v1.0.1, fixes for R-devel with Matrix 1.6-2

welch-lab · Nov 8, 2023 · b77fd01 · b77fd01
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: rliger
 Version: 1.0.1
-Date: 2023-11-02
+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.
@@ -65,6 +65,7 @@ RoxygenNote: 7.2.3
 Encoding: UTF-8
 Suggests:
     Seurat,
+    SeuratObject,
     knitr,
     reticulate,
     rmarkdown,

diff --git a/NEWS.md b/NEWS.md
@@ -4,5 +4,6 @@
 - 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)
+}
+