Merge remote-tracking branch 'upstream/develop'

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: Seurat
-Version: 4.0.0
-Date: 2021-01-27
+Version: 4.0.0.9011
+Date: 2021-02-26
 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>, 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(

NAMESPACE

@@ -40,6 +40,7 @@ S3method(GetImage,VisiumV1)
 S3method(GetTissueCoordinates,STARmap)
 S3method(GetTissueCoordinates,SlideSeq)
 S3method(GetTissueCoordinates,VisiumV1)
+S3method(HVFInfo,SCTAssay)
 S3method(IntegrateEmbeddings,IntegrationAnchorSet)
 S3method(IntegrateEmbeddings,TransferAnchorSet)
 S3method(MappingScore,AnchorSet)

NEWS.md

@@ -1,3 +1,17 @@
+# Seurat develop
+
+## Added
+- Add direction option to `PlotClusterTree()`
+- Add `cols` parameter to `JackStrawPlot()`
+
+## Changes
+- Equality added to differential expression thresholds in `FindMarkers` (e.g, >= logfc.threshold rather than >)
+- `Read10X()` now prepends dataset number for first dataset when reading multiple datasets
+- Bug fix for `subset.AnchorSet()`
+- Bug fix for fold change values in `FindMarkers()` when setting a different pseudocount ([#4111](https://github.com/satijalab/seurat/pull/4111))
+- Bug fix for `RunLDA()` related to proper passing of assay parameter. 
+- When using `order=TRUE` in `SingleDimPlot()`, print NA points under all others.
+
 # Seurat 4.0.0 (2020-01-27) 
 ## Added
 - Expose `FoldChange()` component in `FindMarkers()`. 
@@ -18,6 +32,7 @@
 - Add `AnnotateAnchors()` to aid in AnchorSet interpretation as well as `subset.AnchorSet()`
 - Add flexibility of choice for cell column in `Read10X()`
 - Add rasterization option to `FeatureScatter()` and `VariableFeaturePlot()`
+- Add step1 feature parameters in the SCTModel via `PrepVSTResults()`
 
 ## Changes
 - Default neighbor finding algorithm changed from "rann" to "annoy"
@@ -32,6 +47,7 @@
 - Default rasterization limit in `DimPlot()` and `FeaturePlot()` changed from 50,000 to 100,000
 - `SCTransform()` now returns a formalized `Assay` subclass `SCTAssay()`
 - When using `normalization.method='SCT'` in `FindTransferAnchors()`, normalize query using reference SCT model when possible.
+- Change default Neighbor name in `FindNeighbors` to `Assay.nn`
 
 ## Removed
 - `CreateGeneActivityMatrix` replaced by `Signac::GeneActivity()`

R/clustering.R

@@ -559,7 +559,11 @@ FindNeighbors.default <- function(
   # find the k-nearest neighbors for each single cell
   if (!distance.matrix) {
     if (verbose) {
-      message("Computing nearest neighbor graph")
+      if (return.neighbor) {
+        message("Computing nearest neighbors")
+      } else {
+        message("Computing nearest neighbor graph")
+      }
     }
     nn.ranked <- NNHelper(
       data = object,
@@ -709,6 +713,11 @@ FindNeighbors.dist <- function(
 #' @param do.plot Plot SNN graph on tSNE coordinates
 #' @param graph.name Optional naming parameter for stored (S)NN graph
 #' (or Neighbor object, if return.neighbor = TRUE). Default is assay.name_(s)nn.
+#' To store both the neighbor graph and the shared nearest neighbor (SNN) graph,
+#' you must supply a vector containing two names to the \code{graph.name}
+#' parameter. The first element in the vector will be used to store the nearest
+#' neighbor (NN) graph, and the second element used to store the SNN graph. If
+#' only one name is supplied, only the NN graph is stored.
 #'
 #' @importFrom igraph graph.adjacency plot.igraph E
 #'
@@ -787,7 +796,15 @@ FindNeighbors.Seurat <- function(
   if (length(x = neighbor.graphs) == 1) {
     neighbor.graphs <- list(nn = neighbor.graphs)
   }
-  graph.name <- graph.name %||% paste0(assay, "_", names(x = neighbor.graphs))
+  graph.name <- graph.name %||%
+    if (return.neighbor) {
+      paste0(assay, ".", names(x = neighbor.graphs))
+    } else {
+      paste0(assay, "_", names(x = neighbor.graphs))
+    }
+  if (length(x = graph.name) == 1) {
+    message("Only one graph name supplied, storing nearest-neighbor graph only")
+  }
   for (ii in 1:length(x = graph.name)) {
     if (inherits(x = neighbor.graphs[[ii]], what = "Graph")) {
       DefaultAssay(object = neighbor.graphs[[ii]]) <- assay

R/convenience.R

@@ -32,6 +32,7 @@ PCAPlot <- function(object, ...) {
 
 #' @rdname SpatialPlot
 #' @concept convenience
+#' @concept spatial
 #' @export
 #'
 SpatialDimPlot <- function(
@@ -82,6 +83,7 @@ SpatialDimPlot <- function(
 
 #' @rdname SpatialPlot
 #' @concept convenience
+#' @concept spatial
 #' @export
 #'
 SpatialFeaturePlot <- function(

R/differential_expression.R

@@ -513,14 +513,14 @@ FindMarkers.default <- function(
   # feature selection (based on percentages)
   alpha.min <- pmax(fc.results$pct.1, fc.results$pct.2)
   names(x = alpha.min) <- rownames(x = fc.results)
-  features <- names(x = which(x = alpha.min > min.pct))
+  features <- names(x = which(x = alpha.min >= min.pct))
   if (length(x = features) == 0) {
     warning("No features pass min.pct threshold; returning empty data.frame")
     return(fc.results[features, ])
   }
   alpha.diff <- alpha.min - pmin(fc.results$pct.1, fc.results$pct.2)
   features <- names(
-    x = which(x = alpha.min > min.pct & alpha.diff > min.diff.pct)
+    x = which(x = alpha.min >= min.pct & alpha.diff >= min.diff.pct)
   )
   if (length(x = features) == 0) {
     warning("No features pass min.diff.pct threshold; returning empty data.frame")
@@ -531,9 +531,9 @@ FindMarkers.default <- function(
     total.diff <- fc.results[, 1] #first column is logFC
     names(total.diff) <- rownames(fc.results)
     features.diff <- if (only.pos) {
-      names(x = which(x = total.diff > logfc.threshold))
+      names(x = which(x = total.diff >= logfc.threshold))
     } else {
-      names(x = which(x = abs(x = total.diff) > logfc.threshold))
+      names(x = which(x = abs(x = total.diff) >= logfc.threshold))
     }
     features <- intersect(x = features, y = features.diff)
     if (length(x = features) == 0) {
@@ -627,6 +627,7 @@ FindMarkers.Assay <- function(
     cells.1 = cells.1,
     cells.2 = cells.2,
     features = features,
+    pseudocount.use = pseudocount.use,
     mean.fxn = mean.fxn,
     fc.name = fc.name,
     base = base
@@ -680,6 +681,7 @@ FindMarkers.DimReduc <- function(
   min.cells.group = 3,
   pseudocount.use = 1,
   mean.fxn = rowMeans,
+  fc.name = NULL,
   ...
 
 ) {
@@ -705,7 +707,9 @@ FindMarkers.DimReduc <- function(
     object = object,
     cells.1 = cells.1,
     cells.2 = cells.2,
-    features = features
+    features = features,
+    mean.fxn = mean.fxn,
+    fc.name = fc.name
   )
   # subsample cell groups if they are too large
   if (max.cells.per.ident < Inf) {

R/integration.R

@@ -492,7 +492,8 @@ FindIntegrationAnchors <- function(
 #' }
 #' @param reference.reduction Name of dimensional reduction to use from the
 #' reference if running the pcaproject workflow. Optionally enables reuse of
-#' precomputed reference dimensional reduction.
+#' precomputed reference dimensional reduction. If NULL (default), use a PCA
+#' computed on the reference object.
 #' @param project.query Project the PCA from the query dataset onto the
 #' reference. Use only in rare cases where the query dataset has a much larger
 #' cell number, but the reference dataset has a unique assay for transfer. In
@@ -627,25 +628,25 @@ FindTransferAnchors <- function(
   if (normalization.method == "SCT") {
       # ensure all residuals required are computed
       query <- suppressWarnings(expr = GetResidual(object = query, assay = query.assay, features = features, verbose = FALSE))
-        if (is.null(x = reference.reduction)) {
-      reference <- suppressWarnings(expr = GetResidual(object = reference, assay = reference.assay, features = features, verbose = FALSE))
-      features <- intersect(
-        x = features,
-        y = intersect(
-          x = rownames(x = GetAssayData(object = query[[query.assay]], slot = "scale.data")),
-          y = rownames(x = GetAssayData(object = reference[[reference.assay]], slot = "scale.data"))
+      if (is.null(x = reference.reduction)) {
+        reference <- suppressWarnings(expr = GetResidual(object = reference, assay = reference.assay, features = features, verbose = FALSE))
+        features <- intersect(
+          x = features,
+          y = intersect(
+            x = rownames(x = GetAssayData(object = query[[query.assay]], slot = "scale.data")),
+            y = rownames(x = GetAssayData(object = reference[[reference.assay]], slot = "scale.data"))
+          )
         )
-      )
-      reference[[reference.assay]] <- as(
-        object = CreateAssayObject(
-          data = GetAssayData(object = reference[[reference.assay]], slot = "scale.data")[features, ]),
-        Class = "SCTAssay"
-      )
-      reference <- SetAssayData(
-        object = reference,
-        slot = "scale.data",
-        assay = reference.assay,
-        new.data =  as.matrix(x = GetAssayData(object = reference[[reference.assay]], slot = "data"))
+        reference[[reference.assay]] <- as(
+          object = CreateAssayObject(
+            data = GetAssayData(object = reference[[reference.assay]], slot = "scale.data")[features, ]),
+          Class = "SCTAssay"
+        )
+        reference <- SetAssayData(
+          object = reference,
+          slot = "scale.data",
+          assay = reference.assay,
+          new.data =  as.matrix(x = GetAssayData(object = reference[[reference.assay]], slot = "data"))
       )
     }
     query[[query.assay]] <- as(
@@ -2675,6 +2676,7 @@ TransferData <- function(
 #' @rdname AnnotateAnchors
 #' @export
 #' @method AnnotateAnchors default
+#' @concept integration
 #'
 AnnotateAnchors.default <- function(
   anchors,

R/mixscape.R

@@ -532,7 +532,7 @@ RunLDA.default <- function(
 #'
 RunLDA.Assay <- function(
   object,
-  assay,
+  assay = NULL,
   labels,
   features = NULL,
   verbose = TRUE,
@@ -595,6 +595,7 @@ RunLDA.Seurat <- function(
   assay.data <- GetAssay(object = object, assay = assay)
   reduction.data <- RunLDA(
     object = assay.data,
+    assay = assay,
     labels = labels,
     features = features,
     verbose = verbose,