From 4e708620cbe6fe3ffe962b434f19db7f40afd4e1 Mon Sep 17 00:00:00 2001 From: Yichen Wang Date: Wed, 13 Mar 2024 14:15:06 -0400 Subject: [PATCH] git status Renamed package back to rliger --- DESCRIPTION | 2 +- NAMESPACE | 2 +- NEWS.md | 4 +- R/ATAC.R | 10 +- R/RcppExports.R | 48 ++++----- R/aaa.R | 4 +- R/cINMF.R | 4 +- R/classes.R | 10 +- R/clustering.R | 4 +- R/deprecated.R | 6 +- R/embedding.R | 13 +-- R/h5Utility.R | 2 +- R/import.R | 6 +- R/integration.R | 10 +- R/liger-methods.R | 19 +++- R/ligerCommand_relates.R | 4 +- R/util.R | 78 ++++++++++++++ data/bmmc.rda | Bin 50596 -> 50654 bytes data/pbmc.rda | Bin 67112 -> 67126 bytes data/pbmcPlot.rda | Bin 167815 -> 167845 bytes inst/include/rliger.h | 2 - man/createLiger.Rd | 2 +- man/exportInteractTrack.Rd | 4 +- man/liger-class.Rd | 12 ++- man/ligerCommand-class.Rd | 2 +- man/linkGenesAndPeaks.Rd | 2 +- man/louvainCluster-deprecated.Rd | 2 +- man/makeInteractTrack-deprecated.Rd | 2 +- man/optimizeALS-deprecated.Rd | 2 +- man/quantile_norm-deprecated.Rd | 2 +- man/readLiger.Rd | 2 +- man/restoreH5Liger.Rd | 2 +- ...er2-deprecated.Rd => rliger-deprecated.Rd} | 4 +- man/runTSNE.Rd | 13 +-- src/RcppExports.cpp | 98 +++++++++--------- tests/testthat.R | 4 +- tests/testthat/test_downstream.R | 8 +- tests/testthat/test_factorization.R | 8 +- tests/testthat/test_object.R | 10 +- tests/testthat/test_preprocessing.R | 6 +- tests/testthat/test_subset.R | 20 ++-- tests/testthat/test_visualization.R | 6 +- .../articles/Integrating_multi_scRNA_data.rmd | 2 +- .../Integrating_scRNA_and_scATAC_data.Rmd | 4 +- vignettes/articles/SNAREseq_walkthrough.Rmd | 2 +- vignettes/articles/STARmap_dropviz_vig.Rmd | 2 +- vignettes/articles/UINMF_vignette.Rmd | 2 +- vignettes/articles/cross_species_vig.Rmd | 2 +- vignettes/articles/installation.Rmd | 52 ++++++---- vignettes/articles/liger_object.Rmd | 2 +- vignettes/articles/liger_with_seurat.Rmd | 4 +- vignettes/articles/online_iNMF_tutorial.Rmd | 2 +- vignettes/articles/rna_methylation.Rmd | 2 +- 53 files changed, 305 insertions(+), 210 deletions(-) delete mode 100644 inst/include/rliger.h rename man/{rliger2-deprecated.Rd => rliger-deprecated.Rd} (96%) diff --git a/DESCRIPTION b/DESCRIPTION index 5c4b348a..e5e0e727 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,4 +1,4 @@ -Package: rliger2 +Package: rliger Version: 1.99.0 Date: 2023-11-09 Type: Package diff --git a/NAMESPACE b/NAMESPACE index d23e852a..d429bad1 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -256,4 +256,4 @@ importFrom(methods,show) importFrom(rlang,"%||%") importFrom(rlang,.data) importFrom(utils,.DollarNames) -useDynLib(rliger2, .registration = TRUE) +useDynLib(rliger, .registration = TRUE) diff --git a/NEWS.md b/NEWS.md index f3306a50..349da770 100644 --- a/NEWS.md +++ b/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`) diff --git a/R/ATAC.R b/R/ATAC.R index 5125c961..e8c90eae 100644 --- a/R/ATAC.R +++ b/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 diff --git a/R/RcppExports.R b/R/RcppExports.R index ba44a5b8..39a4a078 100644 --- a/R/RcppExports.R +++ b/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) } diff --git a/R/aaa.R b/R/aaa.R index 8f818ce5..a407ac10 100644 --- a/R/aaa.R +++ b/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)) } diff --git a/R/cINMF.R b/R/cINMF.R index edb1de91..091aea50 100644 --- a/R/cINMF.R +++ b/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) diff --git a/R/classes.R b/R/classes.R index b2754bf4..ce195d54 100644 --- a/R/classes.R +++ b/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$dataset)` does not match `names(x)`.") } return(NULL) @@ -307,7 +309,7 @@ setClassUnion("POSIXct_or_NULL", c("POSIXct", "NULL")) #' @slot objSummary List of attributes of the \linkS4class{liger} object as a #' snapshot when command is operated. #' @slot ligerVersion Character string converted from -#' \code{packageVersion("rliger2")}. +#' \code{packageVersion("rliger")}. #' @slot dependencyVersion Named character vector of version number, if any #' dependency library has a chance to be included by the function. A #' dependency might only be invoked under certain conditions, such as using diff --git a/R/clustering.R b/R/clustering.R index d550205b..dd1bb9ee 100644 --- a/R/clustering.R +++ b/R/clustering.R @@ -156,10 +156,10 @@ runCluster <- function( #' \code{"louvain_cluster"} variable in \code{cellMeta} slot. Can be fetched #' with \code{object$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 diff --git a/R/deprecated.R b/R/deprecated.R index 0a2f897e..9647ac42 100755 --- a/R/deprecated.R +++ b/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("-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 <- diff --git a/R/embedding.R b/R/embedding.R index d03d64c8..3744496f 100644 --- a/R/embedding.R +++ b/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 diff --git a/R/h5Utility.R b/R/h5Utility.R index e2a8d861..161ea944 100644 --- a/R/h5Utility.R +++ b/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")`` diff --git a/R/import.R b/R/import.R index 0a1e9f22..251c548a 100644 --- a/R/import.R +++ b/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, diff --git a/R/integration.R b/R/integration.R index 9e817ac7..dee002f6 100644 --- a/R/integration.R +++ b/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 diff --git a/R/liger-methods.R b/R/liger-methods.R index f20d60ad..7cbc7d42 100644 --- a/R/liger-methods.R +++ b/R/liger-methods.R @@ -59,7 +59,7 @@ is.newLiger <- function(object) { #' names(pbmcPlot) #' length(pbmcPlot) #' -#' # rliger2 generics +#' # rliger generics #' ## Retrieving dataset(s), replacement methods available #' datasets(pbmcPlot) #' dataset(pbmcPlot, "ctrl") @@ -79,7 +79,9 @@ is.newLiger <- function(object) { #' commands(pbmcPlot, funcName = "scaleNotCenter") #' #' # S3 methods -#' c(pbmcPlot, pbmcPlot) +#' pbmcPlot2 <- pbmcPlot +#' names(pbmcPlot2) <- paste0(names(pbmcPlot), 2) +#' c(pbmcPlot, pbmcPlot2) #' #' library(ggplot2) #' ggplot(pbmcPlot, aes(x = UMAP.1, y = UMAP.2)) + geom_point() @@ -445,6 +447,7 @@ length.liger <- function(x) { #' @rdname liger-class #' @export +#' @param use.names Whether returned vector should be named with dataset names. #' @method lengths liger lengths.liger <- function(x, use.names = TRUE) { .checkObjVersion(x) @@ -963,7 +966,6 @@ setMethod("getH5File", #' Set cell metadata variable #' @rdname liger-class -#' @param x A \linkS4class{liger} object #' @param i Name or numeric index of cell meta variable to be replaced #' @param value Metadata value to be inserted #' @return Input liger object updated with replaced/new variable in @@ -987,7 +989,7 @@ setMethod("getH5File", ) } x@cellMeta[[i]] <- value - validObject(x) + methods::validObject(x) return(x) } @@ -1319,6 +1321,13 @@ c.liger <- function(...) { objList <- list(...) if (any(sapply(objList, function(obj) !inherits(obj, "liger")))) cli::cli_abort("Can only combine {.cls liger} objects with {.fn c} method for now.") + allNames <- unlist(lapply(objList, names)) + if (any(duplicated(allNames))) + cli::cli_abort( + c("x" = "Cannot combine {.cls liger} objects with duplicated dataset names.", + "i" = "Dataset names of an individual {.cls liger} object can be modified with {.code names(x) <- value}.") + ) + objList[[length(objList)]] <- recordCommand(objList[[length(objList)]]) allDatasets <- list() allCellMeta <- NULL @@ -1333,7 +1342,7 @@ c.liger <- function(...) { } methods::new("liger", datasets = allDatasets, cellMeta = allCellMeta, varFeatures = varFeatures, commands = allCommands, - version = utils::packageVersion("rliger2")) + version = utils::packageVersion("rliger")) } diff --git a/R/ligerCommand_relates.R b/R/ligerCommand_relates.R index f79652b7..45955751 100644 --- a/R/ligerCommand_relates.R +++ b/R/ligerCommand_relates.R @@ -62,7 +62,7 @@ recordCommand <- function( "ligerCommand", funcName = funcName, objSummary = objSummary, parameters = args, - ligerVersion = as.character(utils::packageVersion("rliger2")), + ligerVersion = as.character(utils::packageVersion("rliger")), dependencyVersion = dependVer ) # Do a hash tag to see if an identical operation has been done before @@ -197,7 +197,7 @@ commandDiff <- function(object, cmd1, cmd2) { } # Versions if (x@ligerVersion != y@ligerVersion) - msg <- c(msg, paste0("\"rliger2\" versions differ: ", x@ligerVersion, + msg <- c(msg, paste0("\"rliger\" versions differ: ", x@ligerVersion, " VS ", y@ligerVersion)) if (!identical(x@dependencyVersion, y@dependencyVersion)) msg <- c(msg, paste0("Dependency versions differ. ", diff --git a/R/util.R b/R/util.R index 6e6e42ea..d7f54d10 100644 --- a/R/util.R +++ b/R/util.R @@ -618,3 +618,81 @@ searchH <- function(object, useRaw = NULL) { } return(list(H = H, useRaw = useRaw)) } + +# Internal development use only +# use when you have objects created when this package was named by `rliger2` +# now we rename the package back to `rliger` and you'll need to have the objects +# compatible with "new" package name. +rliger2_to_rliger_namespace <- function(obj) { + if (inherits(obj, "liger")) { + new <- methods::new( + "liger", + datasets = obj@datasets, + cellMeta = obj@cellMeta, + varFeatures = obj@varFeatures, + W = obj@W, + H.norm = obj@H.norm, + uns = obj@uns, + commands = obj@commands, + version = obj@version + ) + } + for (i in seq_along(obj)) { + ld <- obj@datasets[[i]] + basics <- list( + rawData = ld@rawData, + normData = ld@normData, + scaleData = ld@scaleData, + H = ld@H, + V = ld@V, + A = ld@A, + B = ld@B, + varUnsharedFeatures = ld@varUnsharedFeatures, + scaleUnsharedData = ld@scaleUnsharedData, + U = ld@U, + h5fileInfo = ld@h5fileInfo, + featureMeta = ld@featureMeta, + colnames = ld@colnames, + rownames = ld@rownames + ) + if (inherits(ld, "ligerATACDataset")) { + basics <- c(basics, list( + Class = "ligerATACDataset", + rawPeak = ld@rawPeak, + normPeak = ld@normPeak + )) + } else if (inherits(ld, "ligerRNADataset")) { + basics <- c(basics, list( + Class = "ligerRNADataset" + )) + } else if (inherits(ld, "ligerMethDataset")) { + basics <- c(basics, list( + Class = "ligerMethDataset" + )) + } else if (inherits(ld, "ligerSpatialDataset")) { + basics <- c(basics, list( + Class = "ligerSpatialDataset", + coordinate = ld@coordinate + )) + } else { + basics <- c(basics, list( + Class = "ligerDataset" + )) + } + new@datasets[[i]] <- do.call("new", basics) + } + for (i in seq_along(new@commands)) { + cmd <- new@commands[[i]] + new@commands[[i]] <- methods::new( + "ligerCommand", + funcName = cmd@funcName, + time = cmd@time, + call = cmd@call, + parameters = cmd@parameters, + objSummary = cmd@objSummary, + ligerVersion = cmd@ligerVersion, + dependencyVersion = cmd@dependencyVersion + ) + } + new +} diff --git a/data/bmmc.rda b/data/bmmc.rda index 4c8d0054b4a74bddb73547976eeae7e3422c3ecc..a35ec2b5643443ced313197fa394681da0117c78 100644 GIT binary patch delta 49867 zcmZ6x1yG$$&@Ol&K+vEEcZY*J1PGAe?(XjH^1?xaySuv+EVw%acL*LFf@}8sckkV; zyFFFUboaPaP0#ccM}63e`hX>-W5v%ds!gk^eJau11Uvr=NWi23cF4Ma3%*zcH8#PD ztAA+utlh#h4pPftF1EI>Y5ai@{0Ag->Dus<5X4X#2!c`L0{urH3&=nAg8a^G6jnHr zD+2{;2yraznb|Qym1FM4&qHaJ_3U+|G2|`E;aiYfxUE3rcE4Q{M@)sx2s49TdXs*VV*&H4(|ar$7*F;C~H?tATJt%6dUgAkemc zBQz6a1p@W{rzZx1I9L9Qg|Jmj?thZS)@^O#TO;_Q3x@sN;X|((^y~ zbm{OvivKCbS}z15_U!$S0|Ea7{~y7U|8E{45CqEqFZ@^OAOBy-|6Bb(vIqzSkMlqH ze-MsR{Qr{w-y|?Oj*=4m|B>rI0agjbq_kC{0un_Alz=fm|P+gW|Z{veW`X=2Pt{y`!v_^TRW*)A*tCWiz@ z3<0<5HMhjVnorT1>YQK^H>o_i*;qtA{;#mikAmw>5AzO~2s z>!YZ4BaaE?nkB3BVrVoM%%p=_3vpNnN}nq+Vns$2S`mWeXrUZ%Tnl#yv|(SZx#kyq 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zkARFH+DAFJTVR*m8|#YUTr -#define NDEBUG 1 \ No newline at end of file diff --git a/man/createLiger.Rd b/man/createLiger.Rd index 1ae3dbb0..80a92882 100644 --- a/man/createLiger.Rd +++ b/man/createLiger.Rd @@ -87,7 +87,7 @@ stim.raw <- rawData(pbmc, "stim") 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)) diff --git a/man/exportInteractTrack.Rd b/man/exportInteractTrack.Rd index 43cc98a9..247a648b 100644 --- a/man/exportInteractTrack.Rd +++ b/man/exportInteractTrack.Rd @@ -44,12 +44,12 @@ if (requireNamespace("RcppPlanc", quietly = TRUE)) { 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)) diff --git a/man/liger-class.Rd b/man/liger-class.Rd index f07581c1..224589a1 100644 --- a/man/liger-class.Rd +++ b/man/liger-class.Rd @@ -331,6 +331,8 @@ name of a new variable to store.} \item{funcName, arg}{See Command records section.} +\item{use.names}{Whether returned vector should be named with dataset names.} + \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 @@ -347,8 +349,6 @@ 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{x}{A \linkS4class{liger} object} } \value{ See detailed sections for explanetion. @@ -401,7 +401,7 @@ accordingly.} \item{\code{uns}}{List for unstructured meta-info of analyses or presets.} -\item{\code{version}}{Record of version of rliger2 package} +\item{\code{version}}{Record of version of rliger package} }} \section{Dataset access}{ @@ -570,7 +570,7 @@ pbmcPlot[varFeatures(pbmcPlot)[1:10], 1:10] names(pbmcPlot) length(pbmcPlot) -# rliger2 generics +# rliger generics ## Retrieving dataset(s), replacement methods available datasets(pbmcPlot) dataset(pbmcPlot, "ctrl") @@ -590,7 +590,9 @@ commands(pbmcPlot) commands(pbmcPlot, funcName = "scaleNotCenter") # S3 methods -c(pbmcPlot, pbmcPlot) +pbmcPlot2 <- pbmcPlot +names(pbmcPlot2) <- paste0(names(pbmcPlot), 2) +c(pbmcPlot, pbmcPlot2) library(ggplot2) ggplot(pbmcPlot, aes(x = UMAP.1, y = UMAP.2)) + geom_point() diff --git a/man/ligerCommand-class.Rd b/man/ligerCommand-class.Rd index fdc46da7..437b71cf 100644 --- a/man/ligerCommand-class.Rd +++ b/man/ligerCommand-class.Rd @@ -31,7 +31,7 @@ Large object are summarized to short string.} snapshot when command is operated.} \item{\code{ligerVersion}}{Character string converted from -\code{packageVersion("rliger2")}.} +\code{packageVersion("rliger")}.} \item{\code{dependencyVersion}}{Named character vector of version number, if any dependency library has a chance to be included by the function. A diff --git a/man/linkGenesAndPeaks.Rd b/man/linkGenesAndPeaks.Rd index 18793760..9ea2b275 100644 --- a/man/linkGenesAndPeaks.Rd +++ b/man/linkGenesAndPeaks.Rd @@ -66,7 +66,7 @@ if (requireNamespace("RcppPlanc", quietly = TRUE)) { 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") ) } } diff --git a/man/louvainCluster-deprecated.Rd b/man/louvainCluster-deprecated.Rd index fe9dbbfe..0329eeba 100644 --- a/man/louvainCluster-deprecated.Rd +++ b/man/louvainCluster-deprecated.Rd @@ -43,5 +43,5 @@ algorithm for community detection, which is widely used in single-cell analysis and excels at merging small clusters into broad cell classes. } \seealso{ -\code{\link{rliger2-deprecated}} +\code{\link{rliger-deprecated}} } diff --git a/man/makeInteractTrack-deprecated.Rd b/man/makeInteractTrack-deprecated.Rd index 1ef94db8..9b6de3a2 100644 --- a/man/makeInteractTrack-deprecated.Rd +++ b/man/makeInteractTrack-deprecated.Rd @@ -26,5 +26,5 @@ which is compatible with \href{https://genome.ucsc.edu/cgi-bin/hgCustom}{UCSC Genome Browser}. } \seealso{ -\code{\link{rliger2-deprecated}}, \code{\link{exportInteractTrack}} +\code{\link{rliger-deprecated}}, \code{\link{exportInteractTrack}} } diff --git a/man/optimizeALS-deprecated.Rd b/man/optimizeALS-deprecated.Rd index 640fb9df..9cbf2862 100644 --- a/man/optimizeALS-deprecated.Rd +++ b/man/optimizeALS-deprecated.Rd @@ -62,5 +62,5 @@ as it represents the shared components of the metagenes across datasets. The V matrices represent the dataset-specific components of the metagenes. } \seealso{ -\code{\link{rliger2-deprecated}} +\code{\link{rliger-deprecated}} } diff --git a/man/quantile_norm-deprecated.Rd b/man/quantile_norm-deprecated.Rd index 998e0f23..ea4f0943 100644 --- a/man/quantile_norm-deprecated.Rd +++ b/man/quantile_norm-deprecated.Rd @@ -57,5 +57,5 @@ reference dataset). These aligned factor loadings are combined into a single matrix and returned as H.norm. } \seealso{ -\code{\link{rliger2-deprecated}} +\code{\link{rliger-deprecated}} } diff --git a/man/readLiger.Rd b/man/readLiger.Rd index b78aac89..1c7af7b1 100644 --- a/man/readLiger.Rd +++ b/man/readLiger.Rd @@ -48,7 +48,7 @@ saveRDS(pbmc, tempPath) 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) diff --git a/man/restoreH5Liger.Rd b/man/restoreH5Liger.Rd index 9de91907..1d8112e7 100644 --- a/man/restoreH5Liger.Rd +++ b/man/restoreH5Liger.Rd @@ -33,7 +33,7 @@ the restoration of those links so that new analyses can be carried out. for data structure. } \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")`` diff --git a/man/rliger2-deprecated.Rd b/man/rliger-deprecated.Rd similarity index 96% rename from man/rliger2-deprecated.Rd rename to man/rliger-deprecated.Rd index 82164ca4..c16e78b7 100644 --- a/man/rliger2-deprecated.Rd +++ b/man/rliger-deprecated.Rd @@ -4,11 +4,11 @@ \name{makeInteractTrack} \alias{makeInteractTrack} \alias{louvainCluster} -\alias{rliger2-deprecated} +\alias{rliger-deprecated} \alias{optimizeALS} \alias{online_iNMF} \alias{quantile_norm} -\title{Deprecated functions in package \pkg{rliger2}.} +\title{Deprecated functions in package \pkg{rliger}.} \usage{ makeInteractTrack( corr.mat, diff --git a/man/runTSNE.Rd b/man/runTSNE.Rd index 1d25bfcb..750a2c73 100644 --- a/man/runTSNE.Rd +++ b/man/runTSNE.Rd @@ -75,15 +75,12 @@ Runs t-SNE on the quantile normalized cell factors (result from 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}. } \examples{ pbmc <- runTSNE(pbmcPlot) diff --git a/src/RcppExports.cpp b/src/RcppExports.cpp index 59dfaa10..aab8484c 100644 --- a/src/RcppExports.cpp +++ b/src/RcppExports.cpp @@ -13,7 +13,7 @@ Rcpp::Rostream& Rcpp::Rcerr = Rcpp::Rcpp_cerr_get(); // RunModularityClusteringCpp IntegerVector RunModularityClusteringCpp(arma::sp_mat SNN, int modularityFunction, double resolution, int algorithm, int nRandomStarts, int nIterations, int randomSeed, bool printOutput, std::string edgefilename); -RcppExport SEXP _rliger2_RunModularityClusteringCpp(SEXP SNNSEXP, SEXP modularityFunctionSEXP, SEXP resolutionSEXP, SEXP algorithmSEXP, SEXP nRandomStartsSEXP, SEXP nIterationsSEXP, SEXP randomSeedSEXP, SEXP printOutputSEXP, SEXP edgefilenameSEXP) { +RcppExport SEXP _rliger_RunModularityClusteringCpp(SEXP SNNSEXP, SEXP modularityFunctionSEXP, SEXP resolutionSEXP, SEXP algorithmSEXP, SEXP nRandomStartsSEXP, SEXP nIterationsSEXP, SEXP randomSeedSEXP, SEXP printOutputSEXP, SEXP edgefilenameSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -32,7 +32,7 @@ END_RCPP } // colNormalize_dense_cpp arma::mat colNormalize_dense_cpp(arma::mat& x, const arma::uword L); -RcppExport SEXP _rliger2_colNormalize_dense_cpp(SEXP xSEXP, SEXP LSEXP) { +RcppExport SEXP _rliger_colNormalize_dense_cpp(SEXP xSEXP, SEXP LSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -44,7 +44,7 @@ END_RCPP } // colAggregateMedian_dense_cpp arma::mat colAggregateMedian_dense_cpp(const arma::mat& x, const arma::uvec& group, const arma::uword n); -RcppExport SEXP _rliger2_colAggregateMedian_dense_cpp(SEXP xSEXP, SEXP groupSEXP, SEXP nSEXP) { +RcppExport SEXP _rliger_colAggregateMedian_dense_cpp(SEXP xSEXP, SEXP groupSEXP, SEXP nSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -57,7 +57,7 @@ END_RCPP } // scaleNotCenter_byRow_rcpp arma::sp_mat scaleNotCenter_byRow_rcpp(arma::sp_mat x); -RcppExport SEXP _rliger2_scaleNotCenter_byRow_rcpp(SEXP xSEXP) { +RcppExport SEXP _rliger_scaleNotCenter_byRow_rcpp(SEXP xSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -68,7 +68,7 @@ END_RCPP } // scaleNotCenter_byRow_perDataset_rcpp arma::sp_mat scaleNotCenter_byRow_perDataset_rcpp(arma::sp_mat x, const arma::uvec& ann, const arma::uword& n); -RcppExport SEXP _rliger2_scaleNotCenter_byRow_perDataset_rcpp(SEXP xSEXP, SEXP annSEXP, SEXP nSEXP) { +RcppExport SEXP _rliger_scaleNotCenter_byRow_perDataset_rcpp(SEXP xSEXP, SEXP annSEXP, SEXP nSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -81,7 +81,7 @@ END_RCPP } // rowVars_sparse_rcpp NumericVector rowVars_sparse_rcpp(const arma::sp_mat& x, const NumericVector& means); -RcppExport SEXP _rliger2_rowVars_sparse_rcpp(SEXP xSEXP, SEXP meansSEXP) { +RcppExport SEXP _rliger_rowVars_sparse_rcpp(SEXP xSEXP, SEXP meansSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -93,7 +93,7 @@ END_RCPP } // rowDivide_rcpp arma::sp_mat rowDivide_rcpp(arma::sp_mat x, const arma::vec& v); -RcppExport SEXP _rliger2_rowDivide_rcpp(SEXP xSEXP, SEXP vSEXP) { +RcppExport SEXP _rliger_rowDivide_rcpp(SEXP xSEXP, SEXP vSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -105,7 +105,7 @@ END_RCPP } // sumSquaredDeviations NumericVector sumSquaredDeviations(arma::sp_mat x, NumericVector means); -RcppExport SEXP _rliger2_sumSquaredDeviations(SEXP xSEXP, SEXP meansSEXP) { +RcppExport SEXP _rliger_sumSquaredDeviations(SEXP xSEXP, SEXP meansSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -117,7 +117,7 @@ END_RCPP } // denseZScore NumericMatrix denseZScore(NumericMatrix& x, NumericVector m); -RcppExport SEXP _rliger2_denseZScore(SEXP xSEXP, SEXP mSEXP) { +RcppExport SEXP _rliger_denseZScore(SEXP xSEXP, SEXP mSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -129,7 +129,7 @@ END_RCPP } // rowVarsDense NumericVector rowVarsDense(arma::mat x, arma::vec m); -RcppExport SEXP _rliger2_rowVarsDense(SEXP xSEXP, SEXP mSEXP) { +RcppExport SEXP _rliger_rowVarsDense(SEXP xSEXP, SEXP mSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -141,7 +141,7 @@ END_RCPP } // SparseRowVarStd NumericVector SparseRowVarStd(arma::sp_mat x, NumericVector mu, NumericVector sd, double vmax); -RcppExport SEXP _rliger2_SparseRowVarStd(SEXP xSEXP, SEXP muSEXP, SEXP sdSEXP, SEXP vmaxSEXP) { +RcppExport SEXP _rliger_SparseRowVarStd(SEXP xSEXP, SEXP muSEXP, SEXP sdSEXP, SEXP vmaxSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::traits::input_parameter< arma::sp_mat >::type x(xSEXP); @@ -154,7 +154,7 @@ END_RCPP } // colAggregateSums_sparse arma::sp_mat colAggregateSums_sparse(const arma::sp_mat& x, const arma::uvec& group, const arma::uword& ngroups); -RcppExport SEXP _rliger2_colAggregateSums_sparse(SEXP xSEXP, SEXP groupSEXP, SEXP ngroupsSEXP) { +RcppExport SEXP _rliger_colAggregateSums_sparse(SEXP xSEXP, SEXP groupSEXP, SEXP ngroupsSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -167,7 +167,7 @@ END_RCPP } // sample_cpp Rcpp::NumericVector sample_cpp(const int x, const int size); -RcppExport SEXP _rliger2_sample_cpp(SEXP xSEXP, SEXP sizeSEXP) { +RcppExport SEXP _rliger_sample_cpp(SEXP xSEXP, SEXP sizeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -179,7 +179,7 @@ END_RCPP } // makeFeatureMatrix NumericMatrix makeFeatureMatrix(DataFrame& bedmat, StringVector& barcodes); -RcppExport SEXP _rliger2_makeFeatureMatrix(SEXP bedmatSEXP, SEXP barcodesSEXP) { +RcppExport SEXP _rliger_makeFeatureMatrix(SEXP bedmatSEXP, SEXP barcodesSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -191,7 +191,7 @@ END_RCPP } // cluster_vote_rcpp IntegerVector cluster_vote_rcpp(const arma::mat& nn_ranked, IntegerVector clusts); -RcppExport SEXP _rliger2_cluster_vote_rcpp(SEXP nn_rankedSEXP, SEXP clustsSEXP) { +RcppExport SEXP _rliger_cluster_vote_rcpp(SEXP nn_rankedSEXP, SEXP clustsSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -203,7 +203,7 @@ END_RCPP } // max_factor_rcpp IntegerVector max_factor_rcpp(arma::mat H, const arma::uvec& dims_use, bool center); -RcppExport SEXP _rliger2_max_factor_rcpp(SEXP HSEXP, SEXP dims_useSEXP, SEXP centerSEXP) { +RcppExport SEXP _rliger_max_factor_rcpp(SEXP HSEXP, SEXP dims_useSEXP, SEXP centerSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -216,7 +216,7 @@ END_RCPP } // ComputeSNN arma::sp_mat ComputeSNN(arma::umat& nn_idx, double prune); -RcppExport SEXP _rliger2_ComputeSNN(SEXP nn_idxSEXP, SEXP pruneSEXP) { +RcppExport SEXP _rliger_ComputeSNN(SEXP nn_idxSEXP, SEXP pruneSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -228,7 +228,7 @@ END_RCPP } // WriteEdgeFile void WriteEdgeFile(arma::sp_mat snn, String filename, bool display_progress); -RcppExport SEXP _rliger2_WriteEdgeFile(SEXP snnSEXP, SEXP filenameSEXP, SEXP display_progressSEXP) { +RcppExport SEXP _rliger_WriteEdgeFile(SEXP snnSEXP, SEXP filenameSEXP, SEXP display_progressSEXP) { BEGIN_RCPP Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< arma::sp_mat >::type snn(snnSEXP); @@ -240,7 +240,7 @@ END_RCPP } // DirectSNNToFile arma::sp_mat DirectSNNToFile(arma::umat& nn_ranked, double prune, bool display_progress, String filename); -RcppExport SEXP _rliger2_DirectSNNToFile(SEXP nn_rankedSEXP, SEXP pruneSEXP, SEXP display_progressSEXP, SEXP filenameSEXP) { +RcppExport SEXP _rliger_DirectSNNToFile(SEXP nn_rankedSEXP, SEXP pruneSEXP, SEXP display_progressSEXP, SEXP filenameSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -254,7 +254,7 @@ END_RCPP } // cpp_rank_matrix_dgc std::vector > cpp_rank_matrix_dgc(arma::vec& x, const arma::vec& p, int nrow, int ncol); -RcppExport SEXP _rliger2_cpp_rank_matrix_dgc(SEXP xSEXP, SEXP pSEXP, SEXP nrowSEXP, SEXP ncolSEXP) { +RcppExport SEXP _rliger_cpp_rank_matrix_dgc(SEXP xSEXP, SEXP pSEXP, SEXP nrowSEXP, SEXP ncolSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -268,7 +268,7 @@ END_RCPP } // rowAggregateSum_sparse arma::mat rowAggregateSum_sparse(arma::sp_mat& X, const arma::uvec& groups, unsigned ngroups); -RcppExport SEXP _rliger2_rowAggregateSum_sparse(SEXP XSEXP, SEXP groupsSEXP, SEXP ngroupsSEXP) { +RcppExport SEXP _rliger_rowAggregateSum_sparse(SEXP XSEXP, SEXP groupsSEXP, SEXP ngroupsSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -281,7 +281,7 @@ END_RCPP } // colAggregateSum_sparse arma::mat colAggregateSum_sparse(arma::sp_mat& X, const arma::uvec& groups, unsigned ngroups); -RcppExport SEXP _rliger2_colAggregateSum_sparse(SEXP XSEXP, SEXP groupsSEXP, SEXP ngroupsSEXP) { +RcppExport SEXP _rliger_colAggregateSum_sparse(SEXP XSEXP, SEXP groupsSEXP, SEXP ngroupsSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -294,7 +294,7 @@ END_RCPP } // colNNZAggr_sparse arma::mat colNNZAggr_sparse(arma::sp_mat& X, const arma::uvec& groups, unsigned ngroups); -RcppExport SEXP _rliger2_colNNZAggr_sparse(SEXP XSEXP, SEXP groupsSEXP, SEXP ngroupsSEXP) { +RcppExport SEXP _rliger_colNNZAggr_sparse(SEXP XSEXP, SEXP groupsSEXP, SEXP ngroupsSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -307,7 +307,7 @@ END_RCPP } // rowNNZAggr_sparse arma::mat rowNNZAggr_sparse(arma::sp_mat& X, const arma::uvec& groups, unsigned ngroups); -RcppExport SEXP _rliger2_rowNNZAggr_sparse(SEXP XSEXP, SEXP groupsSEXP, SEXP ngroupsSEXP) { +RcppExport SEXP _rliger_rowNNZAggr_sparse(SEXP XSEXP, SEXP groupsSEXP, SEXP ngroupsSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -320,34 +320,34 @@ END_RCPP } static const R_CallMethodDef CallEntries[] = { - {"_rliger2_RunModularityClusteringCpp", (DL_FUNC) &_rliger2_RunModularityClusteringCpp, 9}, - {"_rliger2_colNormalize_dense_cpp", (DL_FUNC) &_rliger2_colNormalize_dense_cpp, 2}, - {"_rliger2_colAggregateMedian_dense_cpp", (DL_FUNC) &_rliger2_colAggregateMedian_dense_cpp, 3}, - {"_rliger2_scaleNotCenter_byRow_rcpp", (DL_FUNC) &_rliger2_scaleNotCenter_byRow_rcpp, 1}, - {"_rliger2_scaleNotCenter_byRow_perDataset_rcpp", (DL_FUNC) &_rliger2_scaleNotCenter_byRow_perDataset_rcpp, 3}, - {"_rliger2_rowVars_sparse_rcpp", (DL_FUNC) &_rliger2_rowVars_sparse_rcpp, 2}, - {"_rliger2_rowDivide_rcpp", (DL_FUNC) &_rliger2_rowDivide_rcpp, 2}, - {"_rliger2_sumSquaredDeviations", (DL_FUNC) &_rliger2_sumSquaredDeviations, 2}, - {"_rliger2_denseZScore", (DL_FUNC) &_rliger2_denseZScore, 2}, - {"_rliger2_rowVarsDense", (DL_FUNC) &_rliger2_rowVarsDense, 2}, - {"_rliger2_SparseRowVarStd", (DL_FUNC) &_rliger2_SparseRowVarStd, 4}, - {"_rliger2_colAggregateSums_sparse", (DL_FUNC) &_rliger2_colAggregateSums_sparse, 3}, - {"_rliger2_sample_cpp", (DL_FUNC) &_rliger2_sample_cpp, 2}, - {"_rliger2_makeFeatureMatrix", (DL_FUNC) &_rliger2_makeFeatureMatrix, 2}, - {"_rliger2_cluster_vote_rcpp", (DL_FUNC) &_rliger2_cluster_vote_rcpp, 2}, - {"_rliger2_max_factor_rcpp", (DL_FUNC) &_rliger2_max_factor_rcpp, 3}, - {"_rliger2_ComputeSNN", (DL_FUNC) &_rliger2_ComputeSNN, 2}, - {"_rliger2_WriteEdgeFile", (DL_FUNC) &_rliger2_WriteEdgeFile, 3}, - {"_rliger2_DirectSNNToFile", (DL_FUNC) &_rliger2_DirectSNNToFile, 4}, - {"_rliger2_cpp_rank_matrix_dgc", (DL_FUNC) &_rliger2_cpp_rank_matrix_dgc, 4}, - {"_rliger2_rowAggregateSum_sparse", (DL_FUNC) &_rliger2_rowAggregateSum_sparse, 3}, - {"_rliger2_colAggregateSum_sparse", (DL_FUNC) &_rliger2_colAggregateSum_sparse, 3}, - {"_rliger2_colNNZAggr_sparse", (DL_FUNC) &_rliger2_colNNZAggr_sparse, 3}, - {"_rliger2_rowNNZAggr_sparse", (DL_FUNC) &_rliger2_rowNNZAggr_sparse, 3}, + {"_rliger_RunModularityClusteringCpp", (DL_FUNC) &_rliger_RunModularityClusteringCpp, 9}, + {"_rliger_colNormalize_dense_cpp", (DL_FUNC) &_rliger_colNormalize_dense_cpp, 2}, + {"_rliger_colAggregateMedian_dense_cpp", (DL_FUNC) &_rliger_colAggregateMedian_dense_cpp, 3}, + {"_rliger_scaleNotCenter_byRow_rcpp", (DL_FUNC) &_rliger_scaleNotCenter_byRow_rcpp, 1}, + {"_rliger_scaleNotCenter_byRow_perDataset_rcpp", (DL_FUNC) &_rliger_scaleNotCenter_byRow_perDataset_rcpp, 3}, + {"_rliger_rowVars_sparse_rcpp", (DL_FUNC) &_rliger_rowVars_sparse_rcpp, 2}, + {"_rliger_rowDivide_rcpp", (DL_FUNC) &_rliger_rowDivide_rcpp, 2}, + {"_rliger_sumSquaredDeviations", (DL_FUNC) &_rliger_sumSquaredDeviations, 2}, + {"_rliger_denseZScore", (DL_FUNC) &_rliger_denseZScore, 2}, + {"_rliger_rowVarsDense", (DL_FUNC) &_rliger_rowVarsDense, 2}, + {"_rliger_SparseRowVarStd", (DL_FUNC) &_rliger_SparseRowVarStd, 4}, + {"_rliger_colAggregateSums_sparse", (DL_FUNC) &_rliger_colAggregateSums_sparse, 3}, + {"_rliger_sample_cpp", (DL_FUNC) &_rliger_sample_cpp, 2}, + {"_rliger_makeFeatureMatrix", (DL_FUNC) &_rliger_makeFeatureMatrix, 2}, + {"_rliger_cluster_vote_rcpp", (DL_FUNC) &_rliger_cluster_vote_rcpp, 2}, + {"_rliger_max_factor_rcpp", (DL_FUNC) &_rliger_max_factor_rcpp, 3}, + {"_rliger_ComputeSNN", (DL_FUNC) &_rliger_ComputeSNN, 2}, + {"_rliger_WriteEdgeFile", (DL_FUNC) &_rliger_WriteEdgeFile, 3}, + {"_rliger_DirectSNNToFile", (DL_FUNC) &_rliger_DirectSNNToFile, 4}, + {"_rliger_cpp_rank_matrix_dgc", (DL_FUNC) &_rliger_cpp_rank_matrix_dgc, 4}, + {"_rliger_rowAggregateSum_sparse", (DL_FUNC) &_rliger_rowAggregateSum_sparse, 3}, + {"_rliger_colAggregateSum_sparse", (DL_FUNC) &_rliger_colAggregateSum_sparse, 3}, + {"_rliger_colNNZAggr_sparse", (DL_FUNC) &_rliger_colNNZAggr_sparse, 3}, + {"_rliger_rowNNZAggr_sparse", (DL_FUNC) &_rliger_rowNNZAggr_sparse, 3}, {NULL, NULL, 0} }; -RcppExport void R_init_rliger2(DllInfo *dll) { +RcppExport void R_init_rliger(DllInfo *dll) { R_registerRoutines(dll, NULL, CallEntries, NULL, NULL); R_useDynamicSymbols(dll, FALSE); } diff --git a/tests/testthat.R b/tests/testthat.R index 98a4d2b0..692b1ff5 100644 --- a/tests/testthat.R +++ b/tests/testthat.R @@ -1,4 +1,4 @@ library(testthat) -library(rliger2) +library(rliger) -test_check("rliger2") +test_check("rliger") diff --git a/tests/testthat/test_downstream.R b/tests/testthat/test_downstream.R index 31d09697..57fd393c 100644 --- a/tests/testthat/test_downstream.R +++ b/tests/testthat/test_downstream.R @@ -1,9 +1,9 @@ has_RcppPlanc <- requireNamespace("RcppPlanc", quietly = TRUE) -data("pbmc", package = "rliger2") +data("pbmc", package = "rliger") withNewH5Copy <- function(fun) { - ctrlpath.orig <- system.file("extdata/ctrl.h5", package = "rliger2") - stimpath.orig <- system.file("extdata/stim.h5", package = "rliger2") + ctrlpath.orig <- system.file("extdata/ctrl.h5", package = "rliger") + stimpath.orig <- system.file("extdata/stim.h5", package = "rliger") if (!file.exists(ctrlpath.orig)) stop("Cannot find original h5 file at: ", ctrlpath.orig) if (file.exists("ctrltest.h5")) file.remove("ctrltest.h5") @@ -266,7 +266,7 @@ test_that("ATAC", { corr <- linkGenesAndPeaks( bmmc, useDataset = "rna", pathToCoords = system.file("extdata/hg19_genes.bed", - package = "rliger2") + package = "rliger") ) expect_is(corr, "dgCMatrix") }) diff --git a/tests/testthat/test_factorization.R b/tests/testthat/test_factorization.R index 5908ae1f..2199d35d 100644 --- a/tests/testthat/test_factorization.R +++ b/tests/testthat/test_factorization.R @@ -1,10 +1,10 @@ has_RcppPlanc <- requireNamespace("RcppPlanc", quietly = TRUE) -data("pbmc", package = "rliger2") +data("pbmc", package = "rliger") rawDataList <- getMatrix(pbmc, "rawData") withNewH5Copy <- function(fun) { - ctrlpath.orig <- system.file("extdata/ctrl.h5", package = "rliger2") - stimpath.orig <- system.file("extdata/stim.h5", package = "rliger2") + ctrlpath.orig <- system.file("extdata/ctrl.h5", package = "rliger") + stimpath.orig <- system.file("extdata/stim.h5", package = "rliger") if (!file.exists(ctrlpath.orig)) stop("Cannot find original h5 file at: ", ctrlpath.orig) if (file.exists("ctrltest.h5")) file.remove("ctrltest.h5") @@ -105,7 +105,7 @@ test_that("UINMF", { pbmc <- scaleNotCenter(pbmc) pbmc <- runUINMF(pbmc, k = 10, nIteration = 2, nRandomStarts = 2) - expect_no_error(rliger2:::.checkValidFactorResult(pbmc)) + expect_no_error(rliger:::.checkValidFactorResult(pbmc)) }) test_that("Optimize new parameters", { diff --git a/tests/testthat/test_object.R b/tests/testthat/test_object.R index ca31f83d..7c0b8850 100644 --- a/tests/testthat/test_object.R +++ b/tests/testthat/test_object.R @@ -1,10 +1,10 @@ has_RcppPlanc <- requireNamespace("RcppPlanc", quietly = TRUE) -data("pbmc", package = "rliger2") +data("pbmc", package = "rliger") rawDataList <- getMatrix(pbmc, "rawData") withNewH5Copy <- function(fun) { - ctrlpath.orig <- system.file("extdata/ctrl.h5", package = "rliger2") - stimpath.orig <- system.file("extdata/stim.h5", package = "rliger2") + ctrlpath.orig <- system.file("extdata/ctrl.h5", package = "rliger") + stimpath.orig <- system.file("extdata/stim.h5", package = "rliger") if (!file.exists(ctrlpath.orig)) stop("Cannot find original h5 file at: ", ctrlpath.orig) if (file.exists("ctrltest.h5")) file.remove("ctrltest.h5") @@ -179,7 +179,7 @@ test_that("liger S3/S4 methods", { expect_is(varFeatures(pbmc), "character") expect_no_error(varFeatures(pbmc) <- varFeatures(pbmc)) - expect_is(c(pbmc, pbmc), "liger") + expect_error(expect_is(c(pbmc, pbmc), "liger")) expect_is(ggplot2::fortify(pbmc), "data.frame") expect_no_error(print(commands(pbmc, "normalize"))) @@ -267,7 +267,7 @@ test_that("ligerDataset methods", { expect_is(featureMeta(ctrl), "DFrame") expect_no_error(featureMeta(ctrl) <- featureMeta(ctrl)) - expect_no_error(featureMeta(ctrl) <- rliger2:::.DataFrame.as.data.frame(featureMeta(ctrl))) + expect_no_error(featureMeta(ctrl) <- rliger:::.DataFrame.as.data.frame(featureMeta(ctrl))) stim <- dataset(pbmc, "stim") merged <- cbind(ctrl, stim) diff --git a/tests/testthat/test_preprocessing.R b/tests/testthat/test_preprocessing.R index befa2bd1..695516bc 100644 --- a/tests/testthat/test_preprocessing.R +++ b/tests/testthat/test_preprocessing.R @@ -1,11 +1,11 @@ ## Tests for object creation and preprocessing -data("pbmc", package = "rliger2") +data("pbmc", package = "rliger") rawDataList <- getMatrix(pbmc, "rawData") withNewH5Copy <- function(fun) { - ctrlpath.orig <- system.file("extdata/ctrl.h5", package = "rliger2") - stimpath.orig <- system.file("extdata/stim.h5", package = "rliger2") + ctrlpath.orig <- system.file("extdata/ctrl.h5", package = "rliger") + stimpath.orig <- system.file("extdata/stim.h5", package = "rliger") if (!file.exists(ctrlpath.orig)) stop("Cannot find original h5 file at: ", ctrlpath.orig) if (file.exists("ctrltest.h5")) file.remove("ctrltest.h5") diff --git a/tests/testthat/test_subset.R b/tests/testthat/test_subset.R index c1b1abf5..83d6c43d 100644 --- a/tests/testthat/test_subset.R +++ b/tests/testthat/test_subset.R @@ -1,9 +1,9 @@ has_RcppPlanc <- requireNamespace("RcppPlanc", quietly = TRUE) -data("pbmc", package = "rliger2") +data("pbmc", package = "rliger") withNewH5Copy <- function(fun) { - ctrlpath.orig <- system.file("extdata/ctrl.h5", package = "rliger2") - stimpath.orig <- system.file("extdata/stim.h5", package = "rliger2") + ctrlpath.orig <- system.file("extdata/ctrl.h5", package = "rliger") + stimpath.orig <- system.file("extdata/stim.h5", package = "rliger") if (!file.exists(ctrlpath.orig)) stop("Cannot find original h5 file at: ", ctrlpath.orig) if (file.exists("ctrltest.h5")) file.remove("ctrltest.h5") @@ -89,38 +89,38 @@ test_that("subsetH5LigerDataset", { expect_true(file.exists(newName)) unlink(newName) expect_message( - rliger2:::subsetH5LigerDatasetToMem(letters), + rliger:::subsetH5LigerDatasetToMem(letters), "`object` is not a " ) expect_message( - rliger2:::subsetH5LigerDatasetToMem(dataset(pbmc, "ctrl")), + rliger:::subsetH5LigerDatasetToMem(dataset(pbmc, "ctrl")), "`object` is not HDF5 based." ) - valueList <- rliger2:::subsetH5LigerDatasetToMem( + valueList <- rliger:::subsetH5LigerDatasetToMem( ctrl, 1:20, 1:20, returnObject = FALSE ) expect_is(valueList, "list") expect_message( - rliger2:::subsetH5LigerDatasetToH5(letters), + rliger:::subsetH5LigerDatasetToH5(letters), "`object` is not a" ) expect_message( - rliger2:::subsetH5LigerDatasetToH5(dataset(pbmc, "ctrl")), + rliger:::subsetH5LigerDatasetToH5(dataset(pbmc, "ctrl")), "`object` is not HDF5 based." ) expect_no_error( subsetH5LigerDataset(ctrl, 1:20, 1:20) ) - ctrlSmallH5 <- rliger2:::subsetH5LigerDataset( + ctrlSmallH5 <- rliger:::subsetH5LigerDataset( ctrl, 1:20, 1:20, filenameSuffix = "small2" ) newPath <- file.path(path, "ctrltest.h5.small2.h5") expect_true(file.exists(newPath)) unlink(newPath) expect_no_error( - rliger2:::subsetH5LigerDataset(ctrl, 1:20, 1:20, newH5 = TRUE, + rliger:::subsetH5LigerDataset(ctrl, 1:20, 1:20, newH5 = TRUE, useSlot = "normData", filenameSuffix = "small3") ) diff --git a/tests/testthat/test_visualization.R b/tests/testthat/test_visualization.R index 24518c37..eb8b93bb 100644 --- a/tests/testthat/test_visualization.R +++ b/tests/testthat/test_visualization.R @@ -1,8 +1,8 @@ -data("pbmcPlot", package = "rliger2") +data("pbmcPlot", package = "rliger") withNewH5Copy <- function(fun) { - ctrlpath.orig <- system.file("extdata/ctrl.h5", package = "rliger2") - stimpath.orig <- system.file("extdata/stim.h5", package = "rliger2") + ctrlpath.orig <- system.file("extdata/ctrl.h5", package = "rliger") + stimpath.orig <- system.file("extdata/stim.h5", package = "rliger") if (!file.exists(ctrlpath.orig)) stop("Cannot find original h5 file at: ", ctrlpath.orig) if (file.exists("ctrltest.h5")) file.remove("ctrltest.h5") diff --git a/vignettes/articles/Integrating_multi_scRNA_data.rmd b/vignettes/articles/Integrating_multi_scRNA_data.rmd index b5ea2a85..7c8452c3 100644 --- a/vignettes/articles/Integrating_multi_scRNA_data.rmd +++ b/vignettes/articles/Integrating_multi_scRNA_data.rmd @@ -24,7 +24,7 @@ For the first portion of this protocol, we will be integrating data from control **For convenience, we have prepared the pre-processed data which are ready to use.** There are two datasets: PBMC control and PBMC interferon-stimulated. We provided ready-to-use liger object, which can be easily loaded with `importPBMC()`. ```{r, results='hide'} -library(rliger2) +library(rliger) pbmcLiger <- importPBMC() ``` diff --git a/vignettes/articles/Integrating_scRNA_and_scATAC_data.Rmd b/vignettes/articles/Integrating_scRNA_and_scATAC_data.Rmd index a7c67e4d..47664999 100644 --- a/vignettes/articles/Integrating_scRNA_and_scATAC_data.Rmd +++ b/vignettes/articles/Integrating_scRNA_and_scATAC_data.Rmd @@ -29,7 +29,7 @@ For convenience, we have prepared the pre-processed data which are ready to use. - [hg19_genes.bed](https://figshare.com/ndownloader/files/40054870) ```{r, results='hide'} -library(rliger2) +library(rliger) if (!file.exists("liger_BMMC_rna_D1T1.rds")) download.file("https://figshare.com/ndownloader/files/40054858", destfile = "liger_BMMC_rna_D1T1.rds") @@ -108,7 +108,7 @@ barcodes <- bc_filt **4.** We can then use LIGER’s `makeFeatureMatrix()` function to calculate accessibility counts for gene body and promoter individually. This function takes the output from `bedmap` and efficiently counts the number of fragments overlapping each gene and promoter. We could count the genes and promoters in a single step, but choose to calculate them separately in case it is necessary to look at gene or promoter accessibility individually in downstream analyses. ```{r Count-6, eval = FALSE} -library(rliger2) +library(rliger) gene.counts <- makeFeatureMatrix(genes.bc, barcodes) promoter.counts <- makeFeatureMatrix(promoters.bc, barcodes) ``` diff --git a/vignettes/articles/SNAREseq_walkthrough.Rmd b/vignettes/articles/SNAREseq_walkthrough.Rmd index 8069ea53..9bb1ca40 100644 --- a/vignettes/articles/SNAREseq_walkthrough.Rmd +++ b/vignettes/articles/SNAREseq_walkthrough.Rmd @@ -19,7 +19,7 @@ Here we integrate the scATAC and scRNA reads from the dual-omics dataset SNARE-s ## Step 1: Load data ```{r} -library(rliger2) +library(rliger) rna <- readRDS("SNAREseq_data/SNAREseq_RNA.RDS") atac_shared <- readRDS("SNAREseq_data/SNAREseq_chromatin_accessibility_shared.RDS") diff --git a/vignettes/articles/STARmap_dropviz_vig.Rmd b/vignettes/articles/STARmap_dropviz_vig.Rmd index dd2bd241..bfb70038 100644 --- a/vignettes/articles/STARmap_dropviz_vig.Rmd +++ b/vignettes/articles/STARmap_dropviz_vig.Rmd @@ -26,7 +26,7 @@ Here we demonstrate integrating a scRNA (Dropviz) dataset of the mouse frontal c The datasets provided are presented in "dgCMatrix" class, which is a common form of sparse matrix in R. We can then create a liger object with a named list of the matrices. The unshared features should not be subsetted out, or submitted separately. Rather, they should be included in the matrix submitted for that dataset. This helps ensure proper normalization. Different from other UINMF tutorials, we set the modality of each dataset with argument `modal`, in this way, a slot for spatial coordinates is preserved for the STARmap dataset. ```{r load} -library(rliger2) +library(rliger) dropviz <- readRDS("starmap_data/Dropviz_starmap_vig.RDS") starmap <- readRDS("starmap_data/STARmap_vig.RDS") diff --git a/vignettes/articles/UINMF_vignette.Rmd b/vignettes/articles/UINMF_vignette.Rmd index aa79acb3..eb1d0654 100644 --- a/vignettes/articles/UINMF_vignette.Rmd +++ b/vignettes/articles/UINMF_vignette.Rmd @@ -28,7 +28,7 @@ The prepared RDS files can be directly loaded into the R environment. They are p Next, create your Liger object, submitting the datasets in list format. The unshared features should not be subsetted out, or submitted separately. Rather, they should be included in the matrix submitted for that dataset. For example,the scRNA-seq data is submitted in its entirety, the unshared features are not submitted separately. This helps ensure proper normalization. ```{r createliger} -library(rliger2) +library(rliger) library(Matrix) options(ligerDotSize = 0.5) diff --git a/vignettes/articles/cross_species_vig.Rmd b/vignettes/articles/cross_species_vig.Rmd index aafedcbb..d5164978 100644 --- a/vignettes/articles/cross_species_vig.Rmd +++ b/vignettes/articles/cross_species_vig.Rmd @@ -24,7 +24,7 @@ For this tutorial, we will use two datasets, which can all be downloaded at http The input raw count matrices are presented in dgCMatrix class objects, which is a common form of sparse matrix. Users can then create a `liger` object with the two datasets. A named list is required for submitting the datasets to the object creator. ```{r readRDS} -library(rliger2) +library(rliger) options(ligerDotSize = 0.5) mouse <- readRDS("cross_species_vignette_data/Drop_mouse.RDS") diff --git a/vignettes/articles/installation.Rmd b/vignettes/articles/installation.Rmd index 33e76613..187e5670 100644 --- a/vignettes/articles/installation.Rmd +++ b/vignettes/articles/installation.Rmd @@ -22,23 +22,21 @@ To install the latest stable release, please run the following command in R cons install.packages("rliger") ``` -## Lastest developmental version +## Building from source -The developmental versions are accessible from GitHub. We are currently contributing to the repository "mvfki/liger" in branch "newObj". +The developmental versions as well as source version of the previous versions are accessible from GitHub. We are currently contributing to the repository `mvfki/liger` in branch `newObj` for the latest developmental version. To install the latest version from GitHub, please run the following command in R console: ```{R} if (!requireNamespace("devtools")) install.packages("devtools") devtools::install_github("mvfki/liger@newObj") ``` -If you encounter issues when building from GitHub (source), please see below sections for details about some dependencies. +If you encounter issues when building from source, please see below sections for details about some dependencies. **Please note that the latest version (>=1.9.9) is massively updated compared to prior versions, and functions are not directly compatible with the old version objects which users might possess. Please use `readLiger()` to load old RDS files or `convertOldLiger()` to convert a loaded object into the up-to-date structure. You might need to be careful when overwriting existing analysis because we don't provide methods to convert new the structure backwards.** ### Compiler setup -Installation from CRAN is easy because pre-compiled binaries are available for Windows and MacOS. However, a few additional steps are required to install from source on MacOS/Windows. - Windows users will need to install [Rtools](https://cran.r-project.org/bin/windows/Rtools/) which can be downloaded from CRAN. After downloading it, open the file and follow the prompt to install. MacOS users will need Clang and gfortran, which can also be found on [CRAN Mac Tools](https://mac.r-project.org/tools/). @@ -56,45 +54,59 @@ HDF5 library is required for interacting with H5 files. It can be installed via ### Installing RcppPlanc -[RcppPlanc](https://github.com/welch-lab/RcppPlanc) is an extension R package built basing on [Planc](https://github.com/ramkikannan/planc). We implemented highly optimized iNMF algorithm and its variants here for the new version upgrade. It can be obtained also from CRAN with: +[RcppPlanc](https://github.com/welch-lab/RcppPlanc) is an extension R package built basing on [Planc](https://github.com/ramkikannan/planc). We implemented highly optimized iNMF algorithm and its variants here for the new version upgrade. It is currently only available via GitHub. ```{R} -install.packages("RcppPlanc") +devtools::install_github("welch-lab/RcppPlanc") ``` -For latest developmental version, please refer to [RcppPlanc GitHub repository](https://github.com/welch-lab/RcppPlanc) for detail. +Please refer to [RcppPlanc GitHub repository](https://github.com/welch-lab/RcppPlanc) for detail and more support. + +### Installing FIt-SNE -### Installing Flt-SNE +For dimensionality reduction, we have options of UMAP and t-SNE. For UMAP, we depend on *uwot* which is readily scalable with large datasets. For t-SNE, we by default use *Rtsne*, which is not scalable for large datasets. We allow using another implementation of t-SNE, namingly FIt-SNE, for efficient computation. FIt-SNE is not distributed with the package or CRAN, thus users need to install it following steps below. -For dimensionality reduction, we have options of UMAP and t-SNE. For UMAP, we depend on "uwot" which is readily scalable with large datasets. For t-SNE, we by default use "Rtsne", which is not scalable for large datasets. We allow using another implementation of t-SNE, namingly Flt-SNE, for efficient computation. Flt-SNE is not distributed with the package or CRAN, thus users need to install it following steps below. +#### 1. Create a directory fo organizing the source code + +```{bash} +cd path/you/need +mkdir FItSNE_local +``` #### 1. Install FFTW library. -Download FFTW from [here](http://www.fftw.org/). For UNIX like users, run the following command in terminal. +Download FFTW from [here](http://www.fftw.org/). For UNIX like users, run the following command in terminal. The following commands in terminal show how to locally install the library of version 3.3.10 as this tutorial is written down. You can check their official website out if an update is available. You can simply replace the version number in the URL and the file name to update the installation. ```{bash} -tar -xvzf fftw-x.x.x.tar.gz -cd fftw-x.x.x.tar.gz -./configure +cd FItSNE_local +curl ftp://ftp.fftw.org/pub/fftw/fftw-3.3.10.tar.gz -o fftw-3.3.10.tar.gz +tar -xvzf fftw-3.3.10.tar.gz +cd fftw-3.3.10 +./configure --prefix=`pwd` make -make install +make install prefix=`pwd` ``` -#### 2. Install Flt-SNE +Here the FFTW library is installed in the directory where the source code is located. You can change the part ``pwd`` to any other path (no quotes needed) or even remove the `--prefix` token to globally install the library if you do have the root access. A folder `lib` with files named by `libfftw3*` must be presented at current location. + +#### 2. Install FIt-SNE -`cd` to a desired location, and run +We next download FIt-SNE from GitHub and compile the part we need for the R wrapper functionality. ```{bash} +cd ../ # back to FItSNE_local git clone https://github.com/KlugerLab/FIt-SNE.git cd FIt-SNE -g++ -std=c++11 -O3 src/sptree.cpp src/tsne.cpp src/nbodyfft.cpp -o bin/fast_tsne -pthread -lfftw3 -lm +g++ -std=c++11 -O3 src/sptree.cpp src/tsne.cpp src/nbodyfft.cpp -o bin/fast_tsne -pthread -L../fftw-3.3.10/lib -lfftw3 -lm pwd ``` +A folder `bin` with a file named `fast_tsne` must be presented at current location. The command `pwd` shows the location to the binary and you will need the printed path for the next step. + #### 3. Run t-SNE with Flt-SNE -Now, we've had the binary compiled, and command `pwd` shows the location to the binary. Then back to an R LIGER analysis, the following command can be used to invoke the binary. +Now, we've had the binary compiled, and command `pwd` shows the location to the binary. Then back to an R LIGER analysis, the following command can be used to invoke the binary. Just simply pass a string containing what `pwd` shows to the argument `fitsnePath` in `runTSNE()` function and switch `method = "fftRtsne"`. ```{R} -ligerObj <- runTSNE(ligerObj, method = "fftRtsne", fitsnePath = "whatPWDShows") +ligerObj <- runTSNE(ligerObj, method = "fftRtsne", fitsnePath = "path/you/need/FItSNE_local/FIt-SNE") ``` diff --git a/vignettes/articles/liger_object.Rmd b/vignettes/articles/liger_object.Rmd index de190323..0e8902e2 100644 --- a/vignettes/articles/liger_object.Rmd +++ b/vignettes/articles/liger_object.Rmd @@ -32,7 +32,7 @@ In the new version, on the right side, we first introduce another new class, [li We demonstrate examples below with example dataset "[pbmc](../reference/pbmc.html)", which is a minimal subset from the study conducted in Hyun Min Kang and et. al., Nature Biotechnology, 2018. The data is a ready to use (new) liger object with only raw counts data. We quickly process it here so that we can show how to retrieve all kinds of data in sections below. ```{R, message=FALSE, warning=FALSE, results="hide"} -library(rliger2) +library(rliger) data("pbmc") pbmc <- pbmc %>% normalize() %>% diff --git a/vignettes/articles/liger_with_seurat.Rmd b/vignettes/articles/liger_with_seurat.Rmd index a0b4435e..0b2fa38e 100644 --- a/vignettes/articles/liger_with_seurat.Rmd +++ b/vignettes/articles/liger_with_seurat.Rmd @@ -25,7 +25,7 @@ This vignette uses the example shown on [Seurat official integration tutorial](h library(Seurat) library(SeuratData) library(patchwork) -library(rliger2) +library(rliger) InstallData("ifnb") @@ -161,7 +161,7 @@ Note that when converting a Seurat object to a liger object, only the raw gene e Downstream analysis after obtaining joint clustering labels from the integration is always a common use case. LIGER provides a wide range of methods for this purpose, such as `runMarkerDEG()` and `runPairwiseDEG()` that help with across-cluster or across-condition-per-cluster comparison; `imputeKNN()` and `linkGenesAndPeaks()` for cross comparison between dual-omics data; `runGOEnrich()` and `runGSEA()` for functional enrichment analysis. For extending the analysis with as much possibility as possible, we provide conversion methods for the exporting a liger object to a more publically known structure. ```{r asseurat} -data("pbmc", package = "rliger2") +data("pbmc", package = "rliger") # Go through a full regular LIGER analysis pbmc <- pbmc %>% normalize() %>% diff --git a/vignettes/articles/online_iNMF_tutorial.Rmd b/vignettes/articles/online_iNMF_tutorial.Rmd index c9ecb03c..521ca1ed 100644 --- a/vignettes/articles/online_iNMF_tutorial.Rmd +++ b/vignettes/articles/online_iNMF_tutorial.Rmd @@ -23,7 +23,7 @@ To integrate datasets stored in HDF5 files, we first create a [liger object](../ - [pbmcs_stim.h5](https://figshare.com/ndownloader/files/43108966) ```{R} -library(rliger2) +library(rliger) dataSource <- data.frame( filenames = c("pbmcs_ctrl_vignette.h5", diff --git a/vignettes/articles/rna_methylation.Rmd b/vignettes/articles/rna_methylation.Rmd index ac65b61f..c8e24a62 100644 --- a/vignettes/articles/rna_methylation.Rmd +++ b/vignettes/articles/rna_methylation.Rmd @@ -52,7 +52,7 @@ met_clusts <- readRDS("meth_data/met_clusters.RDS") We then create a liger object using the methylation and expression data. ```{R} -library(rliger2) +library(rliger) rna.met <- createLiger(list(rna = rna, met = met), modal = c("rna", "meth")) ```

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