
+            } else {
+                cli::cli_alert_warning(
+                    c("{.var {argname}} has to be a length {ifelse(repN, paste0('1 or ', n), n)} object.",
+                      i = "Using it anyway.")
+                )
             }
         }
     }
     if (!is.null(class)) {
         allClassCheck <- sapply(class, function(x) methods::is(arg, x))
         if (!any(allClassCheck)) {
+            class <- cli::cli_vec(class, list("vec-quote" ))
             if (isTRUE(.stop))
-                stop("`", argname, "` has to be of class '",
-                     paste(class, collapse = "', '"), "'")
+                cli::cli_abort(
+                    c("{.var {argname}} has to be of class {.cls {class}}",
+                      "i" = "Given class is {.cls {class(arg)}}")
+                )
             else {
-                warning("`", argname, "` has to be of class '",
-                        paste(class, collapse = "', '"), "'")
+                cli::cli_alert_warning(
+                    c("{.var {argname}} has to be of class {.cls {class}}. Using it anyway.")
+                )
             }
         }
     }
     return(arg)
 }
 
-# Format "not found" string. When we need `need` elements from some source
-# `from` format the string of ", " separeted list of not found elements.
-.nfstr <- function(need, from) {
-    nf <- need[!need %in% from]
-    paste(nf, collapse = ", ")
-}
-
-
-
-
 .getSeuratData <- function(object, layer, slot, assay = NULL) {
     if (!requireNamespace("Seurat", quietly = TRUE)) {
-        stop("Seurat package has to be installed in advance.")
+        cli::cli_abort(
+            "Package {.pkg Seurat} is needed for this function to work.
+            Please install it by command:
+            {.code install.packages('Seurat')}"
+        )
     }
     if (!requireNamespace("SeuratObject", quietly = TRUE)) {
-        stop("SeuratObject package has to be installed in advance.")
+        cli::cli_abort(
+            "Package {.pkg SeuratObject} is needed for this function to work.
+            Please install it by command:
+            {.code install.packages('SeuratObject')}"
+        )
     }
     assayObj <- Seurat::GetAssay(object, assay = assay)
     if (!"layers" %in% methods::slotNames(assayObj)) {
@@ -422,7 +468,7 @@
     if (utils::packageVersion("SeuratObject") >= package_version("4.9.9")) {
         layers <- SeuratObject::Layers(object, assay = assay, search = layer)
         if (length(layers) == 0) {
-            stop("Layer '", layer, "' not found in object.")
+            cli::cli_abort("Layer {.val {layer}} not found in object.")
         } else if (length(layers) == 1) {
             data <- SeuratObject::LayerData(object, assay = assay, layer = layers)
         } else {
@@ -431,19 +477,28 @@
             })
             names(data) <- layers
         }
-    } else {
+    } else { # nocov start
+        cli::cli_alert_info("Using old Seurat package. Upgrade is recommended.")
         data <- SeuratObject::GetAssayData(object, assay = assay, slot = layer)
-    }
+    } # nocov end
     return(data)
 }
 
 .setSeuratData <- function(object, layer, save, slot, value, assay = NULL,
                            denseIfNeeded = FALSE) {
     if (!requireNamespace("Seurat", quietly = TRUE)) {
-        stop("Seurat package has to be installed in advance.")
+        cli::cli_abort(
+            "Package {.pkg Seurat} is needed for this function to work.
+            Please install it by command:
+            {.emph install.packages('Seurat')}"
+        )
     }
     if (!requireNamespace("SeuratObject", quietly = TRUE)) {
-        stop("SeuratObject package has to be installed in advance.")
+        cli::cli_abort(
+            "Package {.pkg SeuratObject} is needed for this function to work.
+            Please install it by command:
+            {.emph install.packages('SeuratObject')}"
+        )
     }
     assayObj <- Seurat::GetAssay(object, assay = assay)
     if (!"layers" %in% methods::slotNames(assayObj)) {
@@ -466,42 +521,14 @@
                 SeuratObject::LayerData(object, assay = assay, layer = save[i]) <- value[[layer[i]]]
             }
         }
-    } else {
+    } else { # nocov start
+        cli::cli_alert_info("Using old {.pkg Seurat} package. Upgrade is recommended.")
         object <- SeuratObject::SetAssayData(object, assay = assay,
                                              slot = save, new.data = value)
-    }
+    } # nocov end
     return(object)
 }
 
-# plyr::mapvalues
-mapvalues <- function(x, from, to, warn_missing = TRUE) {
-    if (length(from) != length(to)) {
-        stop("`from` and `to` vectors are not the same length.")
-    }
-    if (!is.atomic(x) && !is.null(x)) {
-        stop("`x` must be an atomic vector or NULL.")
-    }
-
-    if (is.factor(x)) {
-        # If x is a factor, call self but operate on the levels
-        levels(x) <- mapvalues(levels(x), from, to, warn_missing)
-        return(x)
-    }
-
-    mapidx <- match(x, from)
-    mapidxNA  <- is.na(mapidx)
-
-    # index of items in `from` that were found in `x`
-    from_found <- sort(unique(mapidx))
-    if (warn_missing && length(from_found) != length(from)) {
-        message("The following `from` values were not present in `x`: ",
-                paste(from[!(1:length(from) %in% from_found) ], collapse = ", "))
-    }
-
-    x[!mapidxNA] <- to[mapidx[!mapidxNA]]
-    x
-}
-
 .DataFrame.as.data.frame <- function(x)
 {
     # Copied from Bioconductor package S4Vectors:::.as.data.frame.DataFrame
@@ -554,8 +581,10 @@ searchH <- function(object, useRaw = NULL) {
             # If not found, look for raw H
             Ht <- Reduce(cbind, getMatrix(object, "H"))
             if (is.null(Ht)) {
-                stop("No cell factor loading available. ",
-                     "Please run `runIntegration()` and `quantileNorm()` first.")
+                cli::cli_abort(
+                    "No cell factor loading available.
+                    Please run {.fn runIntegration} and {.fn quantileNorm} first."
+                )
             } else {
                 useRaw <- TRUE
                 H <- t(Ht)
@@ -567,17 +596,21 @@ searchH <- function(object, useRaw = NULL) {
         if (isTRUE(useRaw)) {
             Ht <- Reduce(cbind, getMatrix(object, "H"))
             if (is.null(Ht)) {
-                stop("Raw cell factor loading requested but not found. ",
-                     "Please run `runIntegration()`.")
+                cli::cli_abort(
+                    "Raw cell factor loading requested but not found.
+                    Please run {.fn runIntegration}."
+                )
             } else {
                 H <- t(Ht)
             }
         } else {
             H <- getMatrix(object, "H.norm")
             if (is.null(H)) {
-                stop("Quantile-normalized cell factor loading requested but ",
-                     "not found. Please run `quantileNorm()` after ",
-                     "`runIntegration()`.")
+                cli::cli_abort(
+                    "Quantile-normalized cell factor loading requested but
+                    not found. Please run {.fn quantileNorm} after
+                    {.fn runIntegration}."
+                )
             }
             useRaw <- FALSE
         }
diff --git a/R/visualization.R b/R/visualization.R
index ecd8cdc8..37eb8e2c 100644
--- a/R/visualization.R
+++ b/R/visualization.R
@@ -50,7 +50,10 @@ plotClusterDimRed <- function(
         ...) {
     useDimRed <- useDimRed %||% object@uns$defaultDimRed
     if (is.null(useDimRed)) {
-        stop("No `useDimRed` given or default dimRed not set.")
+        cli::cli_abort(
+            c(x = "No {.var useDimRed} given or default dimRed not set.",
+              i = "Run {.fn runUMAP} or {.fn runTSNE} to create one. Or see {.fn dimRed} and {.fn defaultDimRed}.")
+        )
     }
     useCluster <- useCluster %||% object@uns$defaultCluster
     xVar <- paste0(useDimRed, ".1")
@@ -68,7 +71,10 @@ plotDatasetDimRed <- function(
         ...) {
     useDimRed <- useDimRed %||% object@uns$defaultDimRed
     if (is.null(useDimRed)) {
-        stop("No `useDimRed` given or default dimRed not set.")
+        cli::cli_abort(
+            c(x = "No {.var useDimRed} given or default dimRed not set.",
+              i = "Run {.fn runUMAP} or {.fn runTSNE} to create one. Or see {.fn dimRed} and {.fn defaultDimRed}.")
+        )
     }
     xVar <- paste0(useDimRed, ".1")
     yVar <- paste0(useDimRed, ".2")
@@ -433,8 +439,9 @@ plotProportionDot <- function(
     class1 <- class1 %||% object@uns$defaultCluster
     if (length(class1) != 1 ||
         length(class2) != 1)
-        stop("`class1` and `class2` must be name of one categorical variable ",
-             "in `cellMeta` slot.")
+        cli::cli_abort(
+            "{.var class1} and {.var class2} must be name of one categorical variable in {.code cellMeta(object)}"
+        )
     vars <- .fetchCellMetaVar(object, c(class1, class2),
                               checkCategorical = TRUE)
     freq <- table(vars)
@@ -471,8 +478,7 @@ plotProportionBar <- function(
     class1 <- class1 %||% object@uns$defaultCluster
     if (length(class1) != 1 ||
         length(class2) != 1)
-        stop("`class1` and `class2` must be name of one categorical variable ",
-             "in `cellMeta` slot.")
+        cli::cli_abort("{.var class1} and {.var class2} must be name of one categorical variable in {.code cellMeta(object)}")
     method <- match.arg(method)
     vars <- .fetchCellMetaVar(object, c(class1, class2),
                               checkCategorical = TRUE)
@@ -622,6 +628,9 @@ plotProportionPie <- function(
 #' passed to \code{\link[EnhancedVolcano]{EnhancedVolcano}}.
 #' @return ggplot
 #' @export
+#' @examples
+#' result <- runMarkerDEG(pbmcPlot)
+#' plotVolcano(result, 1)
 plotVolcano <- function(
         result,
         group,
@@ -635,7 +644,10 @@ plotVolcano <- function(
         ...
 ) {
     if (!group %in% result$group) {
-        stop("Selected group does not exist in `result`.")
+        cli::cli_abort(
+            c("Selected group does not exist in {.code result$group}",
+              i = "Available ones: {.val {levels(droplevels(result$group))}}")
+        )
     }
     result <- result[result$group == group, ]
     result <- result[order(abs(result$logFC), decreasing = TRUE), ]
@@ -705,12 +717,12 @@ plotEnhancedVolcano <- function(
         group,
         ...
 ) {
-    if (!requireNamespace("EnhancedVolcano", quietly = TRUE)) {
-        stop("Package \"EnhancedVolcano\" needed for this function to work. ",
-             "Please install it by command:\n",
-             "BiocManager::install('EnhancedVolcano')",
-             call. = FALSE)
-    }
+    if (!requireNamespace("EnhancedVolcano", quietly = TRUE)) { # nocov start
+        cli::cli_abort(
+            "Package {.pkg EnhancedVolcano} is needed for this function to work.
+            Please install it by command:
+            {.code BiocManager::install('EnhancedVolcano')}")
+    } # nocov end
     result <- result[result$group == group, ]
     EnhancedVolcano::EnhancedVolcano(
         toptable = result,
@@ -805,14 +817,12 @@ plotDensityDimRed <- function(
     } else {
         # Will return a single ggplot
         if (length(title) > 1) {
-            warning("`title` has length greater than 1 while only a single ",
-                    "plot is generated. Using the first value only. ")
+            cli::cli_alert_warning("{.var title} has length greater than 1 while only a single plot is generated. Using the first value only.")
             title <- title[1]
         }
         drList <- list(dr)
     }
     plotList <- list()
-    #if (length(drList) == 0) stop("No plot could be generated")
     if (length(drList) == 1) {
         return(.ggDensity(drList[[1]], dotCoordDF = drList[[1]],
                           title = title, minDensity = minDensity,
@@ -1110,11 +1120,11 @@ plotSankey <- function(
         colorValues = scPalette,
         mar = c(2, 2, 4, 2)
 ) {
-    if (!requireNamespace("sankey", quietly = TRUE))
-        stop("Package \"sankey\" needed for this function to work. ",
-             "Please install it by command:\n",
-             "install.packages('sankey')",
-             call. = FALSE)
+    if (!requireNamespace("sankey", quietly = TRUE)) # nocov start
+        cli::cli_abort(
+            "Package {.pkg sankey} is needed for this function to work.
+            Please install it by command:
+            {.code install.packages('sankey')}") # nocov end
 
     clusterConsensus <- clusterConsensus %||% object@uns$defaultCluster
     clusterDF <- .fetchCellMetaVar(object,
@@ -1122,7 +1132,7 @@ plotSankey <- function(
                                    checkCategorical = TRUE, droplevels = TRUE)
 
     titles <- titles %||% c(cluster1, clusterConsensus, cluster2)
-    titles <- .checkArgLen(titles, 3, repN = FALSE)
+    titles <- .checkArgLen(titles, 3, repN = FALSE, class = "character")
     # Prepare for networkD3 input: Links, Nodes
     cluster1Fct <- droplevels(clusterDF[[1]])
     clusterCFct <- droplevels(clusterDF[[2]])
@@ -1139,7 +1149,7 @@ plotSankey <- function(
 
     if (any(duplicated(c(nodes1, nodesC, nodes2)))) {
         prefixes <- prefixes %||% c(cluster1, clusterConsensus, cluster2)
-        prefixes <- .checkArgLen(prefixes, 3, repN = FALSE)
+        prefixes <- .checkArgLen(prefixes, 3, repN = FALSE, class = "character")
         nodes1 <- .addPrefix(prefixes[1], nodes1)
         nodesC <- .addPrefix(prefixes[2], nodesC)
         nodes2 <- .addPrefix(prefixes[3], nodes2)
@@ -1240,7 +1250,7 @@ plotSpatial2D.liger <- function(
         ...) {
     dataset <- .checkUseDatasets(object, useDatasets = dataset,
                                  modal = "spatial")
-    .checkArgLen(dataset, 1)
+    .checkArgLen(dataset, 1, class = "character")
     ld <- dataset(object, dataset)
     useCluster <- useCluster %||%
         defaultCluster(object)[object$dataset == dataset]
@@ -1248,7 +1258,7 @@ plotSpatial2D.liger <- function(
         legendColorTitle <- legendColorTitle %||% useCluster
         useCluster <- cellMeta(object, useCluster, useDatasets = dataset)
     } else {
-        useCluster <- .checkArgLen(useCluster, ncol(ld), repN = FALSE)
+        useCluster <- .checkArgLen(useCluster, ncol(ld), repN = FALSE, class = "factor")
         legendColorTitle <- legendColorTitle %||% "Annotation"
     }
     plotSpatial2D.ligerSpatialDataset(
@@ -1275,11 +1285,11 @@ plotSpatial2D.ligerSpatialDataset <- function(
         labelText = FALSE,
         ...)
 {
-    .checkArgLen(useCluster, ncol(object))
+    .checkArgLen(useCluster, ncol(object), repN = FALSE, class = "factor")
     legendColorTitle <- legendColorTitle %||% "Annotation"
 
     coord <- coordinate(object)
-    .checkArgLen(useDims, 2)
+    .checkArgLen(useDims, 2, repN = FALSE, class = "numeric")
     coord <- coord[, useDims]
     plotDF <- as.data.frame(coord)
     colnames(plotDF) <- c("x", "y")
diff --git a/cleanup.ucrt b/cleanup.ucrt
deleted file mode 100644
index 1b46a16b..00000000
--- a/cleanup.ucrt
+++ /dev/null
@@ -1,4 +0,0 @@
-#!/bin/sh
-
-rm -f src/*.o src/*.dll src/symbols.rds src/Makefile src/*.cmake src/CMakeCache.txt
-rm -rf src/CMakefiles src/CPM_modules
diff --git a/man/as.liger.Rd b/man/as.liger.Rd
index 4a88ee72..2e0f991d 100644
--- a/man/as.liger.Rd
+++ b/man/as.liger.Rd
@@ -1,15 +1,13 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/classConversion.R
-\name{as.liger}
-\alias{as.liger}
+% Please edit documentation in R/classConversion.R, R/generics.R
+\name{as.liger.dgCMatrix}
 \alias{as.liger.dgCMatrix}
 \alias{as.liger.SingleCellExperiment}
 \alias{as.liger.Seurat}
 \alias{seuratToLiger}
+\alias{as.liger}
 \title{Converting other classes of data to a liger object}
 \usage{
-as.liger(object, ...)
-
 \method{as.liger}{dgCMatrix}(object, datasetVar = NULL, modal = NULL, ...)
 
 \method{as.liger}{SingleCellExperiment}(object, datasetVar = NULL, modal = NULL, ...)
@@ -17,12 +15,12 @@ as.liger(object, ...)
 \method{as.liger}{Seurat}(object, datasetVar = NULL, modal = NULL, assay = NULL, ...)
 
 seuratToLiger(object, datasetVar = NULL, modal = NULL, assay = NULL, ...)
+
+as.liger(object, ...)
 }
 \arguments{
 \item{object}{Object.}
 
-\item{...}{Additional arguments passed to \code{\link{createLiger}}}
-
 \item{datasetVar}{Specify the dataset belonging by: 1. Select a variable from
 existing metadata in the object (e.g. colData column); 2. Specify a
 vector/factor that assign the dataset belonging. 3. Give a single character
@@ -34,6 +32,8 @@ to find variable "sample" from SCE or "orig.ident" from Seurat.}
 \item{modal}{Modality setting for each dataset. See
 \code{\link{createLiger}}.}
 
+\item{...}{Additional arguments passed to \code{\link{createLiger}}}
+
 \item{assay}{Name of assay to use. Default \code{NULL} uses current active
 assay.}
 }
@@ -64,6 +64,7 @@ multiSampleMatrix <- mergeSparseAll(matList)
 pbmc2 <- as.liger(multiSampleMatrix, datasetVar = pbmc$dataset)
 pbmc2
 
+\donttest{
 sce <- SingleCellExperiment::SingleCellExperiment(
     assays = list(counts = multiSampleMatrix)
 )
@@ -86,3 +87,4 @@ seu5[["RNA"]] <- split(seu5[["RNA"]], pbmc$dataset)
 print(SeuratObject::Layers(seu5))
 pbmc5 <- as.liger(seu5)
 }
+}
diff --git a/man/as.ligerDataset.Rd b/man/as.ligerDataset.Rd
index 5115e4a5..001a1065 100644
--- a/man/as.ligerDataset.Rd
+++ b/man/as.ligerDataset.Rd
@@ -1,16 +1,14 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/classConversion.R
-\name{as.ligerDataset}
-\alias{as.ligerDataset}
+% Please edit documentation in R/classConversion.R, R/generics.R
+\name{as.ligerDataset.ligerDataset}
 \alias{as.ligerDataset.ligerDataset}
 \alias{as.ligerDataset.default}
 \alias{as.ligerDataset.matrix}
 \alias{as.ligerDataset.Seurat}
 \alias{as.ligerDataset.SingleCellExperiment}
+\alias{as.ligerDataset}
 \title{Converting other classes of data to a as.ligerDataset object}
 \usage{
-as.ligerDataset(object, ...)
-
 \method{as.ligerDataset}{ligerDataset}(
   object,
   modal = c("default", "rna", "atac", "spatial", "meth"),
@@ -41,15 +39,17 @@ as.ligerDataset(object, ...)
   modal = c("default", "rna", "atac", "spatial", "meth"),
   ...
 )
+
+as.ligerDataset(object, ...)
 }
 \arguments{
 \item{object}{Object.}
 
-\item{...}{Additional arguments passed to \code{\link{createLigerDataset}}}
-
 \item{modal}{Modality setting for each dataset. Choose from \code{"default"},
 \code{"rna"}, \code{"atac"}, \code{"spatial"}, \code{"meth"}.}
 
+\item{...}{Additional arguments passed to \code{\link{createLigerDataset}}}
+
 \item{assay}{Name of assay to use. Default \code{NULL} uses current active
 assay.}
 }
diff --git a/man/commandDiff.Rd b/man/commandDiff.Rd
index a600d46d..ce32172d 100644
--- a/man/commandDiff.Rd
+++ b/man/commandDiff.Rd
@@ -1,5 +1,5 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ligerCommand-class.R
+% Please edit documentation in R/ligerCommand_relates.R
 \name{commandDiff}
 \alias{commandDiff}
 \title{Check difference of two liger command}
diff --git a/man/coordinate.Rd b/man/coordinate.Rd
index 764f8973..95b6f6dd 100644
--- a/man/coordinate.Rd
+++ b/man/coordinate.Rd
@@ -1,5 +1,6 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ligerDataset_subclasses.R
+% Please edit documentation in R/generics.R, R/liger-methods.R,
+%   R/ligerDataset_subclass-methods.R
 \name{coordinate}
 \alias{coordinate}
 \alias{coordinate<-}
diff --git a/man/isH5Liger.Rd b/man/isH5Liger.Rd
index 56250ca8..1d65bba1 100644
--- a/man/isH5Liger.Rd
+++ b/man/isH5Liger.Rd
@@ -1,5 +1,5 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ligerDataset-class.R
+% Please edit documentation in R/ligerDataset-methods.R
 \name{isH5Liger}
 \alias{isH5Liger}
 \title{Check if a liger or ligerDataset object is made of HDF5 file}
diff --git a/man/liger-class.Rd b/man/liger-class.Rd
index 8b9b72a6..bbe04b52 100644
--- a/man/liger-class.Rd
+++ b/man/liger-class.Rd
@@ -1,24 +1,34 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/liger-class.R, R/ligerCommand-class.R,
-%   R/ligerDataset-class.R
+% Please edit documentation in R/classes.R, R/generics.R, R/liger-methods.R,
+%   R/ligerDataset-methods.R
 \docType{class}
 \name{liger-class}
 \alias{liger-class}
 \alias{liger}
+\alias{datasets}
+\alias{datasets<-}
+\alias{dataset}
+\alias{dataset<-}
+\alias{cellMeta}
+\alias{cellMeta<-}
+\alias{defaultCluster}
+\alias{defaultCluster<-}
+\alias{dimRed}
+\alias{dimRed<-}
+\alias{defaultDimRed}
+\alias{defaultDimRed<-}
+\alias{varFeatures}
+\alias{varFeatures<-}
+\alias{varUnsharedFeatures}
+\alias{varUnsharedFeatures<-}
+\alias{commands}
 \alias{show,liger-method}
 \alias{dim,liger-method}
 \alias{dimnames,liger-method}
 \alias{dimnames<-,liger,list-method}
-\alias{[,liger,character,missing,ANY-method}
-\alias{[,liger,missing,index,ANY-method}
-\alias{[,liger,character,index,ANY-method}
-\alias{datasets}
-\alias{datasets<-}
 \alias{datasets,liger-method}
 \alias{datasets<-,liger,logical-method}
 \alias{datasets<-,liger,missing-method}
-\alias{dataset}
-\alias{dataset<-}
 \alias{dataset,liger,character_OR_NULL-method}
 \alias{dataset,liger,missing-method}
 \alias{dataset,liger,numeric-method}
@@ -28,81 +38,106 @@
 \alias{names,liger-method}
 \alias{names<-,liger,character-method}
 \alias{length,liger-method}
-\alias{cellMeta}
-\alias{cellMeta<-}
 \alias{cellMeta,liger,NULL-method}
 \alias{cellMeta,liger,character-method}
 \alias{cellMeta,liger,missing-method}
 \alias{cellMeta<-,liger,missing-method}
 \alias{cellMeta<-,liger,character-method}
+\alias{rawData,liger-method}
+\alias{rawData<-,liger,ANY,ANY,matrixLike_OR_NULL-method}
+\alias{rawData<-,liger,ANY,ANY,H5D-method}
+\alias{normData,liger-method}
+\alias{normData<-,liger,ANY,ANY,matrixLike_OR_NULL-method}
+\alias{normData<-,liger,ANY,ANY,H5D-method}
+\alias{scaleData,liger,ANY-method}
+\alias{scaleData<-,liger,ANY,ANY,matrixLike_OR_NULL-method}
+\alias{scaleData<-,liger,ANY,ANY,H5D-method}
+\alias{scaleData<-,liger,ANY,ANY,H5Group-method}
+\alias{scaleUnsharedData,liger,character-method}
+\alias{scaleUnsharedData,liger,numeric-method}
+\alias{scaleUnsharedData<-,liger,ANY,ANY,matrixLike_OR_NULL-method}
+\alias{scaleUnsharedData<-,liger,ANY,ANY,H5D-method}
+\alias{scaleUnsharedData<-,liger,ANY,ANY,H5Group-method}
+\alias{getMatrix,liger,ANY,ANY,ANY-method}
+\alias{getH5File,liger,ANY-method}
 \alias{$,liger-method}
 \alias{$<-,liger-method}
-\alias{defaultCluster}
-\alias{defaultCluster<-}
 \alias{defaultCluster,liger-method}
 \alias{defaultCluster<-,liger,ANY,ANY,character-method}
 \alias{defaultCluster<-,liger,ANY,ANY,factor-method}
 \alias{defaultCluster<-,liger,ANY,ANY,NULL-method}
-\alias{dimRed}
-\alias{dimRed<-}
 \alias{dimRed,liger,missing-method}
 \alias{dimRed,liger,character-method}
 \alias{dimRed<-,liger,character,ANY,matrixLike-method}
-\alias{defaultDimRed}
-\alias{defaultDimRed<-}
 \alias{defaultDimRed,liger-method}
 \alias{defaultDimRed<-,liger,missing,ANY,character-method}
 \alias{defaultDimRed<-,liger,character,ANY,matrixLike-method}
-\alias{varFeatures}
-\alias{varFeatures<-}
 \alias{varFeatures,liger-method}
 \alias{varFeatures<-,liger,ANY,character-method}
-\alias{varUnsharedFeatures}
-\alias{varUnsharedFeatures<-}
 \alias{varUnsharedFeatures,liger,ANY-method}
-\alias{varUnsharedFeatures,ligerDataset,missing-method}
 \alias{varUnsharedFeatures<-,liger,ANY,ANY,character-method}
-\alias{varUnsharedFeatures<-,ligerDataset,missing,ANY,character-method}
 \alias{fortify.liger}
 \alias{c.liger}
-\alias{commands}
 \alias{commands,liger-method}
-\alias{rawData,liger-method}
-\alias{rawData<-,liger,ANY,ANY,matrixLike_OR_NULL-method}
-\alias{rawData<-,liger,ANY,ANY,H5D-method}
-\alias{normData,liger-method}
-\alias{normData<-,liger,ANY,ANY,matrixLike_OR_NULL-method}
-\alias{normData<-,liger,ANY,ANY,H5D-method}
-\alias{scaleData,liger,ANY-method}
-\alias{scaleData<-,liger,ANY,ANY,matrixLike_OR_NULL-method}
-\alias{scaleData<-,liger,ANY,ANY,H5D-method}
-\alias{scaleData<-,liger,ANY,ANY,H5Group-method}
-\alias{scaleUnsharedData,liger,character-method}
-\alias{scaleUnsharedData,liger,numeric-method}
-\alias{scaleUnsharedData<-,liger,ANY,ANY,matrixLike_OR_NULL-method}
-\alias{scaleUnsharedData<-,liger,ANY,ANY,H5D-method}
-\alias{scaleUnsharedData<-,liger,ANY,ANY,H5Group-method}
-\alias{getMatrix,liger,ANY,ANY,ANY-method}
-\alias{getH5File,liger,ANY-method}
+\alias{varUnsharedFeatures,ligerDataset,missing-method}
+\alias{varUnsharedFeatures<-,ligerDataset,missing,ANY,character-method}
 \title{liger class}
 \usage{
-\S4method{show}{liger}(object)
+datasets(x, check = NULL)
 
-\S4method{dim}{liger}(x)
+datasets(x, check = TRUE) <- value
 
-\S4method{dimnames}{liger}(x)
+dataset(x, dataset = NULL)
 
-\S4method{dimnames}{liger,list}(x) <- value
+dataset(x, dataset, type = NULL, qc = TRUE) <- value
+
+cellMeta(
+  x,
+  columns = NULL,
+  useDatasets = NULL,
+  cellIdx = NULL,
+  as.data.frame = FALSE,
+  ...
+)
 
-\S4method{[}{liger,character,missing,ANY}(x, i, j, ..., drop = TRUE)
+cellMeta(
+  x,
+  columns = NULL,
+  useDatasets = NULL,
+  cellIdx = NULL,
+  inplace = FALSE,
+  check = FALSE
+) <- value
 
-\S4method{[}{liger,missing,index,ANY}(x, i, j, ..., drop = TRUE)
+defaultCluster(x, useDatasets = NULL, ...)
 
-\S4method{[}{liger,character,index,ANY}(x, i, j, ..., drop = TRUE)
+defaultCluster(x, name = NULL, useDatasets = NULL, ...) <- value
 
-datasets(x, check = NULL)
+dimRed(x, name = NULL, useDatasets = NULL, ...)
 
-datasets(x, check = TRUE) <- value
+dimRed(x, name = NULL, useDatasets = NULL, ...) <- value
+
+defaultDimRed(x, useDatasets = NULL)
+
+defaultDimRed(x, name, useDatasets = NULL) <- value
+
+varFeatures(x)
+
+varFeatures(x, check = TRUE) <- value
+
+varUnsharedFeatures(x, dataset = NULL)
+
+varUnsharedFeatures(x, dataset, check = TRUE) <- value
+
+commands(x, funcName = NULL, arg = NULL)
+
+\S4method{show}{liger}(object)
+
+\S4method{dim}{liger}(x)
+
+\S4method{dimnames}{liger}(x)
+
+\S4method{dimnames}{liger,list}(x) <- value
 
 \S4method{datasets}{liger}(x, check = NULL)
 
@@ -110,10 +145,6 @@ datasets(x, check = TRUE) <- value
 
 \S4method{datasets}{liger,missing}(x, check = TRUE) <- value
 
-dataset(x, dataset = NULL)
-
-dataset(x, dataset, type = NULL, qc = TRUE) <- value
-
 \S4method{dataset}{liger,character_OR_NULL}(x, dataset = NULL)
 
 \S4method{dataset}{liger,missing}(x, dataset = NULL)
@@ -132,17 +163,6 @@ dataset(x, dataset, type = NULL, qc = TRUE) <- value
 
 \S4method{length}{liger}(x)
 
-cellMeta(
-  x,
-  columns = NULL,
-  useDatasets = NULL,
-  cellIdx = NULL,
-  as.data.frame = FALSE,
-  ...
-)
-
-cellMeta(x, columns = NULL, useDatasets = NULL, cellIdx = NULL, check = FALSE) <- value
-
 \S4method{cellMeta}{liger,NULL}(
   x,
   columns = NULL,
@@ -172,71 +192,14 @@ cellMeta(x, columns = NULL, useDatasets = NULL, cellIdx = NULL, check = FALSE) <
 
 \S4method{cellMeta}{liger,missing}(x, columns = NULL, useDatasets = NULL, cellIdx = NULL, check = FALSE) <- value
 
-\S4method{cellMeta}{liger,character}(x, columns = NULL, useDatasets = NULL, cellIdx = NULL, check = FALSE) <- value
-
-\S4method{$}{liger}(x, name)
-
-\S4method{$}{liger}(x, name) <- value
-
-defaultCluster(x, useDatasets = NULL, ...)
-
-defaultCluster(x, name = NULL, useDatasets = NULL, ...) <- value
-
-\S4method{defaultCluster}{liger}(x, useDatasets = NULL, droplevels = FALSE, ...)
-
-\S4method{defaultCluster}{liger,ANY,ANY,character}(x, name = NULL, useDatasets = NULL, ...) <- value
-
-\S4method{defaultCluster}{liger,ANY,ANY,factor}(x, name = NULL, useDatasets = NULL, droplevels = TRUE, ...) <- value
-
-\S4method{defaultCluster}{liger,ANY,ANY,NULL}(x, name = NULL, useDatasets = NULL, ...) <- value
-
-dimRed(x, name = NULL, useDatasets = NULL, ...)
-
-dimRed(x, name = NULL, useDatasets = NULL, ...) <- value
-
-\S4method{dimRed}{liger,missing}(x, name = NULL, useDatasets = NULL, ...)
-
-\S4method{dimRed}{liger,character}(x, name = NULL, useDatasets = NULL, ...)
-
-\S4method{dimRed}{liger,character,ANY,matrixLike}(x, name = NULL, useDatasets = NULL, asDefault = NULL, ...) <- value
-
-defaultDimRed(x, useDatasets = NULL)
-
-defaultDimRed(x, name, useDatasets = NULL) <- value
-
-\S4method{defaultDimRed}{liger}(x, useDatasets = NULL)
-
-\S4method{defaultDimRed}{liger,missing,ANY,character}(x, name = NULL, useDatasets = NULL) <- value
-
-\S4method{defaultDimRed}{liger,character,ANY,matrixLike}(x, name, useDatasets = NULL) <- value
-
-varFeatures(x)
-
-varFeatures(x, check = TRUE) <- value
-
-\S4method{varFeatures}{liger}(x)
-
-\S4method{varFeatures}{liger,ANY,character}(x, check = TRUE) <- value
-
-varUnsharedFeatures(x, dataset = NULL)
-
-varUnsharedFeatures(x, dataset, check = TRUE) <- value
-
-\S4method{varUnsharedFeatures}{liger,ANY}(x, dataset = NULL)
-
-\S4method{varUnsharedFeatures}{ligerDataset,missing}(x, dataset = NULL)
-
-\S4method{varUnsharedFeatures}{liger,ANY,ANY,character}(x, dataset, check = TRUE) <- value
-
-\S4method{varUnsharedFeatures}{ligerDataset,missing,ANY,character}(x, dataset = NULL, check = TRUE) <- value
-
-\method{fortify}{liger}(model, data, ...)
-
-\method{c}{liger}(...)
-
-commands(x, funcName = NULL, arg = NULL)
-
-\S4method{commands}{liger}(x, funcName = NULL, arg = NULL)
+\S4method{cellMeta}{liger,character}(
+  x,
+  columns = NULL,
+  useDatasets = NULL,
+  cellIdx = NULL,
+  inplace = TRUE,
+  check = FALSE
+) <- value
 
 \S4method{rawData}{liger}(x, dataset = NULL)
 
@@ -277,23 +240,57 @@ commands(x, funcName = NULL, arg = NULL)
 )
 
 \S4method{getH5File}{liger,ANY}(x, dataset = NULL)
-}
-\arguments{
-\item{x, object, model}{A \linkS4class{liger} object}
 
-\item{value}{Check detail sections for requirements.}
+\S4method{$}{liger}(x, name)
 
-\item{i, j}{Feature and cell index for \code{`[`} method. For \code{`[[`}
-method, use a single variable name with \code{i} while \code{j} is not
-applicable.}
+\S4method{$}{liger}(x, name) <- value
 
-\item{...}{See detailed sections for explanation.}
+\S4method{defaultCluster}{liger}(x, useDatasets = NULL, droplevels = FALSE, ...)
 
-\item{drop}{Not applicable.}
+\S4method{defaultCluster}{liger,ANY,ANY,character}(x, name = NULL, useDatasets = NULL, ...) <- value
+
+\S4method{defaultCluster}{liger,ANY,ANY,factor}(x, name = NULL, useDatasets = NULL, droplevels = TRUE, ...) <- value
+
+\S4method{defaultCluster}{liger,ANY,ANY,NULL}(x, name = NULL, useDatasets = NULL, ...) <- value
+
+\S4method{dimRed}{liger,missing}(x, name = NULL, useDatasets = NULL, ...)
+
+\S4method{dimRed}{liger,character}(x, name = NULL, useDatasets = NULL, ...)
+
+\S4method{dimRed}{liger,character,ANY,matrixLike}(x, name = NULL, useDatasets = NULL, asDefault = NULL, ...) <- value
+
+\S4method{defaultDimRed}{liger}(x, useDatasets = NULL)
+
+\S4method{defaultDimRed}{liger,missing,ANY,character}(x, name = NULL, useDatasets = NULL) <- value
+
+\S4method{defaultDimRed}{liger,character,ANY,matrixLike}(x, name, useDatasets = NULL) <- value
+
+\S4method{varFeatures}{liger}(x)
+
+\S4method{varFeatures}{liger,ANY,character}(x, check = TRUE) <- value
+
+\S4method{varUnsharedFeatures}{liger,ANY}(x, dataset = NULL)
+
+\S4method{varUnsharedFeatures}{liger,ANY,ANY,character}(x, dataset, check = TRUE) <- value
+
+\method{fortify}{liger}(model, data, ...)
+
+\method{c}{liger}(...)
+
+\S4method{commands}{liger}(x, funcName = NULL, arg = NULL)
+
+\S4method{varUnsharedFeatures}{ligerDataset,missing}(x, dataset = NULL)
+
+\S4method{varUnsharedFeatures}{ligerDataset,missing,ANY,character}(x, dataset = NULL, check = TRUE) <- value
+}
+\arguments{
+\item{x, object, model}{A \linkS4class{liger} object}
 
 \item{check}{Logical, whether to perform object validity check on setting new
 value. Users are not supposed to set \code{FALSE} here.}
 
+\item{value}{Check detail sections for requirements.}
+
 \item{dataset}{Name or numeric index of a dataset}
 
 \item{type}{When using \code{dataset<-} with a matrix like \code{value},
@@ -315,9 +312,25 @@ acceptable. Default \code{NULL} works with all datasets.}
 \item{as.data.frame}{Logical, whether to apply
 \code{\link[base]{as.data.frame}} on the subscription. Default \code{FALSE}.}
 
+\item{...}{See detailed sections for explanation.}
+
+\item{inplace}{For \code{cellMeta<-} method, when \code{columns} is for
+existing variable and \code{useDatasets} or \code{cellIdx} indicate partial
+insertion to the object, whether to by default (\code{TRUE}) in-place insert
+\code{value} into the variable for selected cells or to replace the whole
+variable with non-selected part left as NA.}
+
 \item{name}{The name of available variables in \code{cellMeta} slot or the
 name of a new variable to store.}
 
+\item{funcName, arg}{See Command records section.}
+
+\item{slot}{Name of slot to retrieve matrix from. Options shown in Usage.}
+
+\item{returnList}{Logical, whether to force return a list even when only one
+dataset-specific matrix (i.e. expression matrices, H, V or U) is requested.
+Default \code{FALSE}.}
+
 \item{droplevels}{Whether to remove unused cluster levels from the factor
 object fetched by \code{defaultCluster()}. Default \code{FALSE}.}
 
@@ -326,14 +339,6 @@ default for visualization methods. Default \code{NULL} sets it when no
 default has been set yet, otherwise does not change current default.}
 
 \item{data}{fortify method required argument. Not used.}
-
-\item{funcName, arg}{See Command records section.}
-
-\item{slot}{Name of slot to retrieve matrix from. Options shown in Usage.}
-
-\item{returnList}{Logical, whether to force return a list even when only one
-dataset-specific matrix (i.e. expression matrices, H, V or U) is requested.
-Default \code{FALSE}.}
 }
 \value{
 See detailed sections for explanetion.
@@ -386,36 +391,6 @@ accordingly.}
 \item{\code{version}}{Record of version of rliger2 package}
 }}
 
-\section{Dimensionality}{
-
-For a \code{liger} object, the column orientation is assigned for
-cells. Due to the data structure, it is hard to define a row index for the
-\code{liger} object, which might contain datasets that vary in number of
-genes.
-
-Therefore, for \code{liger} objects, \code{dim} and \code{dimnames} returns
-\code{NA}/\code{NULL} for rows and total cell counts/barcodes for the
-columns.
-
-For direct call of \code{dimnames<-} method, \code{value} should be a list
-with \code{NULL} as the first element and valid cell identifiers as the
-second element. For \code{colnames<-} method, the character vector of cell
-identifiers. \code{rownames<-} method is not applicable.
-}
-
-\section{Subsetting}{
-
-For more detail of subsetting a \code{liger} object or a
-\linkS4class{ligerDataset} object, please check out \code{\link{subsetLiger}}
-and \code{\link{subsetLigerDataset}}. Here, we set the S4 method
-"single-bracket" \code{[} as a quick wrapper to subset a \code{liger} object.
-Note that \code{j} serves as cell subscriptor which can be any valid index
-refering the collection of all cells (i.e. \code{rownames(cellMeta(obj))}).
-While \code{i}, the feature subscriptor can only be character vector because
-the features for each dataset can vary. \code{...} arugments are passed to
-\code{subsetLiger} so that advanced options are allowed.
-}
-
 \section{Dataset access}{
 
 \code{datasets()} method only accesses the \code{datasets} slot, the list of
@@ -517,14 +492,6 @@ of inner \code{ligerDataset} objects as well as the \code{W} and
 \code{H.norm} slots of the input \code{liger} object.
 }
 
-\section{Combining multiple liger object}{
- The list of \code{datasets} slot,
-the rows of \code{cellMeta} slot and the list of \code{commands} slot will
-be simply concatenated. Variable features in \code{varFeatures} slot will be
-taken a union. The \eqn{W} and \eqn{H.norm} matrices are not taken into
-account for now.
-}
-
 \section{Command records}{
 
 rliger functions, that perform calculation and update the \code{liger}
@@ -541,6 +508,44 @@ all louvain cluster attempts: \code{commands(ligerObj, "louvainCluster",
 "resolution")}
 }
 
+\section{Dimensionality}{
+
+For a \code{liger} object, the column orientation is assigned for
+cells. Due to the data structure, it is hard to define a row index for the
+\code{liger} object, which might contain datasets that vary in number of
+genes.
+
+Therefore, for \code{liger} objects, \code{dim} and \code{dimnames} returns
+\code{NA}/\code{NULL} for rows and total cell counts/barcodes for the
+columns.
+
+For direct call of \code{dimnames<-} method, \code{value} should be a list
+with \code{NULL} as the first element and valid cell identifiers as the
+second element. For \code{colnames<-} method, the character vector of cell
+identifiers. \code{rownames<-} method is not applicable.
+}
+
+\section{Subsetting}{
+
+For more detail of subsetting a \code{liger} object or a
+\linkS4class{ligerDataset} object, please check out \code{\link{subsetLiger}}
+and \code{\link{subsetLigerDataset}}. Here, we set the S4 method
+"single-bracket" \code{[} as a quick wrapper to subset a \code{liger} object.
+Note that \code{j} serves as cell subscriptor which can be any valid index
+refering the collection of all cells (i.e. \code{rownames(cellMeta(obj))}).
+While \code{i}, the feature subscriptor can only be character vector because
+the features for each dataset can vary. \code{...} arugments are passed to
+\code{subsetLiger} so that advanced options are allowed.
+}
+
+\section{Combining multiple liger object}{
+ The list of \code{datasets} slot,
+the rows of \code{cellMeta} slot and the list of \code{commands} slot will
+be simply concatenated. Variable features in \code{varFeatures} slot will be
+taken a union. The \eqn{W} and \eqn{H.norm} matrices are not taken into
+account for now.
+}
+
 \examples{
 # Methods for base generics
 pbmcPlot
diff --git a/man/ligerATACDataset-class.Rd b/man/ligerATACDataset-class.Rd
index a7d53039..07f07c03 100644
--- a/man/ligerATACDataset-class.Rd
+++ b/man/ligerATACDataset-class.Rd
@@ -1,5 +1,5 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ligerDataset_subclasses.R
+% Please edit documentation in R/classes.R
 \docType{class}
 \name{ligerATACDataset-class}
 \alias{ligerATACDataset-class}
diff --git a/man/ligerCommand-class.Rd b/man/ligerCommand-class.Rd
index f8e13d65..fdc46da7 100644
--- a/man/ligerCommand-class.Rd
+++ b/man/ligerCommand-class.Rd
@@ -1,5 +1,5 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ligerCommand-class.R
+% Please edit documentation in R/classes.R, R/ligerCommand_relates.R
 \docType{class}
 \name{ligerCommand-class}
 \alias{ligerCommand-class}
diff --git a/man/ligerDataset-class.Rd b/man/ligerDataset-class.Rd
index e75aa15f..7c10002e 100644
--- a/man/ligerDataset-class.Rd
+++ b/man/ligerDataset-class.Rd
@@ -1,50 +1,81 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ligerDataset-class.R
+% Please edit documentation in R/classes.R, R/generics.R,
+%   R/ligerDataset-methods.R
 \docType{class}
 \name{ligerDataset-class}
 \alias{ligerDataset-class}
 \alias{ligerDataset}
+\alias{rawData}
+\alias{rawData<-}
+\alias{normData}
+\alias{normData<-}
+\alias{scaleData}
+\alias{scaleData<-}
+\alias{scaleUnsharedData}
+\alias{scaleUnsharedData<-}
+\alias{getMatrix}
+\alias{h5fileInfo}
+\alias{h5fileInfo<-}
+\alias{getH5File}
+\alias{getH5File,ligerDataset,missing-method}
+\alias{featureMeta}
+\alias{featureMeta<-}
 \alias{show,ligerDataset-method}
 \alias{dim,ligerDataset-method}
 \alias{dimnames,ligerDataset-method}
 \alias{dimnames<-,ligerDataset,list-method}
-\alias{rawData}
-\alias{rawData<-}
 \alias{rawData,ligerDataset-method}
 \alias{rawData<-,ligerDataset,ANY,ANY,matrixLike_OR_NULL-method}
 \alias{rawData<-,ligerDataset,ANY,ANY,H5D-method}
-\alias{normData}
-\alias{normData<-}
 \alias{normData,ligerDataset-method}
 \alias{normData<-,ligerDataset,ANY,ANY,matrixLike_OR_NULL-method}
 \alias{normData<-,ligerDataset,ANY,ANY,H5D-method}
-\alias{scaleData}
-\alias{scaleData<-}
 \alias{scaleData,ligerDataset,missing-method}
 \alias{scaleData<-,ligerDataset,ANY,ANY,matrixLike_OR_NULL-method}
 \alias{scaleData<-,ligerDataset,ANY,ANY,H5D-method}
 \alias{scaleData<-,ligerDataset,ANY,ANY,H5Group-method}
-\alias{scaleUnsharedData}
-\alias{scaleUnsharedData<-}
 \alias{scaleUnsharedData,ligerDataset,missing-method}
 \alias{scaleUnsharedData<-,ligerDataset,missing,ANY,matrixLike_OR_NULL-method}
 \alias{scaleUnsharedData<-,ligerDataset,missing,ANY,H5D-method}
 \alias{scaleUnsharedData<-,ligerDataset,missing,ANY,H5Group-method}
-\alias{getMatrix}
 \alias{getMatrix,ligerDataset,ANY,missing,missing-method}
-\alias{h5fileInfo}
-\alias{h5fileInfo<-}
 \alias{h5fileInfo,ligerDataset-method}
 \alias{h5fileInfo<-,ligerDataset-method}
-\alias{getH5File}
-\alias{getH5File,ligerDataset,missing-method}
-\alias{featureMeta}
-\alias{featureMeta<-}
 \alias{featureMeta,ligerDataset-method}
 \alias{featureMeta<-,ligerDataset-method}
 \alias{cbind.ligerDataset}
 \title{ligerDataset class}
 \usage{
+rawData(x, dataset = NULL)
+
+rawData(x, dataset = NULL, check = TRUE) <- value
+
+normData(x, dataset = NULL)
+
+normData(x, dataset = NULL, check = TRUE) <- value
+
+scaleData(x, dataset = NULL)
+
+scaleData(x, dataset = NULL, check = TRUE) <- value
+
+scaleUnsharedData(x, dataset = NULL)
+
+scaleUnsharedData(x, dataset = NULL, check = TRUE) <- value
+
+getMatrix(x, slot = "rawData", dataset = NULL, returnList = FALSE)
+
+h5fileInfo(x, info = NULL)
+
+h5fileInfo(x, info = NULL, check = TRUE) <- value
+
+getH5File(x, dataset = NULL)
+
+\S4method{getH5File}{ligerDataset,missing}(x, dataset = NULL)
+
+featureMeta(x, check = NULL)
+
+featureMeta(x, check = TRUE) <- value
+
 \S4method{show}{ligerDataset}(object)
 
 \S4method{dim}{ligerDataset}(x)
@@ -53,30 +84,18 @@
 
 \S4method{dimnames}{ligerDataset,list}(x) <- value
 
-rawData(x, dataset = NULL)
-
-rawData(x, dataset = NULL, check = TRUE) <- value
-
 \S4method{rawData}{ligerDataset}(x, dataset = NULL)
 
 \S4method{rawData}{ligerDataset,ANY,ANY,matrixLike_OR_NULL}(x, dataset = NULL, check = TRUE) <- value
 
 \S4method{rawData}{ligerDataset,ANY,ANY,H5D}(x, dataset = NULL, check = TRUE) <- value
 
-normData(x, dataset = NULL)
-
-normData(x, dataset = NULL, check = TRUE) <- value
-
 \S4method{normData}{ligerDataset}(x, dataset = NULL)
 
 \S4method{normData}{ligerDataset,ANY,ANY,matrixLike_OR_NULL}(x, dataset = NULL, check = TRUE) <- value
 
 \S4method{normData}{ligerDataset,ANY,ANY,H5D}(x, dataset = NULL, check = TRUE) <- value
 
-scaleData(x, dataset = NULL)
-
-scaleData(x, dataset = NULL, check = TRUE) <- value
-
 \S4method{scaleData}{ligerDataset,missing}(x, dataset = NULL)
 
 \S4method{scaleData}{ligerDataset,ANY,ANY,matrixLike_OR_NULL}(x, dataset = NULL, check = TRUE) <- value
@@ -85,10 +104,6 @@ scaleData(x, dataset = NULL, check = TRUE) <- value
 
 \S4method{scaleData}{ligerDataset,ANY,ANY,H5Group}(x, dataset = NULL, check = TRUE) <- value
 
-scaleUnsharedData(x, dataset = NULL)
-
-scaleUnsharedData(x, dataset = NULL, check = TRUE) <- value
-
 \S4method{scaleUnsharedData}{ligerDataset,missing}(x, dataset = NULL)
 
 \S4method{scaleUnsharedData}{ligerDataset,missing,ANY,matrixLike_OR_NULL}(x, check = TRUE) <- value
@@ -97,8 +112,6 @@ scaleUnsharedData(x, dataset = NULL, check = TRUE) <- value
 
 \S4method{scaleUnsharedData}{ligerDataset,missing,ANY,H5Group}(x, check = TRUE) <- value
 
-getMatrix(x, slot = "rawData", dataset = NULL, returnList = FALSE)
-
 \S4method{getMatrix}{ligerDataset,ANY,missing,missing}(
   x,
   slot = c("rawData", "normData", "scaleData", "scaleUnsharedData", "H", "V", "U", "A",
@@ -106,22 +119,10 @@ getMatrix(x, slot = "rawData", dataset = NULL, returnList = FALSE)
   dataset = NULL
 )
 
-h5fileInfo(x, info = NULL)
-
-h5fileInfo(x, info = NULL, check = TRUE) <- value
-
 \S4method{h5fileInfo}{ligerDataset}(x, info = NULL)
 
 \S4method{h5fileInfo}{ligerDataset}(x, info = NULL, check = TRUE) <- value
 
-getH5File(x, dataset = NULL)
-
-\S4method{getH5File}{ligerDataset,missing}(x, dataset = NULL)
-
-featureMeta(x, check = NULL)
-
-featureMeta(x, check = TRUE) <- value
-
 \S4method{featureMeta}{ligerDataset}(x, check = NULL)
 
 \S4method{featureMeta}{ligerDataset}(x, check = TRUE) <- value
@@ -131,12 +132,12 @@ featureMeta(x, check = TRUE) <- value
 \arguments{
 \item{x, object}{A \code{ligerDataset} object.}
 
-\item{value}{See detail sections for requirements}
-
 \item{dataset}{Not applicable for \code{ligerDataset} methods.}
 
 \item{check}{Whether to perform object validity check on setting new value.}
 
+\item{value}{See detail sections for requirements}
+
 \item{slot}{The slot name when using \code{getMatrix}.}
 
 \item{returnList}{Not applicable for \code{ligerDataset} methods.}
@@ -184,33 +185,6 @@ datasets}
 \item{\code{rownames}}{character}
 }}
 
-\section{Dimensionality}{
-
-For a \code{ligerDataset} object, the column orientation is assigned for
-cells and rows are for features. Therefore, for \code{ligerDataset} objects,
-\code{dim()} returns a numeric vector of two numbers which are number of
-features and number of cells. \code{dimnames()} returns a list of two
-character vectors, which are the feature names and the cell barcodes.
-
-For direct call of \code{dimnames<-} method, \code{value} should be a list
-with a character vector of feature names as the first element and cell
-identifiers as the second element. For \code{colnames<-} method, the
-character vector of cell identifiers. For \code{rownames<-} method, the
-character vector of feature names.
-}
-
-\section{Subsetting}{
-
-For more detail of subsetting a \code{liger} object or a
-\linkS4class{ligerDataset} object, please check out \code{\link{subsetLiger}}
-and \code{\link{subsetLigerDataset}}. Here, we set the S3 method
-"single-bracket" \code{[} as a quick wrapper to subset a \code{ligerDataset}
-object. \code{i} and \code{j} serves as feature and cell subscriptor,
-respectively, which can be any valid index refering the available features
-and cells in a dataset. \code{...} arugments are passed to
-\code{subsetLigerDataset} so that advanced options are allowed.
-}
-
 \section{Matrix access}{
 
 For \code{ligerDataset} object, \code{rawData()}, \code{normData},
@@ -260,6 +234,33 @@ For example, \code{featureMeta(ligerD)$nCell} or
 \code{featureMeta(ligerD)[varFeatures(ligerObj), "gene_var"]}.
 }
 
+\section{Dimensionality}{
+
+For a \code{ligerDataset} object, the column orientation is assigned for
+cells and rows are for features. Therefore, for \code{ligerDataset} objects,
+\code{dim()} returns a numeric vector of two numbers which are number of
+features and number of cells. \code{dimnames()} returns a list of two
+character vectors, which are the feature names and the cell barcodes.
+
+For direct call of \code{dimnames<-} method, \code{value} should be a list
+with a character vector of feature names as the first element and cell
+identifiers as the second element. For \code{colnames<-} method, the
+character vector of cell identifiers. For \code{rownames<-} method, the
+character vector of feature names.
+}
+
+\section{Subsetting}{
+
+For more detail of subsetting a \code{liger} object or a
+\linkS4class{ligerDataset} object, please check out \code{\link{subsetLiger}}
+and \code{\link{subsetLigerDataset}}. Here, we set the S3 method
+"single-bracket" \code{[} as a quick wrapper to subset a \code{ligerDataset}
+object. \code{i} and \code{j} serves as feature and cell subscriptor,
+respectively, which can be any valid index refering the available features
+and cells in a dataset. \code{...} arugments are passed to
+\code{subsetLigerDataset} so that advanced options are allowed.
+}
+
 \section{Concatenate ligerDataset}{
 
 \code{cbind()} method is implemented for concatenating \code{ligerDataset}
diff --git a/man/ligerMethDataset-class.Rd b/man/ligerMethDataset-class.Rd
index af068570..8c7009ce 100644
--- a/man/ligerMethDataset-class.Rd
+++ b/man/ligerMethDataset-class.Rd
@@ -1,5 +1,5 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ligerDataset_subclasses.R
+% Please edit documentation in R/classes.R
 \docType{class}
 \name{ligerMethDataset-class}
 \alias{ligerMethDataset-class}
diff --git a/man/ligerRNADataset-class.Rd b/man/ligerRNADataset-class.Rd
index a57d6a85..ddb35a84 100644
--- a/man/ligerRNADataset-class.Rd
+++ b/man/ligerRNADataset-class.Rd
@@ -1,5 +1,5 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ligerDataset_subclasses.R
+% Please edit documentation in R/classes.R
 \docType{class}
 \name{ligerRNADataset-class}
 \alias{ligerRNADataset-class}
diff --git a/man/ligerSpatialDataset-class.Rd b/man/ligerSpatialDataset-class.Rd
index bd4b266f..e59146fd 100644
--- a/man/ligerSpatialDataset-class.Rd
+++ b/man/ligerSpatialDataset-class.Rd
@@ -1,5 +1,5 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ligerDataset_subclasses.R
+% Please edit documentation in R/classes.R
 \docType{class}
 \name{ligerSpatialDataset-class}
 \alias{ligerSpatialDataset-class}
diff --git a/man/modalOf.Rd b/man/modalOf.Rd
index fb1b5d4e..139301fa 100644
--- a/man/modalOf.Rd
+++ b/man/modalOf.Rd
@@ -1,5 +1,5 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ligerDataset-class.R
+% Please edit documentation in R/ligerDataset-methods.R
 \name{modalOf}
 \alias{modalOf}
 \title{Return preset modality of a ligerDataset object or that of all datasets in a
diff --git a/man/normalize.Rd b/man/normalize.Rd
index 2145f81a..8d1f48ba 100644
--- a/man/normalize.Rd
+++ b/man/normalize.Rd
@@ -13,12 +13,12 @@ normalize(object, ...)
 
 \method{normalize}{dgCMatrix}(object, log = FALSE, scaleFactor = NULL, ...)
 
-\method{normalize}{ligerDataset}(object, chunk = 1000, verbose = getOption("ligerVerbose"), ...)
+\method{normalize}{ligerDataset}(object, chunk = 1000, verbose = getOption("ligerVerbose", TRUE), ...)
 
 \method{normalize}{liger}(
   object,
   useDatasets = NULL,
-  verbose = getOption("ligerVerbose"),
+  verbose = getOption("ligerVerbose", TRUE),
   format.type = NULL,
   remove.missing = NULL,
   ...
@@ -29,7 +29,7 @@ normalize(object, ...)
 normalizePeak(
   object,
   useDatasets = NULL,
-  verbose = getOption("ligerVerbose"),
+  verbose = getOption("ligerVerbose", TRUE),
   ...
 )
 }
@@ -51,7 +51,7 @@ factor before transformation. \code{NULL} for not scaling. Default
 working on HDF5 file based ligerDataset. Default \code{1000}.}
 
 \item{verbose}{Logical. Whether to show information of the progress. Default
-\code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.}
+\code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.}
 
 \item{useDatasets}{A character vector of the names, a numeric or logical
 vector of the index of the datasets to be normalized. Should specify ATACseq
diff --git a/man/peak.Rd b/man/peak.Rd
index 4dfbd19a..851cbe05 100644
--- a/man/peak.Rd
+++ b/man/peak.Rd
@@ -1,5 +1,6 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ligerDataset_subclasses.R
+% Please edit documentation in R/generics.R, R/liger-methods.R,
+%   R/ligerDataset_subclass-methods.R
 \name{rawPeak}
 \alias{rawPeak}
 \alias{rawPeak<-}
@@ -7,10 +8,10 @@
 \alias{normPeak<-}
 \alias{rawPeak,liger,character-method}
 \alias{rawPeak<-,liger,character-method}
-\alias{rawPeak,ligerATACDataset,missing-method}
-\alias{rawPeak<-,ligerATACDataset,missing-method}
 \alias{normPeak,liger,character-method}
 \alias{normPeak<-,liger,character-method}
+\alias{rawPeak,ligerATACDataset,missing-method}
+\alias{rawPeak<-,ligerATACDataset,missing-method}
 \alias{normPeak,ligerATACDataset,missing-method}
 \alias{normPeak<-,ligerATACDataset,missing-method}
 \title{Access ligerATACDataset peak data}
@@ -27,14 +28,14 @@ normPeak(x, dataset, check = TRUE) <- value
 
 \S4method{rawPeak}{liger,character}(x, dataset, check = TRUE) <- value
 
-\S4method{rawPeak}{ligerATACDataset,missing}(x, dataset = NULL)
-
-\S4method{rawPeak}{ligerATACDataset,missing}(x, dataset = NULL, check = TRUE) <- value
-
 \S4method{normPeak}{liger,character}(x, dataset)
 
 \S4method{normPeak}{liger,character}(x, dataset, check = TRUE) <- value
 
+\S4method{rawPeak}{ligerATACDataset,missing}(x, dataset = NULL)
+
+\S4method{rawPeak}{ligerATACDataset,missing}(x, dataset = NULL, check = TRUE) <- value
+
 \S4method{normPeak}{ligerATACDataset,missing}(x, dataset = NULL)
 
 \S4method{normPeak}{ligerATACDataset,missing}(x, dataset = NULL, check = TRUE) <- value
diff --git a/man/plotVolcano.Rd b/man/plotVolcano.Rd
index fdf586f0..f5becf37 100644
--- a/man/plotVolcano.Rd
+++ b/man/plotVolcano.Rd
@@ -59,3 +59,7 @@ most of arguments with other rliger plotting functions.
 substantial amount of arguments for graphical control. However, that requires
 the installation of package "EnhancedVolcano".
 }
+\examples{
+result <- runMarkerDEG(pbmcPlot)
+plotVolcano(result, 1)
+}
diff --git a/man/reexports.Rd b/man/reexports.Rd
index 8cd827d2..68970992 100644
--- a/man/reexports.Rd
+++ b/man/reexports.Rd
@@ -1,5 +1,5 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/zzz.R
+% Please edit documentation in R/aaa.R
 \docType{import}
 \name{reexports}
 \alias{reexports}
diff --git a/man/removeMissing.Rd b/man/removeMissing.Rd
index 34fc12e3..7cd4404a 100644
--- a/man/removeMissing.Rd
+++ b/man/removeMissing.Rd
@@ -13,7 +13,7 @@ removeMissing(
   useDatasets = NULL,
   newH5 = TRUE,
   filenameSuffix = "removeMissing",
-  verbose = getOption("ligerVerbose"),
+  verbose = getOption("ligerVerbose", TRUE),
   ...
 )
 
@@ -21,7 +21,7 @@ removeMissingObs(
   object,
   slot.use = NULL,
   use.cols = TRUE,
-  verbose = getOption("ligerVerbose")
+  verbose = getOption("ligerVerbose", TRUE)
 )
 }
 \arguments{
@@ -51,7 +51,7 @@ H5-based dataset on subset. Default \code{TRUE}}
 suffix will be added to all the filenames. Default \code{"removeMissing"}.}
 
 \item{verbose}{Logical. Whether to show information of the progress. Default
-\code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.}
+\code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.}
 
 \item{...}{Arguments passed to \code{\link{subsetLigerDataset}}}
 
diff --git a/man/reverseMethData.Rd b/man/reverseMethData.Rd
index 2e5b729a..15f6c055 100644
--- a/man/reverseMethData.Rd
+++ b/man/reverseMethData.Rd
@@ -4,7 +4,7 @@
 \alias{reverseMethData}
 \title{Create "scaled data" for DNA methylation datasets}
 \usage{
-reverseMethData(object, useDatasets, verbose = getOption("ligerVerbose"))
+reverseMethData(object, useDatasets, verbose = getOption("ligerVerbose", TRUE))
 }
 \arguments{
 \item{object}{A \linkS4class{liger} object, with variable genes identified.}
@@ -14,7 +14,7 @@ logical vector of the index of the datasets that should be identified as
 methylation data where the reversed data will be created.}
 
 \item{verbose}{Logical. Whether to show information of the progress. Default
-\code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.}
+\code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.}
 }
 \value{
 The input \linkS4class{liger} object, where the \code{scaleData} slot
diff --git a/man/runCluster.Rd b/man/runCluster.Rd
index 5d3ec01b..d0230dd2 100644
--- a/man/runCluster.Rd
+++ b/man/runCluster.Rd
@@ -18,7 +18,7 @@ runCluster(
   groupSingletons = TRUE,
   clusterName = paste0(method, "_cluster"),
   seed = 1,
-  verbose = getOption("ligerVerbose")
+  verbose = getOption("ligerVerbose", TRUE)
 )
 }
 \arguments{
diff --git a/man/runGeneralQC.Rd b/man/runGeneralQC.Rd
index cc5d6f4c..d95ef128 100644
--- a/man/runGeneralQC.Rd
+++ b/man/runGeneralQC.Rd
@@ -13,7 +13,7 @@ runGeneralQC(
   pattern = NULL,
   useDatasets = NULL,
   chunkSize = 1000,
-  verbose = getOption("ligerVerbose")
+  verbose = getOption("ligerVerbose", TRUE)
 )
 }
 \arguments{
@@ -40,7 +40,7 @@ vector of the index of the datasets to be included for QC. Default
 on HDF5 based dataset. Default \code{1000}}
 
 \item{verbose}{Logical. Whether to show information of the progress. Default
-\code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.}
+\code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.}
 }
 \value{
 Updated \code{object} with \code{nUMI}, \code{nGene} updated
diff --git a/man/scaleNotCenter.Rd b/man/scaleNotCenter.Rd
index 4eb2588e..f8a48cc2 100644
--- a/man/scaleNotCenter.Rd
+++ b/man/scaleNotCenter.Rd
@@ -17,14 +17,14 @@ scaleNotCenter(object, ...)
   object,
   features = NULL,
   chunk = 1000,
-  verbose = getOption("ligerVerbose"),
+  verbose = getOption("ligerVerbose", TRUE),
   ...
 )
 
 \method{scaleNotCenter}{ligerMethDataset}(
   object,
   features = NULL,
-  verbose = getOption("ligerVerbose"),
+  verbose = getOption("ligerVerbose", TRUE),
   ...
 )
 
@@ -32,7 +32,7 @@ scaleNotCenter(object, ...)
   object,
   useDatasets = NULL,
   features = varFeatures(object),
-  verbose = getOption("ligerVerbose"),
+  verbose = getOption("ligerVerbose", TRUE),
   remove.missing = NULL,
   ...
 )
@@ -65,7 +65,7 @@ features. "Seurat" method by default uses
 scaling is applied to any HDF5 based dataset. Default \code{1000}.}
 
 \item{verbose}{Logical. Whether to show information of the progress. Default
-\code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.}
+\code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.}
 
 \item{useDatasets}{A character vector of the names, a numeric or logical
 vector of the index of the datasets to be scaled but not centered. Default
diff --git a/man/selectGenes.Rd b/man/selectGenes.Rd
index fa1ea7cb..46e389ce 100644
--- a/man/selectGenes.Rd
+++ b/man/selectGenes.Rd
@@ -18,7 +18,7 @@ selectGenes(object, thresh = 0.1, nGenes = NULL, alpha = 0.99, ...)
   unsharedThresh = 0.1,
   combine = c("union", "intersection"),
   chunk = 1000,
-  verbose = getOption("ligerVerbose"),
+  verbose = getOption("ligerVerbose", TRUE),
   var.thresh = thresh,
   alpha.thresh = alpha,
   num.genes = nGenes,
@@ -42,7 +42,7 @@ selectGenes(object, thresh = 0.1, nGenes = NULL, alpha = 0.99, ...)
   assay = NULL,
   datasetVar = "orig.ident",
   combine = c("union", "intersection"),
-  verbose = getOption("ligerVerbose"),
+  verbose = getOption("ligerVerbose", TRUE),
   ...
 )
 }
@@ -88,7 +88,7 @@ Choose from \code{"union"} or \code{"intersection"}. Default \code{"union"}.}
 gene selection is applied to any HDF5 based dataset. Default \code{1000}.}
 
 \item{verbose}{Logical. Whether to show information of the progress. Default
-\code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.}
+\code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.}
 
 \item{var.thresh, alpha.thresh, num.genes, datasets.use, unshared.datasets, unshared.thresh}{\bold{Deprecated}.
 These arguments are renamed and will be removed in the future. Please see
diff --git a/man/selectGenesVST.Rd b/man/selectGenesVST.Rd
index 6b288a17..d969d2e5 100644
--- a/man/selectGenesVST.Rd
+++ b/man/selectGenesVST.Rd
@@ -11,7 +11,7 @@ selectGenesVST(
   loessSpan = 0.3,
   clipMax = "auto",
   useShared = TRUE,
-  verbose = getOption("ligerVerbose")
+  verbose = getOption("ligerVerbose", TRUE)
 )
 }
 \arguments{
@@ -33,7 +33,7 @@ root of the number of cells.}
 dataset. Default \code{TRUE}.}
 
 \item{verbose}{Logical. Whether to show information of the progress. Default
-\code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.}
+\code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.}
 }
 \description{
 Seurat FindVariableFeatures VST method. This allows the selection of a fixed
diff --git a/man/sub-liger.Rd b/man/sub-liger.Rd
new file mode 100644
index 00000000..25dbf90c
--- /dev/null
+++ b/man/sub-liger.Rd
@@ -0,0 +1,32 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/liger-methods.R
+\name{sub-liger}
+\alias{sub-liger}
+\alias{[.liger}
+\title{Subset liger with brackets}
+\usage{
+\method{[}{liger}(x, i, j, ...)
+}
+\arguments{
+\item{x}{A \linkS4class{liger} object}
+
+\item{i}{Feature subscriptor, passed to \code{featureIdx} of
+\code{\link{subsetLiger}}.}
+
+\item{j}{Cell subscriptor, passed to \code{cellIdx} of
+\code{\link{subsetLiger}}.}
+
+\item{...}{Additional arguments passed to \code{\link{subsetLiger}}.}
+}
+\value{
+Subset of \code{x} with specified features and cells.
+}
+\description{
+Subset liger with brackets
+}
+\examples{
+pbmcPlot[varFeatures(pbmcPlot)[1:10], 1:10]
+}
+\seealso{
+\code{\link{subsetLiger}}
+}
diff --git a/man/sub-ligerDataset.Rd b/man/sub-ligerDataset.Rd
index 7cc893d9..91f36773 100644
--- a/man/sub-ligerDataset.Rd
+++ b/man/sub-ligerDataset.Rd
@@ -1,5 +1,5 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ligerDataset-class.R
+% Please edit documentation in R/ligerDataset-methods.R
 \name{sub-ligerDataset}
 \alias{sub-ligerDataset}
 \alias{[.ligerDataset}
diff --git a/man/sub-sub-liger.Rd b/man/sub-sub-liger.Rd
index 973236b3..7aeeea73 100644
--- a/man/sub-sub-liger.Rd
+++ b/man/sub-sub-liger.Rd
@@ -1,5 +1,5 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/liger-class.R
+% Please edit documentation in R/liger-methods.R
 \name{sub-sub-liger}
 \alias{sub-sub-liger}
 \alias{[[.liger}
diff --git a/man/sub-subset-.liger.Rd b/man/sub-subset-.liger.Rd
index fceb8c11..bbe1f646 100644
--- a/man/sub-subset-.liger.Rd
+++ b/man/sub-subset-.liger.Rd
@@ -1,5 +1,5 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/liger-class.R
+% Please edit documentation in R/liger-methods.R
 \name{[[<-,liger,ANY,missing,ANY-method}
 \alias{[[<-,liger,ANY,missing,ANY-method}
 \alias{[[<-,liger,ANY,missing-method}
diff --git a/man/subsetLiger.Rd b/man/subsetLiger.Rd
index e2b62939..311d4e65 100644
--- a/man/subsetLiger.Rd
+++ b/man/subsetLiger.Rd
@@ -10,7 +10,7 @@ subsetLiger(
   cellIdx = NULL,
   useSlot = NULL,
   chunkSize = 1000,
-  verbose = getOption("ligerVerbose"),
+  verbose = getOption("ligerVerbose", TRUE),
   newH5 = TRUE,
   returnObject = TRUE,
   ...
@@ -33,7 +33,7 @@ Missing or \code{NULL} for all cells.}
 Default \code{1000}.}
 
 \item{verbose}{Logical. Whether to show information of the progress. Default
-\code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.}
+\code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.}
 
 \item{newH5}{Whether to create new H5 files on disk for the subset datasets
 if involved datasets in the \code{object} is HDF5 based. \code{TRUE} writes a
diff --git a/man/subsetLigerDataset.Rd b/man/subsetLigerDataset.Rd
index 4fb6528d..6380f80a 100644
--- a/man/subsetLigerDataset.Rd
+++ b/man/subsetLigerDataset.Rd
@@ -15,7 +15,7 @@ subsetLigerDataset(
   filename = NULL,
   filenameSuffix = NULL,
   chunkSize = 1000,
-  verbose = getOption("ligerVerbose"),
+  verbose = getOption("ligerVerbose", TRUE),
   returnObject = TRUE,
   ...
 )
@@ -29,7 +29,7 @@ subsetH5LigerDataset(
   filename = NULL,
   filenameSuffix = NULL,
   chunkSize = 1000,
-  verbose = getOption("ligerVerbose"),
+  verbose = getOption("ligerVerbose", TRUE),
   returnObject = TRUE
 )
 
@@ -71,7 +71,7 @@ for the new files so the new filename looks like
 Default \code{1000}.}
 
 \item{verbose}{Logical. Whether to show information of the progress. Default
-\code{getOption("ligerVerbose")} which is \code{TRUE} if users have not set.}
+\code{getOption("ligerVerbose")} or \code{TRUE} if users have not set.}
 
 \item{returnObject}{Logical, whether to return a \linkS4class{ligerDataset}
 object for result. Default \code{TRUE}. \code{FALSE} returns a list
diff --git a/tests/testthat/test_downstream.R b/tests/testthat/test_downstream.R
index e6754e60..31d09697 100644
--- a/tests/testthat/test_downstream.R
+++ b/tests/testthat/test_downstream.R
@@ -156,10 +156,8 @@ test_that("wilcoxon", {
 
     expect_error(getFactorMarkers(pbmc, "ctrl", "stim", factorShareThresh = 0),
                  "No factor passed the dataset specificity threshold")
-    expect_warning(
-        expect_message(
-            res3 <- getFactorMarkers(pbmc, "ctrl", "stim", printGenes = TRUE)
-        )
+    expect_message(
+        res3 <- getFactorMarkers(pbmc, "ctrl", "stim", printGenes = TRUE)
     )
     expect_is(res3, "list")
     expect_identical(names(res3), c("ctrl", "shared", "stim", "num_factors_V1",
@@ -215,7 +213,7 @@ test_that("pseudo bulk", {
             groupCtrl = pbmc$dataset == "stim" & pbmc$leiden_cluster == 0,
             method = "pseudo", useReplicate = "dataset"
         ),
-        "Too few replicates label for condition"
+        "Too few replicates for condition"
     )
 
     pbmc@datasets$ctrl@rawData <- NULL
@@ -225,7 +223,7 @@ test_that("pseudo bulk", {
             variable1 = "leiden_cluster",　method = "pseudo",
             useReplicate = "dataset"
         ),
-        "rawData not all available for involved datasets"
+        "not all available for involved datasets"
     )
 })
 
diff --git a/tests/testthat/test_factorization.R b/tests/testthat/test_factorization.R
index fd38b3c9..5908ae1f 100644
--- a/tests/testthat/test_factorization.R
+++ b/tests/testthat/test_factorization.R
@@ -249,14 +249,14 @@ test_that("Seurat wrapper", {
     expect_in("onlineINMF", SeuratObject::Reductions(seu))
 
     expect_error(quantileNorm(seu, reduction = "orig.ident"),
-                 "Specified `reduction` does not points to a DimReduc")
+                 "Specified `reduction` does not points to a")
     seu <- quantileNorm(seu, reduction = "inmf")
     expect_in("inmfNorm", SeuratObject::Reductions(seu))
 
     expect_error(quantileNorm(seu, reference = "hello"),
                  "Should specify one existing dataset")
     expect_error(quantileNorm(seu, reference = 114514),
-                 "Should specify one dataset within the range.")
+                 "Should specify one existing dataset as reference")
     expect_error(quantileNorm(seu, reference = c(TRUE, FALSE, TRUE)),
-                 "Should specify one dataset within the range.")
+                 "Should specify one existing dataset as reference")
 })
diff --git a/tests/testthat/test_object.R b/tests/testthat/test_object.R
index 99f31d75..ca31f83d 100644
--- a/tests/testthat/test_object.R
+++ b/tests/testthat/test_object.R
@@ -60,7 +60,7 @@ test_that("liger object creation - in memory", {
     expect_error(createLiger(rawData = "hi"),
                  "`rawData` has to be a named list.")
     expect_error(createLiger(rawData = rawDataList, modal = letters[1:3]),
-                 "`modal` has to be a vector of length 2")
+                 "`modal` has to be a length 1 or 2 object of class")
     ldList <- datasets(pbmc)
     cellmeta <- cellMeta(pbmc)
     pbmc2 <- createLiger(rawData = ldList, cellMeta = cellmeta,
@@ -83,7 +83,7 @@ test_that("liger object creation - on disk", {
     withNewH5Copy(
         function(rawList) {
             expect_error(createLiger(rawList, formatType = "Hello"),
-                         "Specified `formatType` '")
+                         "Specified `formatType`")
 
             # Customized paths
             barcodesName <- "matrix/barcodes"
@@ -161,8 +161,8 @@ test_that("liger S3/S4 methods", {
     expect_is(meta, "DFrame")
     expect_null(cellMeta(pbmc, NULL))
     expect_is(cellMeta(pbmc, "dataset"), "factor")
-    expect_warning(cellMeta(pbmc, "UMAP.1"),
-                   "Specified variables from cellMeta not found: UMAP.1")
+    expect_message(cellMeta(pbmc, "UMAP.1"),
+                   "Specified variables from cellMeta not found")
     expect_is(cellMeta(pbmc, "UMAP.1", cellIdx = 1:500, as.data.frame = TRUE),
               "numeric")
     expect_is(pbmc[["nUMI"]], "numeric")
@@ -198,7 +198,7 @@ test_that("liger S3/S4 methods", {
 
 test_that("ligerDataset (in memory) object creation", {
     expect_error(createLigerDataset(),
-                 "At least one type of")
+                 "At least one of")
 
     ld <- createLigerDataset(rawData = rawDataList[[1]], modal = "atac")
     expect_is(ld, "ligerATACDataset")
@@ -213,8 +213,10 @@ test_that("ligerDataset (in memory) object creation", {
     pbmc <- scaleNotCenter(pbmc)
     scaledMat <- scaleData(pbmc, dataset = "ctrl")
     featuremeta <- featureMeta(dataset(pbmc, "ctrl"))
-    ld <- createLigerDataset(scaleData = scaledMat, featureMeta = featuremeta)
-    expect_equal(length(varFeatures(pbmc)), nrow(ld))
+    expect_error(
+        ld <- createLigerDataset(scaleData = scaledMat, featureMeta = featuremeta),
+        "At least one of "
+    )
 })
 
 #%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@@ -227,7 +229,7 @@ test_that("ligerDataset methods", {
     expect_false(isH5Liger(pbmc))
     ctrl <- dataset(pbmc, "ctrl")
     expect_false(isH5Liger(ctrl))
-    expect_warning(isH5Liger("hi"), "Given object is not of liger")
+    expect_message(isH5Liger("hi"), "Given object is not ")
 
     expect_identical(modalOf(ctrl), "default")
     expect_identical(modalOf(pbmc), c(ctrl = "default", stim = "default"))
@@ -274,7 +276,7 @@ test_that("ligerDataset methods", {
 
     # ligerATACDataset related
     expect_error(rawPeak(pbmc, "stim"),
-                 "Specified dataset is not of ligerATACDataset class.")
+                 "Specified dataset is not of ")
     expect_error(rawPeak(pbmc, "stim") <- rawData(ctrl),
                  "Specified dataset is not of")
     ctrl <- as.ligerDataset(ctrl, modal = "atac")
@@ -282,7 +284,7 @@ test_that("ligerDataset methods", {
     rawPeak(pbmc, "ctrl") <- rawData(ctrl)
 
     expect_error(normPeak(pbmc, "stim"),
-                 "Specified dataset is not of ligerATACDataset class.")
+                 "Specified dataset is not of")
     expect_error(normPeak(pbmc, "stim") <- normData(stim),
                  "Specified dataset is not of")
     normPeak(pbmc, "ctrl") <- normData(ctrl)
@@ -290,7 +292,7 @@ test_that("ligerDataset methods", {
     expect_true(validObject(ctrl))
     # ligerSpatialDataset related
 
-    expect_warning(ctrl <- as.ligerDataset(ctrl, modal = "spatial"),
+    expect_message(ctrl <- as.ligerDataset(ctrl, modal = "spatial"),
                    "Will remove information in the following slots when ")
     pbmc@datasets$ctrl <- ctrl
     coords <- matrix(rnorm(300*2), 300, 2)
@@ -305,7 +307,7 @@ test_that("ligerDataset methods", {
     expect_true(validObject(ctrl))
 
     coords <- matrix(rnorm(300*3), 300, 3)
-    expect_warning(coordinate(ctrl) <- coords,
+    expect_message(coordinate(ctrl) <- coords,
                    "No rownames with given spatial coordinate")
     coords <- matrix(rnorm(300*4), 300, 4)
     rownames(coords) <- colnames(ctrl)
@@ -317,10 +319,10 @@ test_that("ligerDataset methods", {
     colnames(coords) <- c("x", "y")
     ctrl@coordinate <- coords
     expect_error(validObject(ctrl), "Inconsistant cell identifiers")
-    expect_warning(coordinate(ctrl) <- coords,
+    expect_message(coordinate(ctrl) <- coords,
                    "NA generated for missing cells")
     # ligerMethDataset related
-    expect_warning(ctrl <- as.ligerDataset(ctrl, modal = "meth"),
+    expect_message(ctrl <- as.ligerDataset(ctrl, modal = "meth"),
                    "Will remove information in the following slots when ")
     expect_no_error(validObject(ctrl))
 })
@@ -361,17 +363,17 @@ test_that("H5 ligerDataset methods", {
                              list(indicesName = "matrix/indices",
                                   indptrName = "matrix/indptr"))
             expect_error(h5fileInfo(ctrl, c("indicesName", "hello")),
-                         "Specified h5file info not found: hello")
+                         "Specified `info` not found")
 
             expect_error(h5fileInfo(ctrl, info = 1:2) <- "hey",
                          "`info` has to be a single character.")
             expect_error(h5fileInfo(ctrl, "indicesName") <- "hey",
-                         "Specified info is invalid,")
+                         "Specified `info`")
             expect_no_error(h5fileInfo(ctrl, "barcodesName") <-
                                 "matrix/barcodes")
 
             ctrl.h5$close()
-            expect_warning(show(ctrl), "Link to HDF5 file fails.")
+            expect_message(show(ctrl), "Link to HDF5 file fails.")
         }
     )
 })
@@ -399,11 +401,10 @@ test_that("as.liger methods", {
             colData = data.frame(dataset = factor(rep(c("a", "b"), each = 150)))
         )
         sce$useless <- 1
-        expect_warning(lig <- as.liger(sce), 'Variable name "dataset"')
+        expect_message(lig <- as.liger(sce))
         expect_equal(names(lig), "SCE")
 
-        expect_warning(lig <- as.liger(sce, datasetVar = "dataset"),
-                       'Variable name "dataset"')
+        expect_message(lig <- as.liger(sce, datasetVar = "dataset"))
         expect_true(all.equal(sapply(datasets(lig), ncol), c(a = 150, b = 150)))
     }
 
@@ -420,7 +421,7 @@ test_that("as.liger methods", {
             Seurat::FindVariableFeatures() %>%
             Seurat::ScaleData() %>%
             Seurat::RunPCA()
-        expect_warning(lig <- as.liger(seu))
+        expect_message(lig <- as.liger(seu))
         expect_true(all.equal(sapply(datasets(lig), ncol), c(a = 150, b = 150)))
 
         expect_in(paste0("pca.", 1:10), colnames(cellMeta(lig, as.data.frame = TRUE)))
@@ -434,7 +435,7 @@ test_that("as.ligerDataset methods", {
     expect_is(ld, "ligerDataset")
     ld <- as.ligerDataset(ctrlLD, modal = "atac")
     expect_is(ld, "ligerATACDataset")
-    expect_warning(ld <- as.ligerDataset(ld, modal = "rna"),
+    expect_message(ld <- as.ligerDataset(ld, modal = "rna"),
                    "Will remove information in the following slots when ")
     expect_is(ld, "ligerDataset")
 
diff --git a/tests/testthat/test_preprocessing.R b/tests/testthat/test_preprocessing.R
index 13d7bd0f..befa2bd1 100644
--- a/tests/testthat/test_preprocessing.R
+++ b/tests/testthat/test_preprocessing.R
@@ -150,7 +150,8 @@ test_that("Normalization - in-memory", {
       expect_equal(sum(normPeak(ld)[, i]), 1, tolerance = 1e-6)
     }
 
-    expect_warning(fakeNorm <- normalize(fakePeak, scaleFactor = -1))
+    expect_message(fakeNorm <- normalize(fakePeak, scaleFactor = -1),
+                   "Invalid `scaleFactor` given")
     expect_true(all.equal(colSums(fakeNorm),
                           setNames(rep(1, ncol(fakeNorm)), colnames(fakeNorm))))
 
@@ -183,8 +184,6 @@ test_that("Normalize - on disk", {
 context("Select variable genes")
 test_that("selectGenes", {
     pbmc <- normalize(pbmc, useDatasets = 1)
-    expect_error(selectGenes(pbmc, thresh = 1:3),
-                 "`thresh` has to be a vector of length 2")
     expect_error(selectGenes(pbmc, thresh = 0.1),
                    "Normalized data not available")
     pbmc <- normalize(pbmc, useDatasets = 2)
@@ -196,7 +195,7 @@ test_that("selectGenes", {
     pbmc <- selectGenes(pbmc, combine = "inters")
     expect_equal(length(varFeatures(pbmc)), 161)
 
-    expect_warning(selectGenes(pbmc, thresh = 3),
+    expect_message(selectGenes(pbmc, thresh = 3),
                    "No genes were selected.")
 
     pbmc <- selectGenes(pbmc)
@@ -216,7 +215,7 @@ test_that("selectGenes", {
     pbmc <- selectGenesVST(pbmc, useDataset = "ctrl", n = 50)
     expect_equal(length(varFeatures(pbmc)), 50)
 
-    expect_warning(pbmc <- selectGenesVST(pbmc, useDataset = "ctrl", n = 300,
+    expect_message(pbmc <- selectGenesVST(pbmc, useDataset = "ctrl", n = 300,
                                           useShared = FALSE),
                    "Not all variable features passed are found in datasets")
     expect_equal(length(varFeatures(pbmc)), 266)
diff --git a/tests/testthat/test_subset.R b/tests/testthat/test_subset.R
index dd30b038..c1b1abf5 100644
--- a/tests/testthat/test_subset.R
+++ b/tests/testthat/test_subset.R
@@ -50,12 +50,12 @@ process <- function(object) {
 
 context("subset liger object")
 test_that("subsetLiger", {
-    expect_warning(a <- subsetLiger("a"), "`object` is not a liger obejct")
+    expect_message(a <- subsetLiger("a"), "`object` is not a ")
     expect_identical(a, "a")
     skip_if_not(has_RcppPlanc)
     pbmc <- process(pbmc)
     expect_error(subsetLiger(pbmc, featureIdx = 1:3),
-                 "Feature subscription from liger object")
+                 "Feature subscription from a")
     expect_error(
         expect_warning(subsetLiger(pbmc,
                                    featureIdx = c("fakeGene1", "fakeGene2")),
@@ -79,7 +79,7 @@ test_that("subsetH5LigerDataset", {
             expect_false(isH5Liger(ctrlSmall))
             path <- dirname(h5fileInfo(ctrl, "filename"))
             newName <- file.path(path, "ctrltest.h5.small.h5")
-            expect_warning(
+            expect_message(
                 subsetLigerDataset(ctrl, featureIdx = 1:10, cellIdx = 1:10,
                                    newH5 = TRUE,
                                    filename = newName,
@@ -88,11 +88,11 @@ test_that("subsetH5LigerDataset", {
             )
             expect_true(file.exists(newName))
             unlink(newName)
-            expect_warning(
+            expect_message(
                 rliger2:::subsetH5LigerDatasetToMem(letters),
-                "`object` is not a ligerDataset obejct."
+                "`object` is not a "
             )
-            expect_warning(
+            expect_message(
                 rliger2:::subsetH5LigerDatasetToMem(dataset(pbmc, "ctrl")),
                 "`object` is not HDF5 based."
             )
@@ -101,11 +101,11 @@ test_that("subsetH5LigerDataset", {
             )
             expect_is(valueList, "list")
 
-            expect_warning(
+            expect_message(
                 rliger2:::subsetH5LigerDatasetToH5(letters),
-                "`object` is not a ligerDataset obejct."
+                "`object` is not a"
             )
-            expect_warning(
+            expect_message(
                 rliger2:::subsetH5LigerDatasetToH5(dataset(pbmc, "ctrl")),
                 "`object` is not HDF5 based."
             )
diff --git a/tests/testthat/test_visualization.R b/tests/testthat/test_visualization.R
index 3a9301cc..24518c37 100644
--- a/tests/testthat/test_visualization.R
+++ b/tests/testthat/test_visualization.R
@@ -156,7 +156,7 @@ test_that("Density plot", {
     expect_gg(
         expect_no_warning(plotDensityDimRed(pbmcPlot, splitBy = "dataset",
                                             title = "one")),
-        expect_warning(plotDensityDimRed(pbmcPlot, title = letters[1:3],
+        expect_message(plotDensityDimRed(pbmcPlot, title = letters[1:3],
                                          dotRaster = TRUE),
                        "`title` has length greater than")
     )