Merge pull request #2648 from satijalab/develop

Seurat v3.1.4

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: Seurat
-Version: 3.1.3
-Date: 2020-02-07
+Version: 3.1.4
+Date: 2020-02-26
 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.
+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. Please note:  SDMTools is available is available from the CRAN archives with install.packages("https://cran.rstudio.com//src/contrib/Archive/SDMTools/SDMTools_1.1-221.2.tar.gz", repos = NULL); it is not in the standard repositories.
 Authors@R: c(
   person(given = 'Rahul', family = 'Satija', email = 'rsatija@nygenome.org', role = 'aut', comment = c(ORCID = '0000-0001-9448-8833')),
   person(given = 'Andrew', family = 'Butler', email = 'abutler@nygenome.org', role = 'aut', comment = c(ORCID = '0000-0003-3608-0463')),
@@ -43,6 +43,7 @@ Imports:
     MASS,
     Matrix (>= 1.2-14),
     metap,
+    patchwork,
     pbapply,
     plotly,
     png,

NAMESPACE

@@ -482,6 +482,7 @@ importFrom(methods,setOldClass)
 importFrom(methods,signature)
 importFrom(methods,slot)
 importFrom(methods,slotNames)
+importFrom(patchwork,wrap_plots)
 importFrom(pbapply,pbapply)
 importFrom(pbapply,pblapply)
 importFrom(pbapply,pbsapply)

NEWS.md

@@ -2,7 +2,12 @@
 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
+## [3.1.4] - 2020-02-20
+### Changes 
+- Fixes to `DoHeatmap` to remain compatible with ggplot2 v3.3
+- Adoption of `patchwork` framework to replace `CombinePlots`
+
+## [3.1.3] - 2020-02-07
 ### Added
 - New system agnostic `Which` function to address problems with FItSNE on Windows
 

R/convenience.R

@@ -19,6 +19,8 @@ PCHeatmap <- function(object, ...) {
   return(do.call(what = 'DimHeatmap', args = args))
 }
 
+#' @param ... Extra parameters passed to \code{DimPlot}
+#'
 #' @rdname DimPlot
 #' @export
 #'

R/objects.R

@@ -5667,19 +5667,24 @@ merge.Assay <- function(
   if (all(IsSCT(assay = assays))) {
     vst.set.new <- list()
     idx <- 1
+    umi.assay.new <- list()
     for (i in 1:length(x = assays)) {
       vst.set.old <- Misc(object = assays[[i]], slot = "vst.set")
+      umi.assay.old <- Misc(object = assays[[i]], slot = "umi.assay")
       if (!is.null(x = vst.set.old)) {
         for (j in 1:length(x = vst.set.old)) {
           vst.set.new[[idx]] <- vst.set.old[[j]]
+          umi.assay.new[[idx]] <- umi.assay.old[[j]]
           idx <- idx + 1
         }
       } else if (!is.null(x = Misc(object = assays[[i]], slot = "vst.out"))) {
         vst.set.new[[idx]] <- Misc(object = assays[[i]], slot = "vst.out")
+        umi.assay.new[[idx]] <- Misc(object = assays[[i]], slot = "umi.assay")
         idx <- idx + 1
       }
     }
     Misc(object = combined.assay, slot = "vst.set") <- vst.set.new
+    Misc(object = combined.assay, slot = "umi.assay") <- umi.assay.new
     scale.data <- do.call(
       what = cbind,
       args = lapply(X = assays, FUN = function(x) GetAssayData(object = x, slot = "scale.data"))

R/preprocessing.R

@@ -453,14 +453,16 @@ GetResidual <- function(
   object,
   features,
   assay = "SCT",
-  umi.assay = "RNA",
+  umi.assay = NULL,
   clip.range = NULL,
   replace.value = FALSE,
   verbose = TRUE
 ) {
   if (!IsSCT(assay = object[[assay]])) {
     stop(assay, " assay was not generated by SCTransform")
   }
+  umi.assay <- umi.assay %||% Misc(object = object[[assay]], slot = "umi.assay")
+  umi.assay <- umi.assay %||% "RNA" # for object created in 3.1.1 or earlier, default to RNA
   if (replace.value) {
     new_features <- features
   } else {
@@ -534,7 +536,7 @@ GetResidual <- function(
       object.v <- GetResidualVstOut(
         object = object.v,
         assay = assay,
-        umi.assay = umi.assay,
+        umi.assay = umi.assay[[v]],
         new_features = new_features,
         vst_out = vst_out,
         clip.range = clip.range,
@@ -1353,6 +1355,7 @@ SCTransform <- function(
   # save clip.range into vst model
   vst.out$arguments$sct.clip.range <- clip.range
   Misc(object = assay.out, slot = 'vst.out') <- vst.out
+  Misc(object = assay.out, slot = 'umi.assay') <- assay
   # also put gene attributes in meta.features
   assay.out[[paste0('sct.', names(x = vst.out$gene_attr))]] <- vst.out$gene_attr
   assay.out[['sct.variable']] <- rownames(x = assay.out[[]]) %in% top.features