Merge pull request #295 from mvfki/master

Release 1.0.1
welch-lab · Nov 9, 2023 · 43e1860 · 43e1860
2 parents ccd0e5a + b77fd01
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diff --git a/.Rbuildignore b/.Rbuildignore
@@ -1,8 +1,24 @@
+^LICENSE$
+^\.lintr$
+^\.vscode
 ^.*\.Rproj$
 ^\.Rproj\.user$
 ^\.travis\.yml$
+^travis_setup\.sh$
 ^_config\.yml$
-^vignettes/walkthrough_pbmc\.Rmd$
-^docs$
+^appveyor\.yml$
+^vignettes/.*html$
+^vignettes/articles
+^vignettes/Integrating_multi_scRNA_data\.rmd$
 ^vignettes/Integrating_scRNA_and_scATAC_data\.Rmd$
-^vignettes/Integrating_multi_scRNA_data\.Rmd$
+^vignettes/Parameter_selection\.Rmd$
+^vignettes/SNAREseq_walkthrough\.Rmd$
+^vignettes/STARmap_dropviz_vig\.Rmd$
+^vignettes/UINMF_vignette\.Rmd$
+^vignettes/online_iNMF_tutorial\.Rmd$
+^vignettes/pbmc_alignment\.zip$
+^vignettes/walkthrough_pbmc\.Rmd$
+^vignettes/walkthrough_pbmc\.pdf$
+^vignettes/cross_species_vig\.Rmd$
+^docs
+^devdata
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,33 +1,35 @@
 Package: rliger
-Version: 1.0.0
-Date: 2021-03-09
+Version: 1.0.1
+Date: 2023-11-08
 Type: Package
 Title: Linked Inference of Genomic Experimental Relationships
 Description: Uses an extension of nonnegative matrix factorization to identify shared and dataset-specific factors. See Welch J, Kozareva V, et al (2019) <doi:10.1016/j.cell.2019.05.006>, and Liu J, Gao C, Sodicoff J, et al (2020) <doi:10.1038/s41596-020-0391-8> for more details.
 Authors@R: c(
   person(given = 'Joshua', family = 'Welch', email = '[email protected]', role = c('aut', 'ctb')),
-  person(given = 'Chao', family = 'Gao', email = '[email protected]', role = c('aut', 'ctb', 'cre')),
+  person(given = 'Chao', family = 'Gao', email = '[email protected]', role = c('aut', 'ctb')),
   person(given = 'Jialin', family = 'Liu', email = '[email protected]', role = c('aut', 'ctb')),
   person(given = 'Joshua', family = 'Sodicoff', email = '[email protected]', role = c('aut', 'ctb')),
   person(given = 'Velina', family = 'Kozareva', role = c('aut', 'ctb')),
   person(given = 'Evan', family = 'Macosko', role = c('aut', 'ctb')),
+  person(given = 'Yichen', family = 'Wang', email = '[email protected]', role = c('aut', 'ctb', 'cre')),
   person(given = 'Paul', family = 'Hoffman', role = 'ctb'),
   person(given = 'Ilya', family = 'Korsunsky', role = 'ctb'),
   person(given = 'Robert', family = 'Lee', role = 'ctb')
   )
 Author: Joshua Welch [aut, ctb], 
-        Chao Gao [aut, ctb, cre], 
+        Chao Gao [aut, ctb], 
         Jialin Liu [aut, ctb], 
         Joshua Sodicoff [aut, ctb],
         Velina Kozareva [aut, ctb],
         Evan Macosko [aut, ctb],
+        Yichen Wang [aut, ctb, cre],
         Paul Hoffman [ctb],
         Ilya Korsunsky [ctb],
         Robert Lee [ctb]
-Maintainer: Chao Gao <gchao@umich.edu>
+Maintainer: Yichen Wang <wayichen@umich.edu>
 BugReports: https://github.com/welch-lab/liger/issues
 URL: https://github.com/welch-lab/liger
-License: GPL-3 | file LICENSE
+License: GPL-3
 Imports: Rcpp (>= 0.12.10),
      plyr,
      FNN,
@@ -38,31 +40,32 @@ Imports: Rcpp (>= 0.12.10),
      ica,
      Rtsne,
      ggplot2,
-     riverplot,
      foreach,
      parallel,
      doParallel,
      mclust,
-     stats,
      psych,
      RANN,
      uwot,
      rlang,
-     utils,
      hdf5r,
-     scattermore (>= 0.7)
+     scattermore (>= 0.7),
+     patchwork,
+     cowplot
 biocViews:
 LazyData: true
 LinkingTo: Rcpp, RcppArmadillo, RcppEigen, RcppProgress
 Depends:
-    cowplot,
+    R (>= 3.4),
     Matrix,
     methods,
-    patchwork
-RoxygenNote: 7.1.1
+    stats,
+    utils
+RoxygenNote: 7.2.3
 Encoding: UTF-8
 Suggests:
     Seurat,
+    SeuratObject,
     knitr,
     reticulate,
     rmarkdown,

diff --git a/NAMESPACE b/NAMESPACE
@@ -144,8 +144,6 @@ importFrom(methods,slot)
 importFrom(methods,slotNames)
 importFrom(plyr,mapvalues)
 importFrom(plyr,rbind.fill.matrix)
-importFrom(riverplot,makeRiver)
-importFrom(riverplot,riverplot)
 importFrom(rlang,.data)
 importFrom(scattermore,geom_scattermore)
 importFrom(stats,approxfun)

diff --git a/NEWS.md b/NEWS.md
@@ -0,0 +1,9 @@
+## rliger 1.0.1
+
+- Allow setting mito pattern in `getMitoProportion()` #271
+- Fix efficiency issue when taking the log of norm.data (e.g. `runWilcoxon`)
+- Add runable examples to all exported functions when possible
+- Fix typo in online_iNMF matrix initialization
+- Adapt to Seurat5
+- Other minor fixes
+
diff --git a/R/RcppExports.R b/R/RcppExports.R
@@ -1,113 +1,113 @@
-# Generated by using Rcpp::compileAttributes() -> do not edit by hand
-# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
-
-RunModularityClusteringCpp <- function(SNN, modularityFunction, resolution, algorithm, nRandomStarts, nIterations, randomSeed, printOutput, edgefilename) {
-    .Call('_rliger_RunModularityClusteringCpp', PACKAGE = 'rliger', SNN, modularityFunction, resolution, algorithm, nRandomStarts, nIterations, randomSeed, printOutput, edgefilename)
-}
-
-scaleNotCenterFast <- function(x) {
-    .Call('_rliger_scaleNotCenterFast', PACKAGE = 'rliger', x)
-}
-
-rowMeansFast <- function(x) {
-    .Call('_rliger_rowMeansFast', PACKAGE = 'rliger', x)
-}
-
-rowVarsFast <- function(x, means) {
-    .Call('_rliger_rowVarsFast', PACKAGE = 'rliger', x, means)
-}
-
-sumSquaredDeviations <- function(x, means) {
-    .Call('_rliger_sumSquaredDeviations', PACKAGE = 'rliger', x, means)
-}
-
-cpp_sumGroups_dgc <- function(x, p, i, ncol, groups, ngroups) {
-    .Call('_rliger_cpp_sumGroups_dgc', PACKAGE = 'rliger', x, p, i, ncol, groups, ngroups)
-}
-
-cpp_sumGroups_dgc_T <- function(x, p, i, ncol, nrow, groups, ngroups) {
-    .Call('_rliger_cpp_sumGroups_dgc_T', PACKAGE = 'rliger', x, p, i, ncol, nrow, groups, ngroups)
-}
-
-cpp_sumGroups_dense <- function(X, groups, ngroups) {
-    .Call('_rliger_cpp_sumGroups_dense', PACKAGE = 'rliger', X, groups, ngroups)
-}
-
-cpp_sumGroups_dense_T <- function(X, groups, ngroups) {
-    .Call('_rliger_cpp_sumGroups_dense_T', PACKAGE = 'rliger', X, groups, ngroups)
-}
-
-cpp_nnzeroGroups_dense <- function(X, groups, ngroups) {
-    .Call('_rliger_cpp_nnzeroGroups_dense', PACKAGE = 'rliger', X, groups, ngroups)
-}
-
-cpp_nnzeroGroups_dense_T <- function(X, groups, ngroups) {
-    .Call('_rliger_cpp_nnzeroGroups_dense_T', PACKAGE = 'rliger', X, groups, ngroups)
-}
-
-cpp_nnzeroGroups_dgc <- function(p, i, ncol, groups, ngroups) {
-    .Call('_rliger_cpp_nnzeroGroups_dgc', PACKAGE = 'rliger', p, i, ncol, groups, ngroups)
-}
-
-cpp_in_place_rank_mean <- function(v_temp, idx_begin, idx_end) {
-    .Call('_rliger_cpp_in_place_rank_mean', PACKAGE = 'rliger', v_temp, idx_begin, idx_end)
-}
-
-cpp_rank_matrix_dgc <- function(x, p, nrow, ncol) {
-    .Call('_rliger_cpp_rank_matrix_dgc', PACKAGE = 'rliger', x, p, nrow, ncol)
-}
-
-cpp_rank_matrix_dense <- function(X) {
-    .Call('_rliger_cpp_rank_matrix_dense', PACKAGE = 'rliger', X)
-}
-
-cpp_nnzeroGroups_dgc_T <- function(p, i, ncol, nrow, groups, ngroups) {
-    .Call('_rliger_cpp_nnzeroGroups_dgc_T', PACKAGE = 'rliger', p, i, ncol, nrow, groups, ngroups)
-}
-
-#' Fast calculation of feature count matrix
-#' 
-#' @param bedmat A feature count list generated by bedmap
-#' @param barcodes A list of barcodes
-#' 
-#' @return A feature count matrix with features as rows and barcodes as
-#' columns
-#' @export
-#' @examples
-#' \dontrun{
-#' gene.counts <- makeFeatureMatrix(genes.bc, barcodes)
-#' promoter.counts <- makeFeatureMatrix(promoters.bc, barcodes)
-#' samnple <- gene.counts + promoter.counts
-#' }
-makeFeatureMatrix <- function(bedmat, barcodes) {
-    .Call('_rliger_makeFeatureMatrix', PACKAGE = 'rliger', bedmat, barcodes)
-}
-
-cluster_vote <- function(nn_ranked, clusts) {
-    .Call('_rliger_cluster_vote', PACKAGE = 'rliger', nn_ranked, clusts)
-}
-
-scale_columns_fast <- function(mat, scale = TRUE, center = TRUE) {
-    .Call('_rliger_scale_columns_fast', PACKAGE = 'rliger', mat, scale, center)
-}
-
-max_factor <- function(H, dims_use, center_cols = FALSE) {
-    .Call('_rliger_max_factor', PACKAGE = 'rliger', H, dims_use, center_cols)
-}
-
-solveNNLS <- function(C, B) {
-    .Call('_rliger_solveNNLS', PACKAGE = 'rliger', C, B)
-}
-
-ComputeSNN <- function(nn_ranked, prune) {
-    .Call('_rliger_ComputeSNN', PACKAGE = 'rliger', nn_ranked, prune)
-}
-
-WriteEdgeFile <- function(snn, filename, display_progress) {
-    invisible(.Call('_rliger_WriteEdgeFile', PACKAGE = 'rliger', snn, filename, display_progress))
-}
-
-DirectSNNToFile <- function(nn_ranked, prune, display_progress, filename) {
-    .Call('_rliger_DirectSNNToFile', PACKAGE = 'rliger', nn_ranked, prune, display_progress, filename)
-}
-
+# Generated by using Rcpp::compileAttributes() -> do not edit by hand
+# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
+
+RunModularityClusteringCpp <- function(SNN, modularityFunction, resolution, algorithm, nRandomStarts, nIterations, randomSeed, printOutput, edgefilename) {
+    .Call('_rliger_RunModularityClusteringCpp', PACKAGE = 'rliger', SNN, modularityFunction, resolution, algorithm, nRandomStarts, nIterations, randomSeed, printOutput, edgefilename)
+}
+
+scaleNotCenterFast <- function(x) {
+    .Call('_rliger_scaleNotCenterFast', PACKAGE = 'rliger', x)
+}
+
+rowMeansFast <- function(x) {
+    .Call('_rliger_rowMeansFast', PACKAGE = 'rliger', x)
+}
+
+rowVarsFast <- function(x, means) {
+    .Call('_rliger_rowVarsFast', PACKAGE = 'rliger', x, means)
+}
+
+sumSquaredDeviations <- function(x, means) {
+    .Call('_rliger_sumSquaredDeviations', PACKAGE = 'rliger', x, means)
+}
+
+cpp_sumGroups_dgc <- function(x, p, i, ncol, groups, ngroups) {
+    .Call('_rliger_cpp_sumGroups_dgc', PACKAGE = 'rliger', x, p, i, ncol, groups, ngroups)
+}
+
+cpp_sumGroups_dgc_T <- function(x, p, i, ncol, nrow, groups, ngroups) {
+    .Call('_rliger_cpp_sumGroups_dgc_T', PACKAGE = 'rliger', x, p, i, ncol, nrow, groups, ngroups)
+}
+
+cpp_sumGroups_dense <- function(X, groups, ngroups) {
+    .Call('_rliger_cpp_sumGroups_dense', PACKAGE = 'rliger', X, groups, ngroups)
+}
+
+cpp_sumGroups_dense_T <- function(X, groups, ngroups) {
+    .Call('_rliger_cpp_sumGroups_dense_T', PACKAGE = 'rliger', X, groups, ngroups)
+}
+
+cpp_nnzeroGroups_dense <- function(X, groups, ngroups) {
+    .Call('_rliger_cpp_nnzeroGroups_dense', PACKAGE = 'rliger', X, groups, ngroups)
+}
+
+cpp_nnzeroGroups_dense_T <- function(X, groups, ngroups) {
+    .Call('_rliger_cpp_nnzeroGroups_dense_T', PACKAGE = 'rliger', X, groups, ngroups)
+}
+
+cpp_nnzeroGroups_dgc <- function(p, i, ncol, groups, ngroups) {
+    .Call('_rliger_cpp_nnzeroGroups_dgc', PACKAGE = 'rliger', p, i, ncol, groups, ngroups)
+}
+
+cpp_in_place_rank_mean <- function(v_temp, idx_begin, idx_end) {
+    .Call('_rliger_cpp_in_place_rank_mean', PACKAGE = 'rliger', v_temp, idx_begin, idx_end)
+}
+
+cpp_rank_matrix_dgc <- function(x, p, nrow, ncol) {
+    .Call('_rliger_cpp_rank_matrix_dgc', PACKAGE = 'rliger', x, p, nrow, ncol)
+}
+
+cpp_rank_matrix_dense <- function(X) {
+    .Call('_rliger_cpp_rank_matrix_dense', PACKAGE = 'rliger', X)
+}
+
+cpp_nnzeroGroups_dgc_T <- function(p, i, ncol, nrow, groups, ngroups) {
+    .Call('_rliger_cpp_nnzeroGroups_dgc_T', PACKAGE = 'rliger', p, i, ncol, nrow, groups, ngroups)
+}
+
+#' Fast calculation of feature count matrix
+#' 
+#' @param bedmat A feature count list generated by bedmap
+#' @param barcodes A list of barcodes
+#' 
+#' @return A feature count matrix with features as rows and barcodes as
+#' columns
+#' @export
+#' @examples
+#' \dontrun{
+#' gene.counts <- makeFeatureMatrix(genes.bc, barcodes)
+#' promoter.counts <- makeFeatureMatrix(promoters.bc, barcodes)
+#' samnple <- gene.counts + promoter.counts
+#' }
+makeFeatureMatrix <- function(bedmat, barcodes) {
+    .Call('_rliger_makeFeatureMatrix', PACKAGE = 'rliger', bedmat, barcodes)
+}
+
+cluster_vote <- function(nn_ranked, clusts) {
+    .Call('_rliger_cluster_vote', PACKAGE = 'rliger', nn_ranked, clusts)
+}
+
+scale_columns_fast <- function(mat, scale = TRUE, center = TRUE) {
+    .Call('_rliger_scale_columns_fast', PACKAGE = 'rliger', mat, scale, center)
+}
+
+max_factor <- function(H, dims_use, center_cols = FALSE) {
+    .Call('_rliger_max_factor', PACKAGE = 'rliger', H, dims_use, center_cols)
+}
+
+solveNNLS <- function(C, B) {
+    .Call('_rliger_solveNNLS', PACKAGE = 'rliger', C, B)
+}
+
+ComputeSNN <- function(nn_ranked, prune) {
+    .Call('_rliger_ComputeSNN', PACKAGE = 'rliger', nn_ranked, prune)
+}
+
+WriteEdgeFile <- function(snn, filename, display_progress) {
+    invisible(.Call('_rliger_WriteEdgeFile', PACKAGE = 'rliger', snn, filename, display_progress))
+}
+
+DirectSNNToFile <- function(nn_ranked, prune, display_progress, filename) {
+    .Call('_rliger_DirectSNNToFile', PACKAGE = 'rliger', nn_ranked, prune, display_progress, filename)
+}
+
diff --git a/R/data.R b/R/data.R
@@ -0,0 +1,10 @@
+#' dgCMatrix object of PBMC subsample data with Control and Stimulated datasets
+#' @format \code{dgCMatrix} object of gene expression matrix from PBMC study,
+#'  named by "ctrl" and "stim".
+#' @source https://www.nature.com/articles/nbt.4042
+#' @references Hyun Min Kang and et. al., Nature Biotechnology, 2018
+#' @rdname liger-demodata
+"ctrl"
+
+#' @rdname liger-demodata
+"stim"