Merge pull request #6467 from satijalab/release/4.2.0

Seurat v4.2.0

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: Seurat
-Version: 4.1.1
-Date: 2022-05-01
+Version: 4.2.0
+Date: 2022-09-21
 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>, Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031>, and Hao, Hao, et al (2020) <doi:10.1101/2020.10.12.335331> for more details.
 Authors@R: c(
@@ -48,7 +48,7 @@ Imports:
     leiden (>= 0.3.1),
     lmtest,
     MASS,
-    Matrix (>= 1.2-14),
+    Matrix (>= 1.5.0),
     matrixStats,
     miniUI,
     patchwork,
@@ -65,16 +65,16 @@ Imports:
     Rtsne,
     scales,
     scattermore (>= 0.7),
-    sctransform (>= 0.3.3),
-    SeuratObject (>= 4.1.0),
+    sctransform (>= 0.3.4),
+    SeuratObject (>= 4.1.2),
     shiny,
     spatstat.core,
     spatstat.geom,
     stats,
     tibble,
     tools,
     utils,
-    uwot (>= 0.1.9)
+    uwot (>= 0.1.14)
 LinkingTo: Rcpp (>= 0.11.0), RcppEigen, RcppProgress
 License: MIT + file LICENSE
 LazyData: true
@@ -95,7 +95,7 @@ Collate:
     'tree.R'
     'utilities.R'
     'zzz.R'
-RoxygenNote: 7.1.2
+RoxygenNote: 7.2.1
 Encoding: UTF-8
 Suggests:
     ape,

NAMESPACE

@@ -521,7 +521,6 @@ importFrom(ggplot2,position_jitterdodge)
 importFrom(ggplot2,scale_alpha)
 importFrom(ggplot2,scale_alpha_ordinal)
 importFrom(ggplot2,scale_color_brewer)
-importFrom(ggplot2,scale_color_discrete)
 importFrom(ggplot2,scale_color_distiller)
 importFrom(ggplot2,scale_color_gradient)
 importFrom(ggplot2,scale_color_gradientn)

NEWS.md

@@ -1,3 +1,16 @@
+# Seurat 4.2.0 (2022-09-21)
+
+## Changes
+- Fix legend color in `DoHeatmap()` ([#5783](https://github.com/satijalab/seurat/issues/5783))
+- Fix bug in `ScaleData()` when regressing out one gene ([#5970](https://github.com/satijalab/seurat/pull/5970))
+- Fix name pulling in `PlotPerturbScore()` ([#6081](https://github.com/satijalab/seurat/pull/6081))
+- Support spaceranger 2.0 ([#6208](https://github.com/satijalab/seurat/pull/6208))
+- Fix bug in `SpatialDimPlot()` when using `group.by` ([#6179](https://github.com/satijalab/seurat/issues/6179))
+- Add `add.noise` parameter in `VlnPlot()`
+([#5756](https://github.com/satijalab/seurat/issues/5756))
+- Fix uwot model backwards compatibility ([#6345](https://github.com/satijalab/seurat/issues/6345))
+- Allow `pseudocount.use` in differential expression functions to be set at the `Assay` level
+
 # Seurat 4.1.1 (2022-05-01)
 
 ## Changes

R/clustering.R

@@ -259,9 +259,7 @@ PredictAssay <- function(
   )
   colnames(x = predicted) <- Cells(x = object)
   if (return.assay) {
-    # TODO: restore once check.matrix is implemented in SeuratObject
-    # predicted.assay <- CreateAssayObject(data = predicted, check.matrix = FALSE)
-    predicted.assay <- CreateAssayObject(data = predicted)
+    predicted.assay <- CreateAssayObject(data = predicted, check.matrix = FALSE)
     return (predicted.assay)
   } else {
     return (predicted)
@@ -1689,7 +1687,7 @@ RunLeiden <- function(
         graph_from_adj_list(adjlist = object)
       } else if (inherits(x = object, what = c('dgCMatrix', 'matrix', 'Matrix'))) {
         if (inherits(x = object, what = 'Graph')) {
-          object <- as(object = object, Class = "dgCMatrix")
+          object <- as.sparse(x = object)
         }
         graph_from_adjacency_matrix(adjmatrix = object, weighted = TRUE)
       } else if (inherits(x = object, what = 'igraph')) {

R/differential_expression.R

@@ -59,7 +59,6 @@ FindAllMarkers <- function(
   latent.vars = NULL,
   min.cells.feature = 3,
   min.cells.group = 3,
-  pseudocount.use = 1,
   mean.fxn = NULL,
   fc.name = NULL,
   base = 2,
@@ -136,7 +135,6 @@ FindAllMarkers <- function(
           latent.vars = latent.vars,
           min.cells.feature = min.cells.feature,
           min.cells.group = min.cells.group,
-          pseudocount.use = pseudocount.use,
           mean.fxn = mean.fxn,
           fc.name = fc.name,
           base = base,
@@ -512,6 +510,7 @@ FindMarkers.default <- function(
   densify = FALSE,
   ...
 ) {
+  pseudocount.use <- pseudocount.use %||% 1
   ValidateCellGroups(
     object = object,
     cells.1 = cells.1,
@@ -603,6 +602,9 @@ FindMarkers.default <- function(
   return(de.results)
 }
 
+#' @param norm.method Normalization method for fold change calculation when
+#' \code{slot} is \dQuote{\code{data}}
+#'
 #' @rdname FindMarkers
 #' @concept differential_expression
 #' @export
@@ -630,8 +632,10 @@ FindMarkers.Assay <- function(
   fc.name = NULL,
   base = 2,
   densify = FALSE,
+  norm.method = NULL,
   ...
 ) {
+  pseudocount.use <- pseudocount.use %||% 1
   data.slot <- ifelse(
     test = test.use %in% DEmethods_counts(),
     yes = 'counts',
@@ -652,7 +656,8 @@ FindMarkers.Assay <- function(
     pseudocount.use = pseudocount.use,
     mean.fxn = mean.fxn,
     fc.name = fc.name,
-    base = base
+    base = base,
+    norm.method = norm.method
   )
   de.results <- FindMarkers(
     object = data.use,
@@ -712,6 +717,7 @@ FindMarkers.SCTAssay <- function(
   recorrect_umi = TRUE,
   ...
 ) {
+  pseudocount.use <- pseudocount.use %||% 1
   data.slot <- ifelse(
     test = test.use %in% DEmethods_counts(),
     yes = 'counts',
@@ -813,6 +819,7 @@ FindMarkers.DimReduc <- function(
   ...
 
 ) {
+  pseudocount.use <- pseudocount.use %||% 1
   if (test.use %in% DEmethods_counts()) {
     stop("The following tests cannot be used for differential expression on a reduction as they assume a count model: ",
          paste(DEmethods_counts(), collapse=", "))
@@ -927,7 +934,6 @@ FindMarkers.Seurat <- function(
   latent.vars = NULL,
   min.cells.feature = 3,
   min.cells.group = 3,
-  pseudocount.use = 1,
   mean.fxn = NULL,
   fc.name = NULL,
   base = 2,
@@ -971,17 +977,14 @@ FindMarkers.Seurat <- function(
   }
   # check normalization method
   norm.command <- paste0("NormalizeData.", assay)
-  if (norm.command %in% Command(object = object) && is.null(x = reduction)) {
-    norm.method <- Command(
+  norm.method <- if (norm.command %in% Command(object = object) && is.null(x = reduction)) {
+    Command(
       object = object,
       command = norm.command,
       value = "normalization.method"
     )
-    if (norm.method != "LogNormalize") {
-      mean.fxn <- function(x) {
-        return(log(x = rowMeans(x = x) + pseudocount.use, base = base))
-      }
-    }
+  } else {
+    NULL
   }
   de.results <- FindMarkers(
     object = data.use,
@@ -1000,11 +1003,11 @@ FindMarkers.Seurat <- function(
     latent.vars = latent.vars,
     min.cells.feature = min.cells.feature,
     min.cells.group = min.cells.group,
-    pseudocount.use = pseudocount.use,
     mean.fxn = mean.fxn,
     base = base,
     fc.name = fc.name,
     densify = densify,
+    norm.method = norm.method,
     ...
   )
   return(de.results)
@@ -1050,7 +1053,9 @@ FoldChange.default <- function(
   return(fc.results)
 }
 
-
+#' @param norm.method Normalization method for mean function selection
+#' when \code{slot} is \dQuote{\code{data}}
+#'
 #' @importFrom Matrix rowMeans
 #' @rdname FoldChange
 #' @concept differential_expression
@@ -1066,18 +1071,25 @@ FoldChange.Assay <- function(
   fc.name = NULL,
   mean.fxn = NULL,
   base = 2,
+  norm.method = NULL,
   ...
 ) {
+  pseudocount.use <- pseudocount.use %||% 1
   data <- GetAssayData(object = object, slot = slot)
+  default.mean.fxn <- function(x) {
+    return(log(x = rowMeans(x = x) + pseudocount.use, base = base))
+  }
   mean.fxn <- mean.fxn %||% switch(
     EXPR = slot,
-    'data' = function(x) {
-      return(log(x = rowMeans(x = expm1(x = x)) + pseudocount.use, base = base))
-    },
+    'data' = switch(
+      EXPR = norm.method %||% '',
+      'LogNormalize' = function(x) {
+        return(log(x = rowMeans(x = expm1(x = x)) + pseudocount.use, base = base))
+      },
+      default.mean.fxn
+    ),
     'scale.data' = rowMeans,
-    function(x) {
-      return(log(x = rowMeans(x = x) + pseudocount.use, base = base))
-    }
+    default.mean.fxn
   )
   # Omit the decimal value of e from the column name if base == exp(1)
   base.text <- ifelse(
@@ -1111,11 +1123,12 @@ FoldChange.DimReduc <- function(
   cells.2,
   features = NULL,
   slot = NULL,
-  pseudocount.use = NULL,
+  pseudocount.use = 1,
   fc.name = NULL,
   mean.fxn = NULL,
   ...
 ) {
+  pseudocount.use <- pseudocount.use %||% 1
   mean.fxn <- mean.fxn %||% rowMeans
   fc.name <- fc.name %||% "avg_diff"
   data <- t(x = Embeddings(object = object))
@@ -1143,7 +1156,7 @@ FoldChange.DimReduc <- function(
 #' @param assay Assay to use in fold change calculation
 #' @param slot Slot to pull data from
 #' @param pseudocount.use Pseudocount to add to averaged expression values when
-#' calculating logFC. 1 by default.
+#' calculating logFC.
 #' @param mean.fxn Function to use for fold change or average difference calculation
 #' @param base The base with respect to which logarithms are computed.
 #' @param fc.name Name of the fold change, average difference, or custom function column
@@ -1163,7 +1176,7 @@ FoldChange.Seurat <- function(
   slot = 'data',
   reduction = NULL,
   features = NULL,
-  pseudocount.use = 1,
+  pseudocount.use = NULL,
   mean.fxn = NULL,
   base = 2,
   fc.name = NULL,

R/dimensional_reduction.R

@@ -1379,6 +1379,10 @@ RunUMAP.default <- function(
         object = reduction.model,
         slot = "model"
       )
+      # add num_precomputed_nns to <v0.1.13 uwot models to prevent errors with newer versions of uwot
+      if (!"num_precomputed_nns" %in% names(model)) {
+        model$num_precomputed_nns <- 1
+      }
       if (length(x = model) == 0) {
         stop(
           "The provided reduction.model does not have a model stored. Please try running umot-learn on the object first",
@@ -1388,7 +1392,7 @@ RunUMAP.default <- function(
       if (is.list(x = object)) {
         if (ncol(object$idx) != model$n_neighbors) {
           warning("Number of neighbors between query and reference ", 
-          "is not equal to the number of neighbros within reference")
+          "is not equal to the number of neighbors within reference")
           model$n_neighbors <- ncol(object$idx)
         }
        umap_transform(