Merge pull request #2605 from satijalab/develop

Seurat v3.1.3

Author: mojaveazure

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: Seurat
-Version: 3.1.2
-Date: 2019-12-12
+Version: 3.1.3
+Date: 2020-02-07
 Title: Tools for Single Cell Genomics
 Description: A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, and Butler A and Satija R (2017) <doi:10.1101/164889> for more details.
 Authors@R: c(
@@ -57,7 +57,6 @@ Imports:
     Rtsne,
     scales,
     sctransform (>= 0.2.0),
-    SDMTools,
     stats,
     tools,
     tsne,
@@ -86,6 +85,7 @@ Encoding: UTF-8
 biocViews:
 Suggests:
     loomR,
+    SDMTools,
     testthat,
     hdf5r,
     S4Vectors,

NAMESPACE

@@ -199,6 +199,7 @@ export(DefaultAssay)
 export(DietSeurat)
 export(DimHeatmap)
 export(DimPlot)
+export(DiscretePalette)
 export(DoHeatmap)
 export(DotPlot)
 export(ElbowPlot)
@@ -357,7 +358,6 @@ importFrom(RcppAnnoy,AnnoyEuclidean)
 importFrom(RcppAnnoy,AnnoyHamming)
 importFrom(RcppAnnoy,AnnoyManhattan)
 importFrom(Rtsne,Rtsne)
-importFrom(SDMTools,pnt.in.poly)
 importFrom(ape,as.phylo)
 importFrom(ape,drop.tip)
 importFrom(ape,nodelabels)
@@ -379,6 +379,7 @@ importFrom(ggplot2,coord_cartesian)
 importFrom(ggplot2,coord_fixed)
 importFrom(ggplot2,coord_flip)
 importFrom(ggplot2,cut_number)
+importFrom(ggplot2,discrete_scale)
 importFrom(ggplot2,dup_axis)
 importFrom(ggplot2,element_blank)
 importFrom(ggplot2,element_line)

NEWS.md

@@ -2,6 +2,18 @@
 All notable changes to Seurat will be documented in this file.
 The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
 
+## [3.1.3] = 2020-02-07
+### Added
+- New system agnostic `Which` function to address problems with FItSNE on Windows
+
+### Changes
+- Export `CellsByIdentities` and `RowMergeSparseMatrices` functions
+- nCount and nFeature metadata variables retained after subset and updated properly with `UpdateSeuratObject`
+- Fix uwot support for running directly on feature matrices
+- Fixes for keys with underscores
+- Fix issue with leiden option for `FindClusters`
+- Fix for data transfer when using sctransform
+- SDMTools moved to Suggests as package is orphaned 
 
 ## [3.1.2] - 2019-12-11
 ### Added

R/clustering.R

@@ -713,29 +713,35 @@ RunLeiden <- function(
       call. = FALSE
     )
   }
-  if (method %in% c("matrix", "igraph")) {
-    if (method == "igraph") {
-      object <- graph_from_adjacency_matrix(adjmatrix = object)
-    }
-  } else {
-    warning(
-      "method for Leiden recommended as 'matrix' or 'igraph'",
-      call. = FALSE,
-      immediate. = TRUE
-    )
-  }
-  input <- if (inherits(x = object, what = 'list')) {
-    graph_from_adj_list(adjlist = object)
-  } else if (inherits(x = object, what = c('dgCMatrix', 'matrix', "Matrix"))) {
-    graph_from_adjacency_matrix(adjmatrix = object)
-  } else if (inherits(x = object, what = 'igraph')) {
-    object
-  } else {
-    stop(
-      paste("method for Leiden not found for class", class(x = object)),
-      call. = FALSE
-    )
-  }
+  switch(
+    EXPR = method,
+    "matrix" = {
+      input <- as(object = object, Class = "matrix")
+      },
+    "igraph" = {
+      input <- if (inherits(x = object, what = 'list')) {
+        if (is.null(x = weights)) {
+          graph_from_adj_list(adjlist = object)
+        } else {
+          graph_from_adj_list(adjlist = object)
+        }
+      } else if (inherits(x = object, what = c('dgCMatrix', 'matrix', "Matrix"))) {
+        if (is.null(x = weights)) {
+          graph_from_adjacency_matrix(adjmatrix = object)
+        } else {
+          graph_from_adjacency_matrix(adjmatrix = object, weighted = TRUE)
+        }
+      } else if (inherits(x = object, what = 'igraph')) {
+        object
+      } else {
+        stop(
+          "Method for Leiden not found for class", class(x = object), 
+           call. = FALSE
+        )
+      }
+    },
+    stop("Method for Leiden must be either 'matrix' or igraph'")
+  )
   #run leiden from CRAN package (calls python with reticulate)
   partition <- leiden(
     object = input,

R/differential_expression.R

@@ -437,7 +437,7 @@ FindConservedMarkers <- function(
 #' @param pseudocount.use Pseudocount to add to averaged expression values when
 #' calculating logFC. 1 by default.
 #'
-#' @importFrom Matrix rowSums
+#' @importFrom Matrix rowSums rowMeans
 #' @importFrom stats p.adjust
 #'
 #' @rdname FindMarkers
@@ -540,25 +540,18 @@ FindMarkers.default <- function(
     switch(
       EXPR = slot,
       'data' = function(x) {
-        return(log(x = mean(x = expm1(x = x)) + pseudocount.use))
+        return(log(x = rowMeans(x = expm1(x = x)) + pseudocount.use))
       },
       function(x) {
-        return(log(x = mean(x = x) + pseudocount.use))
+        return(log(x = rowMeans(x = x) + pseudocount.use))
       }
     )
   } else {
-    mean
+    rowMeans
   }
-  data.1 <- apply(
-    X = data[features, cells.1, drop = FALSE],
-    MARGIN = 1,
-    FUN = mean.fxn
-  )
-  data.2 <- apply(
-    X = data[features, cells.2, drop = FALSE],
-    MARGIN = 1,
-    FUN = mean.fxn
-  )
+  data.1 <- mean.fxn(data[features, cells.1, drop = FALSE])
+  data.2 <- mean.fxn(data[features, cells.2, drop = FALSE])
+
   total.diff <- (data.1 - data.2)
   if (is.null(x = reduction) && slot != "scale.data") {
     features.diff <- if (only.pos) {

R/dimensional_reduction.R

@@ -861,7 +861,7 @@ RunPCA.default <- function(
   return(reduction.data)
 }
 
-#' @param features Features to compute PCA on. If features=NULL, PCA will be run 
+#' @param features Features to compute PCA on. If features=NULL, PCA will be run
 #' using the variable features for the Assay. Note that the features must be present
 #' in the scaled data. Any requested features that are not scaled or have 0 variance
 #' will be dropped, and the PCA will be run using the remaining features.
@@ -1456,10 +1456,30 @@ RunUMAP.Seurat <- function(
       stop("Please specify only one of the following arguments: dims, features, or graph")
   }
   if (!is.null(x = features)) {
-    data.use <- t(x = GetAssayData(object = object, slot = 'data', assay = assay)[features, ])
+    data.use <- as.matrix(x = t(x = GetAssayData(object = object, slot = 'data', assay = assay)[features, , drop = FALSE]))
+    if (ncol(x = data.use) < n.components) {
+      stop(
+        "Please provide as many or more features than n.components: ",
+        length(x = features),
+        " features provided, ",
+        n.components,
+        " UMAP components requested",
+        call. = FALSE
+      )
+    }
   } else if (!is.null(x = dims)) {
     data.use <- Embeddings(object[[reduction]])[, dims]
     assay <- DefaultAssay(object = object[[reduction]])
+    if (length(x = dims) < n.components) {
+      stop(
+        "Please provide as many or more dims than n.components: ",
+        length(x = dims),
+        " dims provided, ",
+        n.components,
+        " UMAP components requested",
+        call. = FALSE
+      )
+    }
   } else if (!is.null(x = graph)) {
     data.use <- object[[graph]]
   } else {
@@ -1703,7 +1723,12 @@ fftRtsne <- function(X,
     result_path <- tempfile(pattern = 'fftRtsne_result_', fileext = '.dat')
   }
   if (is.null(x = fast_tsne_path)) {
-    suppressWarnings(expr = fast_tsne_path <- system2(command = 'which', args = 'fast_tsne', stdout = TRUE))
+    # suppressWarnings(expr = fast_tsne_path <- system2(command = 'which', args = 'fast_tsne', stdout = TRUE))
+    fast_tsne_path <- SysExec(progs = ifelse(
+      test = .Platform$OS.type == 'windows',
+      yes = 'FItSNE.exe',
+      no = 'fast_tsne'
+      ))
     if (length(x = fast_tsne_path) == 0) {
       stop("no fast_tsne_path specified and fast_tsne binary is not in the search path")
     }

R/generics.R

@@ -764,9 +764,6 @@ RunALRA <- function(object, ...) {
 #'
 #' @return Returns a combined Seurat object with the CCA results stored.
 #'
-#' @rdname RunCCA
-#' @export RunCCA
-#'
 #' @seealso \code{\link{merge.Seurat}}
 #'
 #' @examples