nf scBarplot.CellsPerCluster

bf AutoNumber.by.UMAP

CITATION.cff

@@ -1,6 +1,6 @@
 cff-version: 1.2.0
 title: vertesy/Seurat.utils
-version: v1.5.0
+version: v1.5.2
 message: >-
   If you use this software, please cite it using these metadata.
 type: software

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: Seurat.utils
 Title: Seurat.utils - utility functions for Seurat
-Version: 1.5.0
+Version: 1.5.2
 Authors@R: 
     person("Abel", "Vertesy", , "[email protected]", role = c("aut", "cre"))
 Author: Abel Vertesy <[email protected]> [aut, cre]
@@ -51,6 +51,6 @@ Imports:
 Suggests: 
     SoupX
 Encoding: UTF-8
-Packaged: 2022-10-19 13:57:07
+Packaged: 2022-10-19 17:47:22
 Roxygen: list(markdown = TRUE)
 RoxygenNote: 7.2.0

Development/Create_the_Seurat.utils_Package.v0.1.0.R

@@ -21,7 +21,7 @@ require('CodeAndRoll2')
 
 # Setup ------------------------
 PackageName = 	"Seurat.utils"
-package.version = "1.5.0"
+package.version = "1.5.2"
 setwd("~/GitHub/Packages/")
 
 RepositoryDir = kollapse("~/GitHub/Packages/", PackageName, "/")

Development/Development.bac

@@ -348,17 +348,21 @@ DimPlot.ClusterNames <- function(obj = combined.obj # Plot UMAP with Cluster nam
 #' }
 #' @export
 AutoNumber.by.UMAP <- function(obj = combined.obj # Relabel cluster numbers along a UMAP (or tSNE) axis
-                               , dim = 1, swap= F, reduction="umap", res = "integrated_snn_res.0.5" ) {
+                               , dim = 1, swap= F, reduction="umap", res = "RNA_snn_res.0.5" ) {
 
   dim_name <- kppu(toupper(reduction),dim)
   coord.umap <- as.named.vector(FetchData(object = obj, vars = dim_name))
-  ls.perCl <- split(coord.umap, f = obj[[res]])
+  identX <- as.character([email protected][[res]])
+
+  ls.perCl <- split(coord.umap, f = identX)
   MedianClusterCoordinate <- unlapply(ls.perCl, median)
+
   OldLabel <- names(sort(MedianClusterCoordinate, decreasing = swap))
   NewLabel <- as.character(0:(length(MedianClusterCoordinate) - 1))
-  NewMeta <- translate(vec = obj[[res]], oldvalues = OldLabel, newvalues = NewLabel)
+  NewMeta <- translate(vec = identX, oldvalues = OldLabel, newvalues = NewLabel)
   NewMetaCol <- kpp(res,"ordered")
   iprint("NewMetaCol:",NewMetaCol)
+
   obj[[NewMetaCol]] <- NewMeta
   return(obj)
 }
@@ -1583,10 +1587,9 @@ get.clustercomposition <- function(obj = combined.obj, ident = 'integrated_snn_r
 #' remove.residual.small.clusters
 #' @description E.g.: after subsetting often some residual cells remain in clusters originally denfined in the full dataset.
 #' @param identitites Identities to scan for residual clusters
-#' @param obj
+#' @param obj Seurat object, Default: combined.obj
 #' @param max.cells Max number of cells in cluster to be removed. Default: 0.5% of the dataset
 #' @export
-#' @examples
 
 remove.residual.small.clusters <- function(identitites = GetOrderedClusteringRuns()
                                            , obj = combined.obj
@@ -1623,7 +1626,6 @@ remove.residual.small.clusters <- function(identitites = GetOrderedClusteringRun
 #' drop.levels.Seurat
 #' @description Drop levels in clustering vectors in metadata (e.g. after subsetting)
 #' @param obj Seurat object, Default: combined.obj
-#' @examples
 #' @export
 
 drop.levels.Seurat <- function(obj = combined.obj) {
@@ -3464,9 +3466,16 @@ scBarplot.CellFractions <- function(obj = combined.obj
 # _________________________________________________________________________________________________
 #' @title scBarplot.CellsPerCluster
 #' @description Barplot the Fraction of cells per cluster. (dupl?)
+#'
 #' @param obj Seurat object, Default: combined.obj
 #' @param ident identity used, Default: 'cl.names.KnownMarkers.0.5'
-#' @param sort PARAM_DESCRIPTION, Default: F
+#' @param label True: displays cell count, but you can provide anything in a vector.
+#' @param palette Color palette. Default: glasbey.
+#' @param return_table Should it return the plotting data instead of the plot?
+#' @param ... Pass any other parameter to the internally called functions (most of them should work).
+#' @param sort Sort by cluster size? Default: F
+#' @param suffix File name suffix
+#'
 #' @examples
 #' \dontrun{
 #' if(interactive()){
@@ -3477,21 +3486,25 @@ scBarplot.CellFractions <- function(obj = combined.obj
 
 scBarplot.CellsPerCluster <- function(ident =  GetOrderedClusteringRuns()[1]
                                       , sort = F
-                                      , label = T
+                                      , label = list(T, 'percent')[[1]]
+                                      , suffix = if (label == 'percent') 'percent' else NULL
                                       , palette = c("alphabet", "alphabet2", "glasbey", "polychrome", "stepped")[3]
                                       , obj = combined.obj
                                       , return_table = F
                                       , ...) {
   cell.per.cl <- obj[[ident]][,1]
   cell.per.cluster <- (table(cell.per.cl))
   if (sort) cell.per.cluster <- sort(cell.per.cluster)
-  lbl <- if (isFALSE(label)) NULL else if(isTRUE(label)) cell.per.cluster else label
+  lbl <- if (isFALSE(label)) { NULL
+    } else if (label == 'percent') { percentage_formatter(cell.per.cluster/sum(cell.per.cluster))
+      } else if (label == 'T') { cell.per.cluster
+        } else label
 
   n.clusters <- length(cell.per.cluster)
   if (return_table) {
     cell.per.cluster
   } else {
-    ggExpress::qbarplot(cell.per.cluster, subtitle = ident, suffix = ident
+    ggExpress::qbarplot(cell.per.cluster, subtitle = ident, suffix = kpp(ident, suffix)
              , col = 1:n.clusters
              , xlab.angle = 45
              , label = lbl
@@ -5632,9 +5645,8 @@ IntersectWithExpressed <- function(genes, obj=combined.obj, genes.shown = 10) {
 # _________________________________________________________________________________________________
 #' seu.RemoveMetadata
 #'
-#' @param obj Seurat object
+#' @param obj Seurat object, Default: combined.obj
 #' @param cols_remove columns to remove
-#' @example # seu.RemoveMetadata()
 #' @export
 
 seu.RemoveMetadata <- function(obj = combined.obj
@@ -5654,11 +5666,11 @@ seu.RemoveMetadata <- function(obj = combined.obj
 
 # _________________________________________________________________________________________________
 #' Percent.in.Trome
-#' @description  Gene expression as fraction of all UMI's
+#' @description Gene expression as fraction of all UMI's
 #' @param obj Seurat object
 #' @param n.genes.barplot number of top genes shows
 #' @param width.barplot barplot width
-#' @return  Seurat object
+#' @return Seurat object
 #' @export
 #' @examples # combined.obj <- Percent.in.Trome()
 

R/Seurat.Utils.R

@@ -348,17 +348,21 @@ DimPlot.ClusterNames <- function(obj = combined.obj # Plot UMAP with Cluster nam
 #' }
 #' @export
 AutoNumber.by.UMAP <- function(obj = combined.obj # Relabel cluster numbers along a UMAP (or tSNE) axis
-                               , dim = 1, swap= F, reduction="umap", res = "integrated_snn_res.0.5" ) {
+                               , dim = 1, swap= F, reduction="umap", res = "RNA_snn_res.0.5" ) {
 
   dim_name <- kppu(toupper(reduction),dim)
   coord.umap <- as.named.vector(FetchData(object = obj, vars = dim_name))
-  ls.perCl <- split(coord.umap, f = obj[[res]])
+  identX <- as.character(obj@meta.data[[res]])
+
+  ls.perCl <- split(coord.umap, f = identX)
   MedianClusterCoordinate <- unlapply(ls.perCl, median)
+
   OldLabel <- names(sort(MedianClusterCoordinate, decreasing = swap))
   NewLabel <- as.character(0:(length(MedianClusterCoordinate) - 1))
-  NewMeta <- translate(vec = obj[[res]], oldvalues = OldLabel, newvalues = NewLabel)
+  NewMeta <- translate(vec = identX, oldvalues = OldLabel, newvalues = NewLabel)
   NewMetaCol <- kpp(res,"ordered")
   iprint("NewMetaCol:",NewMetaCol)
+
   obj[[NewMetaCol]] <- NewMeta
   return(obj)
 }
@@ -3462,9 +3466,16 @@ scBarplot.CellFractions <- function(obj = combined.obj
 # _________________________________________________________________________________________________
 #' @title scBarplot.CellsPerCluster
 #' @description Barplot the Fraction of cells per cluster. (dupl?)
+#'
 #' @param obj Seurat object, Default: combined.obj
 #' @param ident identity used, Default: 'cl.names.KnownMarkers.0.5'
-#' @param sort PARAM_DESCRIPTION, Default: F
+#' @param label True: displays cell count, but you can provide anything in a vector.
+#' @param palette Color palette. Default: glasbey.
+#' @param return_table Should it return the plotting data instead of the plot?
+#' @param ... Pass any other parameter to the internally called functions (most of them should work).
+#' @param sort Sort by cluster size? Default: F
+#' @param suffix File name suffix
+#'
 #' @examples
 #' \dontrun{
 #' if(interactive()){
@@ -3475,21 +3486,25 @@ scBarplot.CellFractions <- function(obj = combined.obj
 
 scBarplot.CellsPerCluster <- function(ident =  GetOrderedClusteringRuns()[1]
                                       , sort = F
-                                      , label = T
+                                      , label = list(T, 'percent')[[1]]
+                                      , suffix = if (label == 'percent') 'percent' else NULL
                                       , palette = c("alphabet", "alphabet2", "glasbey", "polychrome", "stepped")[3]
                                       , obj = combined.obj
                                       , return_table = F
                                       , ...) {
   cell.per.cl <- obj[[ident]][,1]
   cell.per.cluster <- (table(cell.per.cl))
   if (sort) cell.per.cluster <- sort(cell.per.cluster)
-  lbl <- if (isFALSE(label)) NULL else if(isTRUE(label)) cell.per.cluster else label
+  lbl <- if (isFALSE(label)) { NULL
+    } else if (label == 'percent') { percentage_formatter(cell.per.cluster/sum(cell.per.cluster))
+      } else if (label == 'T') { cell.per.cluster
+        } else label
 
   n.clusters <- length(cell.per.cluster)
   if (return_table) {
     cell.per.cluster
   } else {
-    ggExpress::qbarplot(cell.per.cluster, subtitle = ident, suffix = ident
+    ggExpress::qbarplot(cell.per.cluster, subtitle = ident, suffix = kpp(ident, suffix)
              , col = 1:n.clusters
              , xlab.angle = 45
              , label = lbl