v1.2.3

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: Seurat.utils
 Title: Seurat.utils - utility functions for Seurat
-Version: 1.2.2
+Version: 1.2.3
 Authors@R: 
     person("Abel", "Vertesy", , "[email protected]", role = c("aut", "cre"))
 Author: Abel Vertesy <[email protected]> [aut, cre]
@@ -50,7 +50,7 @@ Imports:
 Suggests: 
     SoupX
 Encoding: UTF-8
-Packaged: 2021-11-27 23:09:18
+Packaged: 2021-11-30 23:24:31
 Repository: CRAN
 Roxygen: list(markdown = TRUE)
 RoxygenNote: 7.1.2

Development/Create_the_Seurat.utils_Package.v0.1.0.R

@@ -36,7 +36,7 @@ DESCRIPTION <- list("Title" = "Seurat.utils - utility functions for Seurat"
     Functions allow the automation / multiplexing of plotting, 3D plotting, visualisation of statistics &
     QC, interaction with the Seurat object, etc. Some functionalities require functions from CodeAndRoll and MarkdownReports libraries."
     , "License" = "GPL-3 + file LICENSE"
-    , "Version" = "1.2.2"
+    , "Version" = "1.2.3"
     , "Packaged" =  Sys.time()
     , "Repository" =  "CRAN"
     , "Depends" =  "Stringendo, CodeAndRoll2, ggExpress, ggplot2"

Development/Development.bac

@@ -38,7 +38,7 @@ SmallestNonAboveX <- function(vec, X = 0) { # replace small values with the next
 #' @param p_val_min PARAM_DESCRIPTION, Default: 1e-25
 #' @param pval_scaling PARAM_DESCRIPTION, Default: 0.001
 #' @param colP PARAM_DESCRIPTION, Default: 'p_val'
-#' @param colLFC PARAM_DESCRIPTION, Default: grepv(pattern = c("avg_logFC|avg_log2FC"), x = colnames(df),
+#' @param colLFC PARAM_DESCRIPTION, Default: CodeAndRoll2::grepv(pattern = c("avg_logFC|avg_log2FC"), x = colnames(df),
 #'    perl = T)
 #' @examples
 #' \dontrun{
@@ -48,7 +48,7 @@ SmallestNonAboveX <- function(vec, X = 0) { # replace small values with the next
 #' }
 #' @export
 Add.DE.combined.score <- function(df = df.markers, p_val_min = 1e-25, pval_scaling = 0.001, colP = "p_val"
-                                  , colLFC = grepv(pattern = c("avg_logFC|avg_log2FC"), x = colnames(df), perl = T)
+                                  , colLFC = CodeAndRoll2::grepv(pattern = c("avg_logFC|avg_log2FC"), x = colnames(df), perl = T)
                                   # , colLFC = "avg_log2FC"
 ) { # Score = -LOG10(p_val) * avg_log2FC
   p_cutoff <- SmallestNonAboveX(vec = df[[colP]], X = p_val_min)
@@ -253,7 +253,7 @@ AutoLabel.KnownMarkers <- function(obj = combined.obj, topN =1, res = 0.5 # Crea
                                    , df_markers = obj@misc$"df.markers"[[paste0("res.",res)]] ) {
   stopifnot(!is.null("df_markers"))
 
-  lfcCOL <- grepv(pattern = c("avg_logFC|avg_log2FC"), x = colnames(df_markers), perl = T)
+  lfcCOL <- CodeAndRoll2::grepv(pattern = c("avg_logFC|avg_log2FC"), x = colnames(df_markers), perl = T)
   keep <- unique(c(lfcCOL, 'p_val_adj', 'cluster', order.by, 'gene'  ))
 
 
@@ -684,7 +684,7 @@ add.meta.fraction <- function(col.name = "percent.mito", gene.symbol.pattern = c
 
   geneset <- check.genes(list.of.genes = gene.set, obj = obj)
   total_expr <- Matrix::colSums(GetAssayData(object = obj))
-  genes.matching <- if (!isFALSE(gene.set)) intersect(gene.set, rownames(obj)) else grepv(pattern = gene.symbol.pattern, x = rownames(obj))
+  genes.matching <- if (!isFALSE(gene.set)) intersect(gene.set, rownames(obj)) else CodeAndRoll2::grepv(pattern = gene.symbol.pattern, x = rownames(obj))
 
   genes.expr = GetAssayData(object = obj)[genes.matching, ]
   target_expr <- if (length(genes.matching) >1) Matrix::colSums(genes.expr) else genes.expr
@@ -712,7 +712,7 @@ add.meta.fraction <- function(col.name = "percent.mito", gene.symbol.pattern = c
 #' @export
 GetClusteringRuns <- function(obj = combined.obj, res = F, pat = "*snn_res.*[0-9]$") { # Get Clustering Runs: metadata column names
   if (res) pat = gsub(x = pat, pattern = '\\[.*\\]', replacement = res)
-  clustering.results <- grepv(x = colnames([email protected]), pattern = pat)
+  clustering.results <- CodeAndRoll2::grepv(x = colnames([email protected]), pattern = pat)
   if ( identical(clustering.results, character(0)) ) warning("No matching column found!")
   return(clustering.results)
 }
@@ -737,7 +737,7 @@ GetNamedClusteringRuns <- function(obj = combined.obj  # Get Clustering Runs: me
                                    , res = c(F, 0.5)[1], topgene = F, pat = "^cl.names.Known.*[0,1]\\.[0-9]$") {
   if (res) pat = gsub(x = pat, pattern = '\\[.*\\]', replacement = res)
   if (topgene) pat = gsub(x = pat, pattern = 'Known', replacement = 'top')
-  clustering.results <- grepv(x = colnames([email protected]), pattern = pat)
+  clustering.results <- CodeAndRoll2::grepv(x = colnames([email protected]), pattern = pat)
   if ( identical(clustering.results, character(0)) ) {
     print("Warning: NO matching column found! Trying GetClusteringRuns(..., pat = '*_res.*[0,1]\\.[0-9]$)")
     clustering.results <- GetClusteringRuns(obj = obj, res = F, pat = "*_res.*[0,1]\\.[0-9]$")
@@ -762,7 +762,7 @@ GetNamedClusteringRuns <- function(obj = combined.obj  # Get Clustering Runs: me
 #' @export
 GetOrderedClusteringRuns <- function(obj = combined.obj, res = F, pat = "*snn_res.*[0,1]\\.[0-9]\\.ordered$") { # Get Clustering Runs: metadata column names
   if (res) pat = gsub(x = pat, pattern = '\\[.*\\]', replacement = res)
-  clustering.results <- grepv(x = colnames([email protected]), pattern = pat)
+  clustering.results <- CodeAndRoll2::grepv(x = colnames([email protected]), pattern = pat)
   if ( identical(clustering.results, character(0)) ) warning("No matching column found!")
   return(clustering.results)
 }
@@ -944,6 +944,7 @@ seu.map.and.add.new.ident.to.meta <- function(obj = combined.obj, ident.table =
 #' }
 #' @export
 #' @importFrom Stringendo percentage_formatter
+
 calc.cluster.averages <- function(col_name = "Score.GO.0006096"
                                   , plot.UMAP.too = TRUE
                                   , return.plot = F
@@ -959,6 +960,7 @@ calc.cluster.averages <- function(col_name = "Score.GO.0006096"
                                   , filter = c(FALSE, 'above', 'below')[1]
                                   , ylab.text = paste("Cluster", stat, "score")
                                   , title = paste("Cluster", stat, col_name)
+                                  , prefix.cl.names= FALSE
                                   , report = TRUE
                                   , subtitle = NULL
                                   , width = 8, height =6
@@ -990,7 +992,7 @@ calc.cluster.averages <- function(col_name = "Score.GO.0006096"
 
   if (simplify) {
     av.score <- df.summary[[stat]]
-    names(av.score) <- ppp("cl",df.summary[[1]])
+    names(av.score) <- if ( !isFALSE(prefix.cl.names)) ppp("cl",df.summary[[1]]) else df.summary[[1]]
     av.score <- sortbyitsnames(av.score)
     if (scale.zscore) av.score <- (scale(av.score)[,1])
 
@@ -1018,7 +1020,7 @@ calc.cluster.averages <- function(col_name = "Score.GO.0006096"
       } else {
         p <- qbarplot(vec = av.score, save = F
                       , hline = cutoff
-                      , title = title
+                      , plotname = title
                       , suffix = quantile.thr
                       , subtitle = subtitle
                       , ylab = ylab.text
@@ -1050,6 +1052,7 @@ calc.cluster.averages <- function(col_name = "Score.GO.0006096"
   }
 }
 
+
 # _________________________________________________________________________________________________
 #' @title seu.add.meta.from.table
 #' @description Add multiple new metadata columns to a Seurat object from a table. #
@@ -1220,6 +1223,25 @@ fix.orig.ident <- function(obj = merged.obj) {
 set.all.genes <- function(obj = combined.obj) iprint("Use calc.q90.Expression.and.set.all.genes()")
 
 
+
+# _________________________________________________________________________________________________
+#' @title set.mm
+#' @description Helps to find metadata columns. It creates a list with the names of of '[email protected]'.
+#' @param obj Seurat object, Default: combined.obj
+#' @examples
+#' \dontrun{
+#' if(interactive()){
+#'  set.mm(); mm
+#'  }
+#' }
+#' @export
+set.mm <- function(obj = combined.obj) {
+  mm <- CodeAndRoll2::list.fromNames(colnames([email protected]))
+  assign(x = 'mm', value = mm, envir = as.environment(1))
+}
+
+
+
 # _________________________________________________________________________________________________
 #' @title recall.all.genes
 #' @description all.genes set by calc.q90.Expression.and.set.all.genes() #
@@ -3296,14 +3318,17 @@ CellFractionsBarplot2 <- function(obj = combined.obj
 #'  }
 #' }
 #' @export barplot.cells.per.cluster
-barplot.cells.per.cluster <- function(obj = combined.obj, ident =  "cl.names.KnownMarkers.0.5", sort = F) {
+barplot.cells.per.cluster <- function(obj = combined.obj
+                                      , ident =  "cl.names.KnownMarkers.0.5"
+                                      , sort = F, ...) {
   cell.per.cluster <- (table(obj[[ident]][,1]))
   if (sort) cell.per.cluster <- sort(cell.per.cluster)
   qbarplot(cell.per.cluster, subtitle = ident, suffix = ident
            , col = rainbow(length(cell.per.cluster))
            , xlab.angle = 45
            # , col = getClusterColors(ident = ident, show = T)
-           , palette_use = NULL, )
+           , palette_use = NULL
+           , ...)
 }
 
 
@@ -3606,7 +3631,7 @@ plot.Gene.Cor.Heatmap <- function(genes = WU.2017.139.IEGsf
 
   if (is.null(cor.mat)) {
     iprint(slotname_cor.mat, " not found in @misc.")
-    iprint("Correlation slots present in @misc:",grepv(names(obj@misc), pattern = "^cor"))
+    iprint("Correlation slots present in @misc:", CodeAndRoll2::grepv(names(obj@misc), pattern = "^cor"))
 
     # Calculate ------------------------------------
     if (calc.COR) {
@@ -3904,7 +3929,7 @@ Convert10Xfolders <- function(InputDir # Take a parent directory with a number o
 
   # finOrig <- list.dirs(InputDir, recursive = subdirs)
   finOrig <- list.dirs.depth.n(InputDir, depth = 2)
-  fin <- grepv(x = finOrig, pattern = folderPattern, perl = regex)
+  fin <- CodeAndRoll2::grepv(x = finOrig, pattern = folderPattern, perl = regex)
 
   iprint(length(fin), "samples found.")
   if (length(fin)) {
@@ -3960,7 +3985,7 @@ Convert10Xfolders.old <- function(InputDir # Take a parent directory with a numb
                                   , folderPattern = c("filtered", "SoupX_decont")[1]
                                   , min.cells = 10, min.features = 200, updateHGNC = T, ShowStats = T) {
   fin <- list.dirs(InputDir, recursive = F)
-  fin <- grepv(x = fin, pattern = folderPattern, perl = F)
+  fin <- CodeAndRoll2::grepv(x = fin, pattern = folderPattern, perl = F)
 
   for (i in 1:length(fin)) {
     pathIN = fin[i]; print(pathIN)
@@ -4021,7 +4046,7 @@ ConvertDropSeqfolders <- function(InputDir # Take a parent directory with a numb
                                   , min.cells = 10, min.features = 200, updateHGNC = T, ShowStats = T, minDimension = 10, overwrite = FALSE) {
   InputDir <- FixPath(InputDir)
   fin <- list.dirs(InputDir, recursive = F)
-  fin <- grepv(x = fin, pattern = folderPattern, perl = F)
+  fin <- CodeAndRoll2::grepv(x = fin, pattern = folderPattern, perl = F)
 
   for (i in 1:length(fin)) { print(i)
     pathIN <- FixPath(fin[i]); print(pathIN)
@@ -4450,21 +4475,21 @@ gene.name.check <- function(Seu.obj = ls.Seurat[[1]] ) { # Check gene names in a
   llprint("### Gene name pattern")
 
   llogit('`rn = rownames(GetAssayData(object = ls.Seurat[[1]], slot = "counts"))`')
-  llogit('`head(grepv(rn, pattern = "-"), 10)`')
+  llogit('`head(CodeAndRoll2::grepv(rn, pattern = "-"), 10)`')
   print('pattern = -')
-  llprint(head(grepv(rn, pattern = "-"), 10))
+  llprint(head(CodeAndRoll2::grepv(rn, pattern = "-"), 10))
 
-  llogit('`head(grepv(rn, pattern = "_"), 10)`')
+  llogit('`head(CodeAndRoll2::grepv(rn, pattern = "_"), 10)`')
   print('pattern = _')
-  llprint(head(grepv(rn, pattern = "_"), 10))
+  llprint(head(CodeAndRoll2::grepv(rn, pattern = "_"), 10))
 
-  llogit('`head(grepv(rn, pattern = "\\."), 10)`')
+  llogit('`head(CodeAndRoll2::grepv(rn, pattern = "\\."), 10)`')
   print('pattern = \\.')
-  llprint(head(grepv(rn, pattern = "\\."), 10))
+  llprint(head(CodeAndRoll2::grepv(rn, pattern = "\\."), 10))
 
-  llogit('`head(grepv(rn, pattern = "\\.AS[1-9]"), 10)`')
+  llogit('`head(CodeAndRoll2::grepv(rn, pattern = "\\.AS[1-9]"), 10)`')
   print('pattern = \\.AS[1-9]')
-  llprint(head(grepv(rn, pattern = "\\.AS[1-9]"), 10))
+  llprint(head(CodeAndRoll2::grepv(rn, pattern = "\\.AS[1-9]"), 10))
 }
 
 
@@ -5040,7 +5065,7 @@ plotTheSoup <- function(CellRangerOutputDir = "~/Data/114593/114593"
     soup.LINC.sum <- sum(soupProfile[grep('^LINC', names(soupProfile))])
     soup.AC.sum <- sum(soupProfile[grep('^AC', names(soupProfile))])
     soup.AL.sum <- sum(soupProfile[grep('^AL', names(soupProfile))])
-    genes.non.Above <- soupProfile[grepv('^RPL|^RPS|^MT-|^LINC|^AC|^AL', names(soupProfile), invert = T)]
+    genes.non.Above <- soupProfile[CodeAndRoll2::grepv('^RPL|^RPS|^MT-|^LINC|^AC|^AL', names(soupProfile), invert = T)]
   }
   head(sort(genes.non.Above), n = 50)
 
@@ -5235,3 +5260,5 @@ parallel.computing.by.future <- function(workers_ = 6, maxMemSize = 4000 * 1024^
   # So to set Max mem size to 2GB, you would run :
   options(future.globals.maxSize = maxMemSize)
 }
+
+

NAMESPACE

@@ -122,6 +122,7 @@ export(saveRDS.compress.in.BG)
 export(scBarplotFractionAboveThr)
 export(scBarplotFractionBelowThr)
 export(set.all.genes)
+export(set.mm)
 export(seu.Make.Cl.Label.per.cell)
 export(seu.PC.var.explained)
 export(seu.add.meta.from.table)