Further conditioning down the use of Suggests in example/tests

R/generics.R

@@ -479,27 +479,32 @@ setGeneric("normPeak<-", function(x, dataset, check = TRUE, value) standardGener
 #' pbmc2
 #'
 #' \donttest{
-#' sce <- SingleCellExperiment::SingleCellExperiment(
-#'     assays = list(counts = multiSampleMatrix)
-#' )
-#' sce$sample <- pbmc$dataset
-#' pbmc3 <- as.liger(sce, datasetVar = "sample")
-#' pbmc3
+#' if (requireNamespace("SingleCellExperiment", quietly = TRUE)) {
+#'     sce <- SingleCellExperiment::SingleCellExperiment(
+#'         assays = list(counts = multiSampleMatrix)
+#'     )
+#'     sce$sample <- pbmc$dataset
+#'     pbmc3 <- as.liger(sce, datasetVar = "sample")
+#'     pbmc3
+#' }
 #'
-#' seu <- SeuratObject::CreateSeuratObject(multiSampleMatrix)
-#' # Seurat creates variable "orig.ident" by identifying the cell barcode
-#' # prefixes, which is indeed what we need in this case. Users might need
-#' # to be careful and have it confirmed first.
-#' pbmc4 <- as.liger(seu, datasetVar = "orig.ident")
-#' pbmc4
+#' if (requireNamespace("Seurat", quietly = TRUE)) {
+#'     seu <- SeuratObject::CreateSeuratObject(multiSampleMatrix)
+#'     # Seurat creates variable "orig.ident" by identifying the cell barcode
+#'     # prefixes, which is indeed what we need in this case. Users might need
+#'     # to be careful and have it confirmed first.
+#'     pbmc4 <- as.liger(seu, datasetVar = "orig.ident")
+#'     pbmc4
 #'
-#' # As per Seurat V5 updates with layered data, specifically helpful udner the
-#' # scenario of dataset integration. "counts" and etc for each datasets can be
-#' # split into layers.
-#' seu5 <- seu
-#' seu5[["RNA"]] <- split(seu5[["RNA"]], pbmc$dataset)
-#' print(SeuratObject::Layers(seu5))
-#' pbmc5 <- as.liger(seu5)
+#'     # As per Seurat V5 updates with layered data, specifically helpful udner the
+#'     # scenario of dataset integration. "counts" and etc for each datasets can be
+#'     # split into layers.
+#'     seu5 <- seu
+#'     seu5[["RNA"]] <- split(seu5[["RNA"]], pbmc$dataset)
+#'     print(SeuratObject::Layers(seu5))
+#'     pbmc5 <- as.liger(seu5)
+#'     pbmc5
+#' }
 #' }
 as.liger <- function(object, ...) UseMethod("as.liger", object)
 

R/import.R

@@ -23,7 +23,7 @@
 #' common with 10X data). Default \code{"auto"} detects if matrix columns
 #' already has the exact prefix or not. Logical value forces the action.
 #' @param formatType Select preset of H5 file structure. Current available
-#' options are \code{"10X"} and \code{"AnnData"}. Can be either a single
+#' options are \code{"10x"} and \code{"anndata"}. Can be either a single
 #' specification for all datasets or a character vector that match with each
 #' dataset.
 #' @param anndataX The HDF5 path to the raw count data in an H5AD file. See
@@ -59,9 +59,11 @@
 #' lig <- createLiger(list(ctrl = tempPath))
 #'
 #' # Create from other container object
-#' ctrl.seu <- SeuratObject::CreateSeuratObject(ctrl.raw)
-#' stim.seu <- SeuratObject::CreateSeuratObject(stim.raw)
-#' pbmc2 <- createLiger(list(ctrl = ctrl.seu, stim = stim.seu))
+#' if (requireNamespace("SeuratObject", quietly = TRUE)) {
+#'     ctrl.seu <- SeuratObject::CreateSeuratObject(ctrl.raw)
+#'     stim.seu <- SeuratObject::CreateSeuratObject(stim.raw)
+#'     pbmc2 <- createLiger(list(ctrl = ctrl.seu, stim = stim.seu))
+#' }
 createLiger <- function(
         rawData,
         modal = NULL,
@@ -276,7 +278,7 @@ createLigerDataset <- function(
 #' the AnnData was originally created.
 #' @param h5file Filename of an H5 file
 #' @param formatType Select preset of H5 file structure. Default \code{"10X"}.
-#' Current available option is only \code{"10X"}.
+#' Alternatively, we also support \code{"anndata"} for H5AD files.
 #' @param rawData,indicesName,indptrName The path in a H5 file for the raw
 #' sparse matrix data. These three types of data stands for the \code{x},
 #' \code{i}, and \code{p} slots of a \code{\link[Matrix]{dgCMatrix-class}}
@@ -304,7 +306,7 @@ createLigerDataset <- function(
 #' ld <- createH5LigerDataset(tempPath)
 createH5LigerDataset <- function(
         h5file,
-        formatType = "10X",
+        formatType = "10x",
         rawData = NULL,
         normData = NULL,
         scaleData = NULL,
@@ -453,6 +455,18 @@ createH5LigerDataset <- function(
 #' tempPath <- tempfile(fileext = ".rds")
 #' saveRDS(lig, tempPath)
 #' lig <- readLiger(tempPath)
+#'
+#' \dontrun{
+#' # Read a old liger object <= 1.0.1
+#' # Assume the dimensionality reduction method applied was UMAP
+#' # Assume the clustering was derived with Louvain method
+#' lig <- readLiger(
+#'     filename = "path/to/oldLiger.rds",
+#'     dimredName = "UMAP",
+#'     clusterName = "louvain",
+#'     update = TRUE
+#' )
+#' }
 readLiger <- function(
         filename,
         dimredName = "tsne_coords",

tests/testthat/test_visualization.R

@@ -280,15 +280,18 @@ test_that("Plot spatial coordinates", {
 
 context("Sankey")
 test_that("PlotSankey", {
+    skip_if_not_installed("sankey")
     cellMeta(pbmcPlot, "ctrl_cluster", "ctrl") <-
         cellMeta(pbmcPlot, "leiden_cluster", "ctrl")
     cellMeta(pbmcPlot, "stim_cluster", "stim") <-
         cellMeta(pbmcPlot, "leiden_cluster", "stim")
-    grDevices::pdf(file = tempfile(pattern = "fig_", fileext = ".pdf"))
+    pdfName <- tempfile(pattern = "fig_", fileext = ".pdf")
+    grDevices::pdf(file = pdfName)
     expect_no_error({
         plotSankey(pbmcPlot, "ctrl_cluster", "stim_cluster",
                    titles = c("control", "LIGER", "stim"),
                    prefixes = c("c", NA, "s"))
     })
     grDevices::dev.off()
+    if (file.exists(pdfName)) unlink(pdfName)
 })