Fixes for Seurat new version

DESCRIPTION

@@ -31,6 +31,7 @@ Suggests:
     rgl,
     rmarkdown,
     Seurat,
+    SeuratObject,
     SingleCellExperiment,
     SummarizedExperiment,
     testthat (>= 3.0.0)

R/binary.R

@@ -127,8 +127,8 @@ plotBinary.default <- function(
     }
 }
 
-#' @param slot For "Seurat" method, choose from \code{"counts"},
-#' \code{"data"} or \code{"scale.data"}. Default \code{"counts"}.
+#' @param layer For "Seurat" method, which layer of the assay to be used.
+#' Default \code{"counts"}.
 #' @param assay For "Seurat" method, the specific assay to get data from.
 #' Default \code{NULL} to the default assay.
 #' @rdname plotBinary
@@ -140,25 +140,21 @@ plotBinary.default <- function(
 #' if (FALSE) {
 #'     srt <- CreateSeuratObject(rnaRaw)
 #'     Idents(srt) <- rnaCluster
-#'     srt <- colNormalize(srt)
 #'     gene <- selectTopFeatures(srt, vertices = c("OS", "RE"))
-#'     srt <- colNormalize(srt, scaleFactor = 1e4, log = TRUE)
 #'     plotBinary(srt, features = gene, vertices = c("OS", "RE"))
 #' }
 plotBinary.Seurat <- function(
         x,
-        slot = c("counts", "data", "scale.data"),
+        layer = "counts",
         assay = NULL,
         clusterVar = NULL,
         processed = FALSE,
         ...
 ) {
-    slot <- match.arg(slot)
-    values <- .getSeuratData(x, slot = slot, assay = assay,
+    values <- .getSeuratData(x, layer = layer, assay = assay,
                              clusterVar = clusterVar)
     if (missing(processed)) {
-        if (slot == "counts") processed <- FALSE
-        else processed <- TRUE
+        processed <- layer != "counts"
     }
     plotBinary(x = values[[1]], clusterVar = values[[2]], processed = processed,
                ...)
@@ -188,8 +184,7 @@ plotBinary.SingleCellExperiment <- function(
 ) {
     values <- .getSCEData(x, assay.type = assay.type, clusterVar = clusterVar)
     if (missing(processed)) {
-        if (assay.type == "counts") processed <- FALSE
-        else processed <- TRUE
+        processed <- assay.type != "counts"
     }
     plotBinary(values[[1]], clusterVar = values[[2]], processed = processed,
                ...)

R/normalize.R

@@ -34,8 +34,8 @@ colNormalize.default <- function(x, scaleFactor = NULL, log = FALSE, ...) {
 }
 
 #' @rdname colNormalize
-#' @param slot For "Seurat" method, choose from \code{"counts"},
-#' \code{"data"} or \code{"scale.data"}. Default \code{"counts"}.
+#' @param layer For "Seurat" method, which layer of the assay to be used.
+#' Default \code{"counts"}.
 #' @param assay For "Seurat" method, the specific assay to get data from.
 #' Default \code{NULL} to the default assay.
 #' @return A Seurat object with normalized data in the specified slot of the
@@ -55,10 +55,10 @@ colNormalize.Seurat <- function(
     scaleFactor = NULL,
     log = FALSE,
     assay = NULL,
-    slot = "counts",
+    layer = "counts",
     ...
 ) {
-    value <- .getSeuratData(x, assay = assay, slot = slot, clusterVar = NULL)
+    value <- .getSeuratData(x, assay = assay, layer = layer, clusterVar = NULL)
     mat <- value[[1]]
     norm <- colNormalize.default(mat, scaleFactor = scaleFactor, log = log)
     x <- Seurat::SetAssayData(x, slot = "data", assay = assay, new.data = norm)

R/quaternary.R

@@ -155,8 +155,8 @@ plotQuaternary.default <- function(
     }
 }
 
-#' @param slot For "Seurat" method, choose from \code{"counts"},
-#' \code{"data"} or \code{"scale.data"}. Default \code{"counts"}.
+#' @param layer For "Seurat" method, which layer of the assay to be used.
+#' Default \code{"counts"}.
 #' @param assay For "Seurat" method, the specific assay to get data from.
 #' Default \code{NULL} to the default assay.
 #' @rdname plotQuaternary
@@ -174,18 +174,16 @@ plotQuaternary.default <- function(
 #' }
 plotQuaternary.Seurat <- function(
         x,
-        slot = c("counts", "data", "scale.data"),
+        layer = "counts",
         assay = NULL,
         clusterVar = NULL,
         processed = FALSE,
         ...
 ) {
-    slot <- match.arg(slot)
-    values <- .getSeuratData(x, slot = slot, assay = assay,
+    values <- .getSeuratData(x, layer = layer, assay = assay,
                              clusterVar = clusterVar)
     if (missing(processed)) {
-        if (slot == "counts") processed <- FALSE
-        else processed <- TRUE
+        processed <- layer != "counts"
     }
     plotQuaternary(values[[1]], clusterVar = values[[2]], processed = processed,
                    ...)
@@ -216,8 +214,7 @@ plotQuaternary.SingleCellExperiment <- function(
 ) {
     values <- .getSCEData(x, assay.type = assay.type, clusterVar = clusterVar)
     if (missing(processed)) {
-        if (assay.type == "counts") processed <- FALSE
-        else processed <- TRUE
+        processed <- assay.type != "counts"
     }
     plotQuaternary(values[[1]], clusterVar = values[[2]], processed = processed,
                    ...)

R/selectTopFeatures.R

@@ -111,8 +111,8 @@ selectTopFeatures.default <- function(
 #' @rdname selectTopFeatures
 #' @export
 #' @method selectTopFeatures Seurat
-#' @param slot Slot name of the Seurat object to be used. Default
-#' \code{"counts"}.
+#' @param layer For "Seurat" method, which layer of the assay to be used.
+#' Default \code{"counts"}.
 #' @param assay Assay name of the Seurat object to be used. Default \code{NULL}.
 #' @examples
 #'
@@ -128,16 +128,16 @@ selectTopFeatures.Seurat <- function(
     clusterVar = NULL,
     vertices,
     assay = NULL,
-    slot = c("counts", "data", "scale.data"),
+    layer = "counts",
+    processed = FALSE,
     ...
 ) {
-    slot <- match.arg(slot)
-    value <- .getSeuratData(x, assay = assay, slot = slot,
+    value <- .getSeuratData(x, assay = assay, layer = layer,
                             clusterVar = clusterVar)
     mat <- value[[1]]
     clusterVar <- value[[2]]
 
-    processed <- ifelse(slot != "counts", TRUE, FALSE)
+    if (missing(processed)) processed <- layer != "counts"
     selectTopFeatures(mat, clusterVar, vertices, processed = processed, ...)
 }
 
@@ -160,12 +160,13 @@ selectTopFeatures.SingleCellExperiment <- function(
     clusterVar = NULL,
     vertices,
     assay.type = "counts",
+    processed = FALSE,
     ...
 ) {
     value <- .getSCEData(x, assay.type = assay.type, clusterVar = clusterVar)
     mat <- value[[1]]
     clusterVar <- value[[2]]
-    processed <- ifelse(assay.type == "counts", FALSE, TRUE)
+    if (missing(processed)) processed <- assay.type != "counts"
     selectTopFeatures(mat, clusterVar, vertices, processed = processed, ...)
 }
 

R/ternary.R

@@ -169,8 +169,8 @@ plotTernary.default <- function(
     }
 }
 
-#' @param slot For "Seurat" method, choose from \code{"counts"},
-#' \code{"data"} or \code{"scale.data"}. Default \code{"counts"}.
+#' @param layer For "Seurat" method, which layer of the assay to be used.
+#' Default \code{"counts"}.
 #' @param assay For "Seurat" method, the specific assay to get data from.
 #' Default \code{NULL} to the default assay.
 #' @rdname plotTernary
@@ -187,18 +187,16 @@ plotTernary.default <- function(
 #' }
 plotTernary.Seurat <- function(
         x,
-        slot = c("counts", "data", "scale.data"),
+        layer = "counts",
         assay = NULL,
         clusterVar = NULL,
         processed = FALSE,
         ...
 ) {
-    slot <- match.arg(slot)
-    values <- .getSeuratData(x, slot = slot, assay = assay,
+    values <- .getSeuratData(x, layer = layer, assay = assay,
                              clusterVar = clusterVar)
     if (missing(processed)) {
-        if (slot == "counts") processed <- FALSE
-        else processed <- TRUE
+        processed <- layer != "counts"
     }
     plotTernary(values[[1]], clusterVar = values[[2]], processed = processed,
                 ...)
@@ -228,8 +226,7 @@ plotTernary.SingleCellExperiment <- function(
 ) {
     values <- .getSCEData(x, assay.type = assay.type, clusterVar = clusterVar)
     if (missing(processed)) {
-        if (assay.type == "counts") processed <- FALSE
-        else processed <- TRUE
+        processed <- assay.type != "counts"
     }
     plotTernary(values[[1]], clusterVar = values[[2]], processed = processed,
                 ...)
@@ -395,8 +392,9 @@ plotTernary.simMat <- function(
             p <- p +
                 annotate("segment", x = subcoords[,1], y = subcoords[,2],
                          xend = subcoords[,3], yend = subcoords[,4],
-                         color = labelColors[i], size = arrowLinewidth,
-                         arrow = arrow(angle = arrowAngle, length = unit(arrowLen, "cm"),
+                         color = labelColors[i], linewidth = arrowLinewidth,
+                         arrow = arrow(angle = arrowAngle,
+                                       length = unit(arrowLen, "cm"),
                                        type = "closed"))
         }
     }

R/util.R

@@ -1,3 +1,8 @@
+`%||%` <- function(x, y) {
+    if (is.null(x)) y
+    else x
+}
+
 .scaleMinMax <- function(x) {
     if (all(x == 0)) return(x)
     else {
@@ -69,18 +74,25 @@ is.rawCounts <- function(x) {
 .getSeuratData <- function(
         object,
         assay = NULL,
-        slot = "data",
+        layer = "counts",
         clusterVar = NULL
 ) {
     if (!requireNamespace("Seurat", quietly = TRUE)) {
         stop("Please install package 'Seurat' before interacting with a ", # nocov
              "Seurat object.\ninstall.packages(\"Seurat\")") # nocov
     }
-    mat <- Seurat::GetAssayData(object, slot = slot, assay = assay)
-    if (is.null(clusterVar)) clusterVar <- Seurat::Idents(object)
-    else if (length(clusterVar) == 1) {
+    if (!requireNamespace("SeuratObject", quietly = TRUE)) {
+        stop("Please install package 'SeuratObject' before interacting with a ", # nocov
+             "Seurat object.\ninstall.packages(\"Seurat\")") # nocov
+    }
+    mat <- SeuratObject::LayerData(object, layer = layer, assay = assay)
+    clusterVar <- clusterVar %||% SeuratObject::Idents(object)
+    if (length(clusterVar) == 1) {
         clusterVar <- object[[clusterVar]][[1]]
     }
+    if (length(clusterVar) != ncol(object)) {
+        stop("Invalid `clusterVar`.")
+    }
     return(list(mat, clusterVar))
 }
 
@@ -100,13 +112,20 @@ is.rawCounts <- function(x) {
              "\nBiocManager::install(\"SummarizedExperiment\")") # nocov
     }
     mat <- SummarizedExperiment::assay(object, assay.type)
+
     if (is.null(clusterVar)) {
         if (inherits(object, "SingleCellExperiment")) {
             clusterVar <- SingleCellExperiment::colLabels(object)
+        } else {
+            stop("No default labels available for this SCE object.")
         }
-    } else if (length(clusterVar) == 1) {
+    }
+    if (length(clusterVar) == 1) {
         clusterVar <- SummarizedExperiment::colData(object)[[clusterVar]]
     }
+    if (length(clusterVar) != ncol(object)) {
+        stop("Invalid `clusterVar`.")
+    }
     return(list(mat, clusterVar))
 }