Merge branch 'develop' of https://github.com/satijalab/seurat-private …

…into lis_vignette_updates

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: Seurat
-Version: 5.0.0.9003
-Date: 2023-10-23
+Version: 5.0.0.9007
+Date: 2023-11-15
 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(

NEWS.md

@@ -3,7 +3,8 @@
 ## Changes
 
 - Fixed `SCTransform.StdAssay` to pass extra arguments to `sctransform::vst()`. Fixes [#875](https://github.com/satijalab/seurat/issues/7998)
-
+- Fixed [PercentageFeatureSet layer calling](https://github.com/satijalab/seurat/issues/8009)
+- Fixed [cell highlighting](https://github.com/satijalab/seurat/pull/7914) 
 
 # Seurat 5.0.0 (2023-10-25)
 

R/integration.R

@@ -2621,19 +2621,19 @@ MappingScore.AnchorSet <- function(
   combined.object <- slot(object = anchors, name = "object.list")[[1]]
   combined.object <- RenameCells(
     object = combined.object,
-    new.names = unname(obj = sapply(
+    new.names = unname(obj = make.unique(sapply(
       X = Cells(x = combined.object),
       FUN = RemoveLastField
-    ))
+    )))
   )
-  query.cells <- sapply(
+  query.cells <- make.unique(sapply(
     X = slot(object = anchors, name = "query.cells"),
     FUN = RemoveLastField
-  )
-  ref.cells <- sapply(
+  ))
+  ref.cells <- make.unique(sapply(
     X = slot(object = anchors, name = "reference.cells"),
     FUN = RemoveLastField
-  )
+  ))
   query.embeddings <- Embeddings(object = subset(
     x = combined.object[["pcaproject.l2"]],
     cells = query.cells

R/utilities.R

@@ -1170,7 +1170,7 @@ PercentageFeatureSet <- function(
     warn(message = "Both pattern and features provided. Pattern is being ignored.")
   }
   percent.featureset <- list()
-  layers <- Layers(object = object, pattern = "counts")
+  layers <- Layers(object = object, search = "counts")
   for (i in seq_along(along.with = layers)) {
     layer <- layers[i]
     features.layer <- features %||% grep(
@@ -1462,9 +1462,8 @@ PseudobulkExpression.Seurat <- function(
     )
     colnames(category.matrix) <- col.names
     inform(
-      message = paste0("group.by variable `", group.by[1],
-      "` starts with a number, appending `g` to `", group.by[1],
-      "` variable to ensure\nvalid variable names"),
+      message = paste0("First group.by variable `", group.by[1],
+      "` starts with a number, appending `g` to ensure valid variable names"),
       .frequency = "regularly",
       .frequency_id = "PseudobulkExpression"
     )

R/visualization.R

@@ -921,7 +921,9 @@ DimPlot <- function(
     data[, shape.by] <- object[[shape.by, drop = TRUE]]
   }
   if (!is.null(x = split.by)) {
-    data[, split.by] <- FetchData(object = object, vars = split.by)[split.by]
+    split <- FetchData(object = object, vars = split.by, clean=TRUE)[split.by]
+    data <- data[rownames(split),]
+    data[, split.by] <- split
   }
   if (isTRUE(x = shuffle)) {
     set.seed(seed = seed)
@@ -2045,7 +2047,9 @@ FeatureScatter <- function(
     }
   }
   if (!is.null(x = split.by)) {
-    data[, split.by] <- FetchData(object = object, vars = split.by)[split.by]
+    split <- FetchData(object = object, vars = split.by, clean=TRUE)[split.by]
+    data <- data[rownames(split),]
+    data[, split.by] <- split
   }
   plots <- lapply(
     X = group.by,
@@ -7895,7 +7899,7 @@ SetHighlight <- function(
 
   # Check for raster
   if (isTRUE(x = raster)) {
-    size <- size[1]
+    size <- sizes.highlight[1]
   }
 
   plot.order <- sort(x = unique(x = highlight), na.last = TRUE)
@@ -8200,7 +8204,7 @@ SingleDimPlot <- function(
   raster <- raster %||% (nrow(x = data) > 1e5)
   pt.size <- pt.size %||% AutoPointSize(data = data, raster = raster)
 
-  if (!is.null(x = cells.highlight) && pt.size == AutoPointSize(data = data, raster = raster) && sizes.highlight != pt.size && isTRUE(x = raster)) {
+  if (!is.null(x = cells.highlight) && pt.size != AutoPointSize(data = data, raster = raster) && sizes.highlight != pt.size && isTRUE(x = raster)) {
     warning("When `raster = TRUE` highlighted and non-highlighted cells must be the same size. Plot will use the value provided to 'sizes.highlight'.")
   }