Merge pull request #95 from zhanghao-njmu/develop

fix bugs for CellCorHeatmap

Author: zhanghao-njmu

DESCRIPTION

@@ -54,7 +54,6 @@ Imports:
     sf,
     simplifyEnrichment (>= 1.5.2),
     slingshot,
-    stringr,
     uwot
 Remotes:
     jokergoo/ComplexHeatmap,

NAMESPACE

@@ -111,6 +111,7 @@ export(adata_to_srt)
 export(adjcolors)
 export(as_matrix)
 export(blendcolors)
+export(capitalize)
 export(check_DataType)
 export(check_Python)
 export(check_R)
@@ -456,10 +457,6 @@ importFrom(stats,sd)
 importFrom(stats,setNames)
 importFrom(stats,var)
 importFrom(stats,xtabs)
-importFrom(stringr,str_extract)
-importFrom(stringr,str_replace)
-importFrom(stringr,str_split)
-importFrom(stringr,str_wrap)
 importFrom(utils,askYesNo)
 importFrom(utils,capture.output)
 importFrom(utils,download.file)

R/SCP-analysis.R

@@ -655,7 +655,7 @@ AddModuleScore2 <- function(object, slot = "data", features, pool = NULL, nbin =
 #' )
 #' ClassDimPlot(panc_merge, group.by = c("tech", "celltype", "SubCellType", "Phase"))
 #'
-#' genenames <- make.unique(stringr::str_to_title(rownames(panc8_sub[["RNA"]])))
+#' genenames <- make.unique(capitalize(rownames(panc8_sub[["RNA"]]), force_tolower = TRUE))
 #' panc8_sub <- RenameFeatures(panc8_sub, newnames = genenames, assay = "RNA")
 #' head(rownames(panc8_sub))
 #' panc_merge <- Integration_SCP(

R/SCP-cell_annotation.R

@@ -48,7 +48,7 @@ NULL
 #' # Annotate using single cell RNA-seq data
 #' data("panc8_sub")
 #' # Simply convert genes from human to mouse and preprocess the data
-#' genenames <- make.unique(stringr::str_to_title(rownames(panc8_sub)))
+#' genenames <- make.unique(capitalize(rownames(panc8_sub), force_tolower = TRUE))
 #' panc8_sub <- RenameFeatures(panc8_sub, newnames = genenames)
 #' panc8_sub <- check_srtMerge(panc8_sub, batch = "tech")[["srtMerge"]]
 #'
@@ -509,7 +509,7 @@ RunKNNPredict <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
 #' @examples
 #' data("panc8_sub")
 #' # Simply convert genes from human to mouse and preprocess the data
-#' genenames <- make.unique(stringr::str_to_title(rownames(panc8_sub)))
+#' genenames <- make.unique(capitalize(rownames(panc8_sub), force_tolower = TRUE))
 #' panc8_sub <- RenameFeatures(panc8_sub, newnames = genenames)
 #' panc8_sub <- check_srtMerge(panc8_sub, batch = "tech")[["srtMerge"]]
 #'
@@ -651,7 +651,7 @@ RunScmap <- function(srt_query, srt_ref, ref_group = NULL, method = "scmapCluste
 #' @examples
 #' data("panc8_sub")
 #' # Simply convert genes from human to mouse and preprocess the data
-#' genenames <- make.unique(stringr::str_to_title(rownames(panc8_sub)))
+#' genenames <- make.unique(capitalize(rownames(panc8_sub), force_tolower = TRUE))
 #' panc8_sub <- RenameFeatures(panc8_sub, newnames = genenames)
 #' panc8_sub <- check_srtMerge(panc8_sub, batch = "tech")[["srtMerge"]]
 #'

R/SCP-plot.R

@@ -411,7 +411,7 @@ RecoverCounts <- function(srt, assay = NULL, trans = c("expm1", "exp", "none"),
 #' data("panc8_sub")
 #' head(rownames(panc8_sub))
 #' # Simply convert genes from human to mouse and preprocess the data
-#' genenames <- make.unique(stringr::str_to_title(rownames(panc8_sub)))
+#' genenames <- make.unique(capitalize(rownames(panc8_sub), force_tolower = TRUE))
 #' panc8_rename <- RenameFeatures(panc8_sub, newnames = genenames)
 #' head(rownames(panc8_rename))
 #'

R/SCP-workflow.R

@@ -614,3 +614,25 @@ as_matrix <- function(matrix) {
   colnames(out) <- matrix@Dimnames[[2]]
   return(out)
 }
+
+#' Capitalizes the characters
+#' Making the first letter uppercase
+#'
+#' @param x A vector of character strings to be capitalized.
+#' @param force_tolower Whether to force the remaining letters to be lowercase.
+#' @export
+capitalize <- function(x, force_tolower = FALSE) {
+  if (!inherits(x, "character")) {
+    stop("x must be the type of character.")
+  }
+  if (isTRUE(force_tolower)) {
+    paste(toupper(substr(x, 1, 1)), tolower(substr(x, 2, nchar(x))), sep = "")
+  } else {
+    paste(toupper(substr(x, 1, 1)), substr(x, 2, nchar(x)), sep = "")
+  }
+}
+
+str_wrap <- function(x, width = 80) {
+  x_wrap <- unlist(lapply(x, function(i) paste0(strwrap(i, width = width), collapse = "\n")))
+  return(x_wrap)
+}

R/utils.R

@@ -266,7 +266,7 @@ ClassDimPlot(
 ### Cell projection between single-cell datasets
 
 ```{r RunKNNMap}
-panc8_rename <- RenameFeatures(srt = panc8_sub, newnames = make.unique(stringr::str_to_title(rownames(panc8_sub))), assays = "RNA")
+panc8_rename <- RenameFeatures(srt = panc8_sub, newnames = make.unique(capitalize(rownames(panc8_sub), force_tolower = TRUE)), assays = "RNA")
 pancreas_sub <- RunKNNMap(srt_query = pancreas_sub, srt_ref = panc8_rename, ref_umap = "SeuratUMAP2D")
 ProjectionPlot(
   srt_query = pancreas_sub, srt_ref = panc8_rename,

README.Rmd

@@ -331,7 +331,7 @@ ClassDimPlot(
 ### Cell projection between single-cell datasets
 
 ``` r
-panc8_rename <- RenameFeatures(srt = panc8_sub, newnames = make.unique(stringr::str_to_title(rownames(panc8_sub))), assays = "RNA")
+panc8_rename <- RenameFeatures(srt = panc8_sub, newnames = make.unique(capitalize(rownames(panc8_sub), force_tolower = TRUE)), assays = "RNA")
 pancreas_sub <- RunKNNMap(srt_query = pancreas_sub, srt_ref = panc8_rename, ref_umap = "SeuratUMAP2D")
 ProjectionPlot(
   srt_query = pancreas_sub, srt_ref = panc8_rename,