git status Renamed package back to rliger

DESCRIPTION

@@ -1,4 +1,4 @@
-Package: rliger2
+Package: rliger
 Version: 1.99.0
 Date: 2023-11-09
 Type: Package

NAMESPACE

@@ -256,4 +256,4 @@ importFrom(methods,show)
 importFrom(rlang,"%||%")
 importFrom(rlang,.data)
 importFrom(utils,.DollarNames)
-useDynLib(rliger2, .registration = TRUE)
+useDynLib(rliger, .registration = TRUE)

NEWS.md

@@ -1,4 +1,4 @@
-## rliger2 1.9.9
+## rliger 1.9.9
 
 - Added `ligerDataset` class for per-dataset information storage, with inheritance for specific modalities
 - Added a number of plotting functions with clear function names and useful functionality
@@ -12,7 +12,7 @@
 Now named by `runINMF()`, `runUINMF()` and `runOnlineINMF()` respectively, and wrapped in 
 `runIntegration()`.
 
-## rliger2 1.0.1
+## rliger 1.0.1
 
 - Allow setting mito pattern in `getMitoProportion()` #271
 - Fix efficiency issue when taking the log of norm.data (e.g. `runWilcoxon`)

R/ATAC.R

@@ -171,7 +171,7 @@ imputeKNN <- function(
 #'     bmmc <- imputeKNN(bmmc, reference = "atac", queries = "rna")
 #'     corr <- linkGenesAndPeaks(
 #'         bmmc, useDataset = "rna",
-#'         pathToCoords = system.file("extdata/hg19_genes.bed", package = "rliger2")
+#'         pathToCoords = system.file("extdata/hg19_genes.bed", package = "rliger")
 #'     )
 #' }
 linkGenesAndPeaks <- function(
@@ -359,12 +359,12 @@ linkGenesAndPeaks <- function(
 #'     bmmc <- imputeKNN(bmmc, reference = "atac", queries = "rna")
 #'     corr <- linkGenesAndPeaks(
 #'         bmmc, useDataset = "rna",
-#'         pathToCoords = system.file("extdata/hg19_genes.bed", package = "rliger2")
+#'         pathToCoords = system.file("extdata/hg19_genes.bed", package = "rliger")
 #'     )
 #'     resultPath <- tempfile()
 #'     exportInteractTrack(
 #'         corrMat = corr,
-#'         pathToCoords = system.file("extdata/hg19_genes.bed", package = "rliger2"),
+#'         pathToCoords = system.file("extdata/hg19_genes.bed", package = "rliger"),
 #'         outputPath = resultPath
 #'     )
 #'     head(read.table(resultPath, skip = 1))
@@ -478,10 +478,10 @@ exportInteractTrack <- function(
 #' current working directory.
 #' @return No return value. A file located at \code{outputPath} will be created.
 #' @name makeInteractTrack-deprecated
-#' @seealso \code{\link{rliger2-deprecated}}, \code{\link{exportInteractTrack}}
+#' @seealso \code{\link{rliger-deprecated}}, \code{\link{exportInteractTrack}}
 NULL
 
-#' @rdname rliger2-deprecated
+#' @rdname rliger-deprecated
 #' @section \code{makeInteractTrack}:
 #' For \code{makeInteractTrack}, use \code{\link{exportInteractTrack}}.
 #' @export

R/RcppExports.R

@@ -2,55 +2,55 @@
 # Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
 
 RunModularityClusteringCpp <- function(SNN, modularityFunction, resolution, algorithm, nRandomStarts, nIterations, randomSeed, printOutput, edgefilename) {
-    .Call(`_rliger2_RunModularityClusteringCpp`, SNN, modularityFunction, resolution, algorithm, nRandomStarts, nIterations, randomSeed, printOutput, edgefilename)
+    .Call(`_rliger_RunModularityClusteringCpp`, SNN, modularityFunction, resolution, algorithm, nRandomStarts, nIterations, randomSeed, printOutput, edgefilename)
 }
 
 colNormalize_dense_cpp <- function(x, L) {
-    .Call(`_rliger2_colNormalize_dense_cpp`, x, L)
+    .Call(`_rliger_colNormalize_dense_cpp`, x, L)
 }
 
 colAggregateMedian_dense_cpp <- function(x, group, n) {
-    .Call(`_rliger2_colAggregateMedian_dense_cpp`, x, group, n)
+    .Call(`_rliger_colAggregateMedian_dense_cpp`, x, group, n)
 }
 
 scaleNotCenter_byRow_rcpp <- function(x) {
-    .Call(`_rliger2_scaleNotCenter_byRow_rcpp`, x)
+    .Call(`_rliger_scaleNotCenter_byRow_rcpp`, x)
 }
 
 scaleNotCenter_byRow_perDataset_rcpp <- function(x, ann, n) {
-    .Call(`_rliger2_scaleNotCenter_byRow_perDataset_rcpp`, x, ann, n)
+    .Call(`_rliger_scaleNotCenter_byRow_perDataset_rcpp`, x, ann, n)
 }
 
 rowVars_sparse_rcpp <- function(x, means) {
-    .Call(`_rliger2_rowVars_sparse_rcpp`, x, means)
+    .Call(`_rliger_rowVars_sparse_rcpp`, x, means)
 }
 
 rowDivide_rcpp <- function(x, v) {
-    .Call(`_rliger2_rowDivide_rcpp`, x, v)
+    .Call(`_rliger_rowDivide_rcpp`, x, v)
 }
 
 sumSquaredDeviations <- function(x, means) {
-    .Call(`_rliger2_sumSquaredDeviations`, x, means)
+    .Call(`_rliger_sumSquaredDeviations`, x, means)
 }
 
 denseZScore <- function(x, m) {
-    .Call(`_rliger2_denseZScore`, x, m)
+    .Call(`_rliger_denseZScore`, x, m)
 }
 
 rowVarsDense <- function(x, m) {
-    .Call(`_rliger2_rowVarsDense`, x, m)
+    .Call(`_rliger_rowVarsDense`, x, m)
 }
 
 SparseRowVarStd <- function(x, mu, sd, vmax) {
-    .Call(`_rliger2_SparseRowVarStd`, x, mu, sd, vmax)
+    .Call(`_rliger_SparseRowVarStd`, x, mu, sd, vmax)
 }
 
 colAggregateSums_sparse <- function(x, group, ngroups) {
-    .Call(`_rliger2_colAggregateSums_sparse`, x, group, ngroups)
+    .Call(`_rliger_colAggregateSums_sparse`, x, group, ngroups)
 }
 
 sample_cpp <- function(x, size) {
-    .Call(`_rliger2_sample_cpp`, x, size)
+    .Call(`_rliger_sample_cpp`, x, size)
 }
 
 #' Fast calculation of feature count matrix
@@ -68,46 +68,46 @@ sample_cpp <- function(x, size) {
 #' samnple <- gene.counts + promoter.counts
 #' }
 makeFeatureMatrix <- function(bedmat, barcodes) {
-    .Call(`_rliger2_makeFeatureMatrix`, bedmat, barcodes)
+    .Call(`_rliger_makeFeatureMatrix`, bedmat, barcodes)
 }
 
 cluster_vote_rcpp <- function(nn_ranked, clusts) {
-    .Call(`_rliger2_cluster_vote_rcpp`, nn_ranked, clusts)
+    .Call(`_rliger_cluster_vote_rcpp`, nn_ranked, clusts)
 }
 
 max_factor_rcpp <- function(H, dims_use, center = FALSE) {
-    .Call(`_rliger2_max_factor_rcpp`, H, dims_use, center)
+    .Call(`_rliger_max_factor_rcpp`, H, dims_use, center)
 }
 
 ComputeSNN <- function(nn_idx, prune) {
-    .Call(`_rliger2_ComputeSNN`, nn_idx, prune)
+    .Call(`_rliger_ComputeSNN`, nn_idx, prune)
 }
 
 WriteEdgeFile <- function(snn, filename, display_progress) {
-    invisible(.Call(`_rliger2_WriteEdgeFile`, snn, filename, display_progress))
+    invisible(.Call(`_rliger_WriteEdgeFile`, snn, filename, display_progress))
 }
 
 DirectSNNToFile <- function(nn_ranked, prune, display_progress, filename) {
-    .Call(`_rliger2_DirectSNNToFile`, nn_ranked, prune, display_progress, filename)
+    .Call(`_rliger_DirectSNNToFile`, nn_ranked, prune, display_progress, filename)
 }
 
 cpp_rank_matrix_dgc <- function(x, p, nrow, ncol) {
-    .Call(`_rliger2_cpp_rank_matrix_dgc`, x, p, nrow, ncol)
+    .Call(`_rliger_cpp_rank_matrix_dgc`, x, p, nrow, ncol)
 }
 
 rowAggregateSum_sparse <- function(X, groups, ngroups) {
-    .Call(`_rliger2_rowAggregateSum_sparse`, X, groups, ngroups)
+    .Call(`_rliger_rowAggregateSum_sparse`, X, groups, ngroups)
 }
 
 colAggregateSum_sparse <- function(X, groups, ngroups) {
-    .Call(`_rliger2_colAggregateSum_sparse`, X, groups, ngroups)
+    .Call(`_rliger_colAggregateSum_sparse`, X, groups, ngroups)
 }
 
 colNNZAggr_sparse <- function(X, groups, ngroups) {
-    .Call(`_rliger2_colNNZAggr_sparse`, X, groups, ngroups)
+    .Call(`_rliger_colNNZAggr_sparse`, X, groups, ngroups)
 }
 
 rowNNZAggr_sparse <- function(X, groups, ngroups) {
-    .Call(`_rliger2_rowNNZAggr_sparse`, X, groups, ngroups)
+    .Call(`_rliger_rowNNZAggr_sparse`, X, groups, ngroups)
 }
 

R/aaa.R

@@ -3,7 +3,7 @@
 #' @importFrom rlang .data %||%
 #' @importFrom methods new show
 #' @importFrom utils .DollarNames
-#' @useDynLib rliger2, .registration = TRUE
+#' @useDynLib rliger, .registration = TRUE
 NULL
 
 #' @importFrom magrittr %>%
@@ -75,6 +75,6 @@ scPalette <- c('#E41A1C', '#377EB8', '#4DAF4A', '#FFCF00', '#aa47b9', '#e67c14',
 }
 
 .onUnload <- function(libpath) {
-    library.dynam.unload("rliger2", libpath)
+    library.dynam.unload("rliger", libpath)
     return(invisible(NULL))
 }

R/cINMF.R

@@ -371,10 +371,10 @@ runCINMF.Seurat <- function(
         Vs[[i]] <- colNormalize_dense_cpp(V, L = 1)
     }
     # Vs <- lapply(seq_along(object), function(i) {
-    #     matrix(runif(nrow(W) * k, 0, 2), nrow(W), k)
+    #     matrix(stats::runif(nrow(W) * k, 0, 2), nrow(W), k)
     # })
     Hs <- lapply(seq_along(object), function(i) {
-        matrix(runif(ncol(object[[i]]) * k, 0, 2), ncol(object[[i]]), k)
+        matrix(stats::runif(ncol(object[[i]]) * k, 0, 2), ncol(object[[i]]), k)
     })
 
     if (isTRUE(verbose)) cli::cli_process_done(id = cliID)

R/classes.R

@@ -174,7 +174,7 @@ setValidity("ligerDataset", .valid.ligerDataset)
 #' 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
+#' @slot version Record of version of rliger package
 #' @importClassesFrom S4Vectors DataFrame
 #' @importFrom ggplot2 fortify
 liger <- setClass(
@@ -191,7 +191,7 @@ liger <- setClass(
     ),
     methods::prototype(
         cellMeta = methods::new("DFrame"),
-        version = utils::packageVersion("rliger2")
+        version = utils::packageVersion("rliger")
     )
 )
 
@@ -207,7 +207,9 @@ liger <- setClass(
     if (!is.factor(x@cellMeta$dataset)) {
         return("\"dataset\" variable in cellMeta is not a factor")
     }
-    if (!identical(x@cellMeta$dataset, names(x@datasets))) {
+    ds_cm <- levels(droplevels(x@cellMeta[["dataset"]]))
+    ds_ds <- names(x@datasets)
+    if (!identical(ds_cm, ds_ds)) {
         return("`levels(x$dataset)` does not match `names(x)`.")
     }
     return(NULL)
@@ -307,7 +309,7 @@ setClassUnion("POSIXct_or_NULL", c("POSIXct", "NULL"))
 #' @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")}.
+#' \code{packageVersion("rliger")}.
 #' @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

R/clustering.R

@@ -156,10 +156,10 @@ runCluster <- function(
 #' \code{"louvain_cluster"} variable in \code{cellMeta} slot. Can be fetched
 #' with \code{object$louvain_cluster}
 #' @name louvainCluster-deprecated
-#' @seealso \code{\link{rliger2-deprecated}}
+#' @seealso \code{\link{rliger-deprecated}}
 NULL
 
-#' @rdname rliger2-deprecated
+#' @rdname rliger-deprecated
 #' @section \code{louvainCluster}:
 #' For \code{louvainCluster}, use \code{\link{runCluster}(method = "louvain")}
 #' as the replacement, while \code{\link{runCluster}} with default

R/deprecated.R

@@ -1,9 +1,9 @@
-#' @title Deprecated functions in package \pkg{rliger2}.
+#' @title Deprecated functions in package \pkg{rliger}.
 #' @description The functions listed below are deprecated and will be defunct in
 #'   the near future. When possible, alternative functions with similar
 #'   functionality or a replacement are also mentioned. Help pages for
 #'   deprecated functions are available at \code{help("<function>-deprecated")}.
-#' @name rliger2-deprecated
+#' @name rliger-deprecated
 #' @keywords internal
 NULL
 
@@ -237,7 +237,7 @@ SLMCluster <-
       # NULL random.seed disallowed for this program.
       random.seed = 0
     }
-    liger.dir <- "."#system.file(package = "rliger2")
+    liger.dir <- "."#system.file(package = "rliger")
     ModularityJarFile <-
       paste0(liger.dir, "/java/ModularityOptimizer.jar")
     command <-

R/embedding.R

@@ -95,15 +95,12 @@ runUMAP <- function(
 #' By default \code{\link[Rtsne]{Rtsne}} (Barnes-Hut implementation of t-SNE)
 #' method is invoked, while alternative "fftRtsne" method (FFT-accelerated
 #' Interpolation-based t-SNE, using Kluger Lab implementation) is also
-#' supported.
+#' supported. For very large datasets, it is recommended to use
+#' \code{method = "fftRtsne"} due to its efficiency and scalability.
 #'
-#' In order to run fftRtsne (recommended for large datasets), FIt-SNE must be
-#' installed as instructed in detailed
-#' \href{https://github.com/KlugerLab/FIt-SNE}{here}. Include the path to the
-#' cloned FIt-SNE directory as the \code{fitsne.path} parameter, though this is
-#' only necessary for the first call to run \code{runTSNE}. For more detailed
-#' FIt-SNE installation instructions, see the liger repo
-#' \href{https://github.com/welch-lab/liger#readme}{README}.
+#' Extra external installation steps are required for using "fftRtsne" method.
+#' Please consult
+#' \href{https://welch-lab.github.io/liger/articles/installation.html}{detailed guide}.
 #' @param object \linkS4class{liger} object with factorization results.
 #' @param useRaw Whether to use un-aligned cell factor loadings (\eqn{H}
 #' matrices). Default \code{NULL} search for quantile-normalized loadings first

R/h5Utility.R

@@ -179,7 +179,7 @@ safeH5Create <- function(object,
 #' @rdname restoreH5Liger
 #' @export
 #' @examples
-#' h5Path <- system.file("extdata/ctrl.h5", package = "rliger2")
+#' h5Path <- system.file("extdata/ctrl.h5", package = "rliger")
 #' lig <- createLiger(list(ctrl = h5Path))
 #' # Now it is actually an invalid object! which is equivalent to what users
 #' # will get with `saveRDS(lig, "object.rds"); lig <- readRDS("object.rds")``

R/import.R

@@ -46,7 +46,7 @@
 #' pbmc1 <- createLiger(list(ctrl = ctrl.raw, stim = stim.raw))
 #'
 #' # Create from H5 files
-#' h5Path <- system.file("extdata/ctrl.h5", package = "rliger2")
+#' h5Path <- system.file("extdata/ctrl.h5", package = "rliger")
 #' print(h5Path)
 #' lig <- createLiger(list(ctrl = h5Path))
 #'
@@ -359,7 +359,7 @@ createH5LigerDataset <- function(
 #' pbmc <- readLiger(tempPath)
 #'
 #' # Save and read H5-based liger object
-#' h5Path <- system.file("extdata/ctrl.h5", package = "rliger2")
+#' h5Path <- system.file("extdata/ctrl.h5", package = "rliger")
 #' lig <- createLiger(list(ctrl = h5Path))
 #' tempPath <- tempfile(fileext = ".rds")
 #' saveRDS(lig, tempPath)
@@ -381,7 +381,7 @@ readLiger <- function(
     cli::cli_alert_info("Older version ({.val {ver}}) of {.cls liger} object detected.")
     if (isTRUE(update)) {
         cli::cli_alert_info(
-            "Updating the object structure to make it compatible with current version {.val {utils::packageVersion('rliger2')}}"
+            "Updating the object structure to make it compatible with current version {.val {utils::packageVersion('rliger')}}"
         )
         return(convertOldLiger(obj, dimredName = dimredName,
                                clusterName = clusterName,

R/integration.R

@@ -466,10 +466,10 @@ runINMF.Seurat <- function(
 #' @param ... Arguments passed to other methods
 #' @return \code{liger} object with H, W, and V slots set.
 #' @name optimizeALS-deprecated
-#' @seealso \code{\link{rliger2-deprecated}}
+#' @seealso \code{\link{rliger-deprecated}}
 NULL
 
-#' @rdname rliger2-deprecated
+#' @rdname rliger-deprecated
 #' @section \code{optimizeALS}:
 #' For \code{optimizeALS}, use \code{\link{runIntegration}} or
 #' \code{\link{runINMF}}. For the case of
@@ -981,7 +981,7 @@ runOnlineINMF.Seurat <- function(
 #' @name online_iNMF-deprecated
 NULL
 
-#' @rdname rliger2-deprecated
+#' @rdname rliger-deprecated
 #' @section \code{online_iNMF}:
 #' For \code{online_iNMF}, use \code{\link{runIntegration}} with
 #' \code{method = "online"} or \code{\link{runOnlineINMF}}.
@@ -1540,10 +1540,10 @@ quantileNorm.Seurat <- function(
 #' @param rand.seed Random seed to allow reproducible results (default 1)
 #' @return \code{liger} object with 'H.norm' and 'clusters' slot set.
 #' @name quantile_norm-deprecated
-#' @seealso \code{\link{rliger2-deprecated}}
+#' @seealso \code{\link{rliger-deprecated}}
 NULL
 
-#' @rdname rliger2-deprecated
+#' @rdname rliger-deprecated
 #' @section \code{quantile_norm}:
 #' For \code{quantile_norm}, use \code{\link{quantileNorm}}.
 #' @export