Merge pull request satijalab#3825 from satijalab/develop

Seurat v3.2.3
zdh8328 · Dec 15, 2020 · b56d194 · b56d194
2 parents fe93b05 + fe0f02d
commit b56d194
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: Seurat
-Version: 3.2.2
-Date: 2020-09-25
+Version: 3.2.3
+Date: 2020-12-14
 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 Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031> for more details.
 Authors@R: c(
@@ -58,14 +58,15 @@ Imports:
     rsvd,
     Rtsne,
     scales,
-    sctransform (>= 0.3.0),
+    scattermore (>= 0.7),
+    sctransform (>= 0.3.1),
     shiny,
     spatstat,
     stats,
     tibble,
     tools,
     utils,
-    uwot (>= 0.1.5)
+    uwot (>= 0.1.9)
 LinkingTo: Rcpp (>= 0.11.0), RcppEigen, RcppProgress
 License: GPL-3 | file LICENSE
 LazyData: true

diff --git a/NAMESPACE b/NAMESPACE
@@ -245,6 +245,7 @@ export(CellScatter)
 export(CellSelector)
 export(Cells)
 export(CellsByIdentities)
+export(CenterTitle)
 export(CollapseEmbeddingOutliers)
 export(CollapseSpeciesExpressionMatrix)
 export(ColorDimSplit)
@@ -641,6 +642,7 @@ importFrom(scales,hue_pal)
 importFrom(scales,rescale)
 importFrom(scales,squish_infinite)
 importFrom(scales,zero_range)
+importFrom(scattermore,geom_scattermore)
 importFrom(sctransform,correct_counts)
 importFrom(sctransform,get_residual_var)
 importFrom(sctransform,get_residuals)

diff --git a/NEWS.md b/NEWS.md
@@ -2,6 +2,26 @@
 All notable changes to Seurat will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/)
 
+## [3.2.3] - 2020-12-14
+### Added
+- Titles added to `DimPlot` when specifying `group.by` parameter
+- `keep.scale` parameter added to `FeaturePlot` to control scaling across multiple features and/or splits.
+
+### Changes
+- `Same` deprecated in favor of `base::identity`
+- Fix in `DietSeurat` to work with specialized `Assay` objects
+- Fix p-value return when using the `ape` implementation of Moran's I
+- Fix bug in FindMarkers when using MAST with a latent variable
+- Updates to `Key<-.DimReduc` that allow handling of empty reduction column names
+- Allow setting `ctrl` in `CellCycleScoring`
+- Modify subset.Seurat to allow specialized Assay subsetting methods
+- Fix image selection in interactive spatial plots
+- Update Rcpp functions with `export(rng=FALSE)` to avoid potential future warnings
+- Fix RenameCells bug for integrated SCT assays
+- Fix highlight order with proper factor levels when using `SetHighlight` in plots
+- Small change in CellRanger version detection logic of h5 file to improve robustness to outside tools.
+- `do.cpp` deprecated and will default to true
+
 ## [3.2.2] - 2020-09-25
 ### Changes
 - Set the seed in `WhichCells` regardless of whether or not `idents` is passed

diff --git a/R/differential_expression.R b/R/differential_expression.R
@@ -1351,9 +1351,6 @@ MASTDETest <- function(
   if (!PackageCheck('MAST', error = FALSE)) {
     stop("Please install MAST - learn more at https://github.com/RGLab/MAST")
   }
-  if (length(x = latent.vars) > 0) {
-    latent.vars <- scale(x = latent.vars)
-  }
   group.info <- data.frame(row.names = c(cells.1, cells.2))
   latent.vars <- latent.vars %||% group.info
   group.info[cells.1, "group"] <- "Group1"
@@ -1367,6 +1364,7 @@ MASTDETest <- function(
   rownames(x = fdat) <- fdat[, 1]
   sca <- MAST::FromMatrix(
     exprsArray = as.matrix(x = data.use),
+    check_sanity = FALSE,
     cData = latent.vars,
     fData = fdat
   )

diff --git a/R/dimensional_reduction.R b/R/dimensional_reduction.R
@@ -1301,11 +1301,6 @@ RunUMAP.default <- function(
         )
       }
       if (is.list(x = object)) {
-        if (packageVersion(pkg = "uwot") <= '0.1.8.9000') {
-          stop("This uwot functionality requires uwot version >= 0.1.8.9000",
-               "Installing the latest version from github can be done with",
-               "remotes::install_github('jlmelville/uwot')")
-        }
         uwot::umap_transform(
           X = NULL,
           nn_method = object,

diff --git a/R/integration.R b/R/integration.R
@@ -862,7 +862,8 @@ GetTransferPredictions <- function(object, assay = "predictions", slot = "data",
 #' automatically.
 #' @param preserve.order Do not reorder objects based on size for each pairwise
 #' integration.
-#' @param do.cpp Run cpp code where applicable
+#' @param do.cpp Run cpp code where applicable. This argument is being
+#' deprecated and will be set to TRUE by default.
 #' @param eps Error bound on the neighbor finding algorithm (from
 #' \code{\link{RANN}})
 #' @param verbose Print progress bars and output
@@ -921,6 +922,14 @@ IntegrateData <- function(
   eps = 0,
   verbose = TRUE
 ) {
+  # TODO: deprecate fully in 4.0
+  if (!isTRUE(x = do.cpp)) {
+    warning(
+      "The do.cpp parameter is being deprecated. It will default to TRUE.",
+      call. = FALSE,
+      immediate. = TRUE
+    )
+  }
   normalization.method <- match.arg(arg = normalization.method)
   reference.datasets <- slot(object = anchorset, name = 'reference.objects')
   object.list <- slot(object = anchorset, name = 'object.list')
@@ -1584,7 +1593,8 @@ SelectIntegrationFeatures <- function(
 #' @param sd.weight Controls the bandwidth of the Gaussian kernel for weighting
 #' @param eps Error bound on the neighbor finding algorithm (from
 #' \code{\link{RANN}})
-#' @param do.cpp Run cpp code where applicable
+#' @param do.cpp Run cpp code where applicable. This argument is being
+#' deprecated and will be set to TRUE by default.
 #' @param verbose Print progress bars and output
 #' @param slot Slot to store the imputed data. Must be either "data" (default)
 #' or "counts"
@@ -1641,6 +1651,14 @@ TransferData <- function(
   slot = "data",
   prediction.assay = FALSE
 ) {
+  # TODO: deprecate fully in 4.0
+  if (!isTRUE(x = do.cpp)) {
+    warning(
+      "The do.cpp parameter is being deprecated. It will default to TRUE.",
+      call. = FALSE,
+      immediate. = TRUE
+    )
+  }
   combined.ob <- slot(object = anchorset, name = "object.list")[[1]]
   anchors <- slot(object = anchorset, name = "anchors")
   reference.cells <- slot(object = anchorset, name = "reference.cells")
@@ -2477,7 +2495,8 @@ GetCellOffsets <- function(anchors, dataset, cell, cellnames.list, cellnames) {
 # @param sd.weight Controls the bandwidth of the Gaussian kernel for weighting
 # @param sample.tree Specify the order of integration. If NULL, will compute automatically.
 # @param preserve.order Do not reorder objects based on size for each pairwise integration.
-# @param do.cpp Run cpp code where applicable
+# @param do.cpp Run cpp code where applicable. This argument is being
+# deprecated and will be set to TRUE by default.
 # @param eps Error bound on the neighbor finding algorithm (from \code{\link{RANN}})
 # @param verbose Print progress bars and output
 #
@@ -2500,6 +2519,14 @@ MapQuery <- function(
   eps = 0,
   verbose = TRUE
 ) {
+  # TODO: deprecate fully in 4.0
+  if (!isTRUE(x = do.cpp)) {
+    warning(
+      "The do.cpp parameter is being deprecated. It will default to TRUE.",
+      call. = FALSE,
+      immediate. = TRUE
+    )
+  }
   normalization.method <- match.arg(arg = normalization.method)
   reference.datasets <- slot(object = anchorset, name = 'reference.objects')
   object.list <- slot(object = anchorset, name = 'object.list')
@@ -2619,7 +2646,8 @@ NNtoMatrix <- function(idx, distance, k) {
 # automatically.
 # @param preserve.order Do not reorder objects based on size for each pairwise
 # integration.
-# @param do.cpp Run cpp code where applicable
+# @param do.cpp Run cpp code where applicable. This argument is being
+# deprecated and will be set to TRUE by default.
 # @param eps Error bound on the neighbor finding algorithm (from
 # \code{\link{RANN}})
 # @param verbose Print progress bars and output
@@ -2642,6 +2670,14 @@ PairwiseIntegrateReference <- function(
   eps = 0,
   verbose = TRUE
 ) {
+  # TODO: deprecate fully in 4.0
+  if (!isTRUE(x = do.cpp)) {
+    warning(
+      "The do.cpp parameter is being deprecated. It will default to TRUE.",
+      call. = FALSE,
+      immediate. = TRUE
+    )
+  }
   object.list <- slot(object = anchorset, name = "object.list")
   reference.objects <- slot(object = anchorset, name = "reference.objects")
   features <- features %||% slot(object = anchorset, name = "anchor.features")
@@ -2955,7 +2991,8 @@ ReferenceRange <- function(x, lower = 0.025, upper = 0.975) {
 # query, and weights will need to be calculated for all cells in the object.
 # @param sd.weight Controls the bandwidth of the Gaussian kernel for weighting
 # @param sample.tree Specify the order of integration. If NULL, will compute automatically.
-# @param do.cpp Run cpp code where applicable
+# @param do.cpp Run cpp code where applicable. This argument is being
+# deprecated and will be set to TRUE by default.
 # @param eps Error bound on the neighbor finding algorithm (from \code{\link{RANN}})
 # @param verbose Print progress bars and output
 #
@@ -2976,6 +3013,14 @@ RunIntegration <- function(
   eps,
   verbose
 ) {
+  # TODO: deprecate fully in 4.0
+  if (!isTRUE(x = do.cpp)) {
+    warning(
+      "The do.cpp parameter is being deprecated. It will default to TRUE.",
+      call. = FALSE,
+      immediate. = TRUE
+    )
+  }
   cells1 <- colnames(x = reference)
   cells2 <- colnames(x = query)
   merged.obj <- merge(x = reference, y = query, merge.data = TRUE)

diff --git a/R/objects.R b/R/objects.R
@@ -1077,40 +1077,28 @@ DietSeurat <- function(
     if (!(assay %in% assays)) {
       object[[assay]] <- NULL
     } else {
-      features.assay <- features %||% rownames(x = object[[assay]])
-      features.assay <- intersect(x = features.assay, y = rownames(x = object[[assay]]))
-      if (length(x = features.assay) == 0) {
-        if (assay == DefaultAssay(object = object)) {
-          stop("The default assay is slated to be removed, please change the default assay")
-        } else {
-          warning("No features found in assay '", assay, "', removing...")
-          object[[assay]] <- NULL
-        }
-      } else {
-        if (counts) {
-          if (!is.null(x = features) && !IsMatrixEmpty(x = GetAssayData(object = object[[assay]], slot = "counts"))) {
-            slot(object = object[[assay]], name = 'counts') <- slot(object = object[[assay]], name = 'counts')[features.assay, ]
-          }
-        } else {
-          slot(object = object[[assay]], name = 'counts') <- new(Class = 'matrix')
-        }
-        if (data) {
-          if (!is.null(x = features)) {
-            slot(object = object[[assay]], name = 'data') <- slot(object = object[[assay]], name = 'data')[features.assay, ]
-          }
-        } else {
-          stop('data = FALSE currently not supported')
-          slot(object = object[[assay]], name = 'data') <- new(Class = 'matrix')
-        }
-        features.scaled <- features.assay[features.assay %in% rownames(x = slot(object = object[[assay]], name = 'scale.data'))]
-        if (scale.data && length(x = features.scaled) > 0) {
-          if (! all(rownames(x = slot(object = object[[assay]], name = 'scale.data')) %in% features.scaled)) {
-            slot(object = object[[assay]], name = 'scale.data') <-  slot(object = object[[assay]], name = 'scale.data')[features.scaled, ]
+      if (!is.null(x = features)) {
+        features.assay <- intersect(x = features, y = rownames(x = object[[assay]]))
+        if (length(x = features.assay) == 0) {
+          if (assay == DefaultAssay(object = object)) {
+            stop("The default assay is slated to be removed, please change the default assay")
+          } else {
+            warning("No features found in assay '", assay, "', removing...")
+            object[[assay]] <- NULL
           }
         } else {
-          slot(object = object[[assay]], name = 'scale.data') <- new(Class = 'matrix')
+          object[[assay]] <- subset(x = object[[assay]], features = features.assay)
         }
       }
+      if (!counts) {
+        slot(object = object[[assay]], name = 'counts') <- new(Class = 'matrix')
+      }
+      if (!data) {
+        stop('data = FALSE currently not supported')
+      }
+      if (!scale.data) {
+        slot(object = object[[assay]], name = 'scale.data') <- new(Class = 'matrix')
+      }
     }
   }
   # remove unspecified DimReducs and Graphs
@@ -3844,7 +3832,7 @@ IsGlobal.default <- function(object) {
 #'
 IsGlobal.DimReduc <- function(object) {
   object <- UpdateSlots(object = object)
-  return(slot(object = object, name = 'global'))
+  return(isTRUE(x = slot(object = object, name = 'global')))
 }
 
 #' @rdname IsGlobal
@@ -4008,6 +3996,7 @@ Key.SpatialImage <- function(object, ...) {
 "Key<-.DimReduc" <- function(object, ..., value) {
   CheckDots(...)
   object <- UpdateSlots(object = object)
+  value <- UpdateKey(key = value)
   old.key <- Key(object = object)
   slots <- Filter(
     f = function(x) {
@@ -4018,11 +4007,15 @@ Key.SpatialImage <- function(object, ...) {
   for (s in slots) {
     mat <- slot(object = object, name = s)
     if (!IsMatrixEmpty(x = mat)) {
-      colnames(x = mat) <- sub(
-        pattern = paste0('^', old.key),
-        replacement = value,
-        x = colnames(x = mat)
-      )
+      colnames(x = mat) <- if (is.null(x = colnames(x = mat))) {
+        paste0(value, seq.int(from = 1, to = ncol(x = mat)))
+      } else {
+        sub(
+          pattern = paste0('^', old.key),
+          replacement = value,
+          x = colnames(x = mat)
+        )
+      }
     }
     slot(object = object, name = s) <- mat
   }
@@ -4921,7 +4914,7 @@ ReorderIdent.Seurat <- function(
     yes = function(x) {
       return(max(x) + 1 - x)
     },
-    no = Same
+    no = identity
   )
   new.levels <- names(x = rfxn(x = sort(x = tapply(
     X = data.use,
@@ -4968,16 +4961,16 @@ RenameCells.Assay <- function(object, new.names = NULL, ...) {
   CheckDots(...)
   if (IsSCT(assay = object)) {
     if (is.null(x = Misc(object = object, slot = 'vst.set'))) {
-      suppressWarnings(Misc(object = object, slot = "vst.out")$cells_step1 <- new.names)
-      suppressWarnings(rownames(x = Misc(object = object, slot = "vst.out")$cell_attr) <- new.names)
+      x <- Misc(object = object, slot = "vst.out")
+      suppressWarnings(Misc(object = object, slot = "vst.out")$cells_step1 <- new.names[which(x = x$cells_step1 %in% Cells(x = object))])
+      suppressWarnings(rownames(x = Misc(object = object, slot = "vst.out")$cell_attr) <- new.names[which(x = rownames(x$cell_attr) %in% Cells(x = object))])
     } else{
       suppressWarnings(
         Misc(object, slot = "vst.set") <- lapply(
           X = Misc(object = object, slot = "vst.set"),
           FUN = function(x) {
-            new.names.vst <- new.names[which(x = x$cells_step1 %in% Cells(x = object))]
-            x$cells_step1 <- new.names.vst
-            rownames(x = x$cell_attr) <- new.names.vst
+            x$cells_step1 <- new.names[which(x = x$cells_step1 %in% Cells(x = object))]
+            rownames(x = x$cell_attr) <- new.names[which(x = rownames(x$cell_attr) %in% Cells(x = object))]
             return(x)
           }
         )
@@ -7358,7 +7351,8 @@ subset.Seurat <- function(x, subset, cells = NULL, features = NULL, idents = NUL
   for (assay in assays) {
     assay.features <- features %||% rownames(x = x[[assay]])
     slot(object = x, name = 'assays')[[assay]] <- tryCatch(
-      expr = subset.Assay(x = x[[assay]], cells = cells, features = assay.features),
+      # because subset is also an argument, we need to explictly use the base::subset function
+      expr = base::subset(x = x[[assay]], cells = cells, features = assay.features),
       error = function(e) {
         if (e$message == "Cannot find features provided") {
           return(NULL)