Update differential_expression.R

.Rbuildignore

@@ -0,0 +1,2 @@
+^.*\.Rproj$
+^\.Rproj\.user$

.gitignore

@@ -0,0 +1,4 @@
+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata

DESCRIPTION

@@ -11,14 +11,17 @@ LazyData: true
 Suggests: 
     testthat (>= 3.0.0)
 Config/testthat/edition: 3
+Depends:
+    data.table
 Imports: 
     Seurat,
     MAST,
-    data.table,
+    Matrix,
     ggplot2,
     patchwork,
     parallel,
     sessioninfo,
     utils,
-    magrittr
-RoxygenNote: 7.1.1
+    magrittr,
+    methods
+RoxygenNote: 7.2.3

NAMESPACE

@@ -1 +1,17 @@
-exportPattern("^[[:alpha:]]+")
+# Generated by roxygen2: do not edit by hand
+
+export(.countsperclus)
+export(DE_MAST_RE_seurat)
+export(estimate_dimensions)
+export(geneset_VIF)
+export(geneset_embed)
+export(geneset_embed_list_seurat)
+export(plot_barIdentGroup)
+export(plot_network)
+export(plot_vlnGrid)
+export(prep_HTO_q_area_plot)
+export(prep_intrahash_doub)
+export(prep_qc_rna)
+export(remap)
+export(utils_big_as.matrix)
+importFrom(Matrix,rowSums)

R/differential_expression.R

@@ -332,12 +332,13 @@ DE_MAST_RE_seurat = function(
   # https://github.com/kdzimm/PseudoreplicationPaper/blob/master/Type_1_Error/Type%201%20-%20MAST%20RE.Rmd
 
   de.results <- data.frame(
-    "p_val" = summaryCond$datatable[contrast=='groupGroup1' & component=='H', `Pr(>Chisq)`],
+    "p_val" = summaryCond$datatable[contrast=='groupGroup1' & component=='H', "Pr(>Chisq)"],
+    "z_score" = summaryCond$datatable[contrast=='groupGroup1' & component=='H', "z"],
     fc.results[vec_logical_features,])  #setDF(summaryCond$datatable[contrast=='groupGroup1' & component=='logFC', .(coef)])
 
-  de.results$p_val_adj = p.adjust(de.results$p_val, method=p.adjust.method, n=length(vec_logical_features))
+  de.results$p_val_adj = p.adjust(de.results$p_val, method=p.adjust.method, n=length(features))
 
-  de.results = de.results[order(de.results$p_val, -de.results[[fc.name]]),]
+  de.results = de.results[order(de.results$z_score),]
 
   return(de.results)
 }

R/geneset_enrichment.R

@@ -11,7 +11,7 @@
 #'
 #' @references modified from https://rdrr.io/bioc/qusage/src/R/qusage.R
 #' . drawing on https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3458527/
-#' @examples list_vec_VIF <- geneset_VIF(datExpr=mat_counts, list_genesets=mylist)
+#' @examples ## list_vec_VIF <- geneset_VIF(datExpr=mat_counts, list_genesets=mylist)
 geneset_VIF <- function(datExpr, list_genesets) {
   list_vec_vif = lapply(names(list_genesets), function(genesetname) {
     vec_logicalgenes <-rownames(datExpr) %in% list_genesets[[genesetname]]

R/plot.R

@@ -21,7 +21,7 @@
 #' @return a ggplot2 object
 #' @export
 #'
-#' @examples p <- plot_barIdentGroup(seurat_obj=seu, var_ident="sample",var_group="cluster")
+#' @examples ##p <- plot_barIdentGroup(seurat_obj=seu, var_ident="sample",var_group="cluster")
 plot_barIdentGroup = function(seurat_obj,
                               var_ident,
                               var_group,
@@ -106,7 +106,7 @@ plot_barIdentGroup = function(seurat_obj,
 #' @return ggplot2 object
 #' @export
 #'
-#' @examples p <- plot_vlnGrid(seurat_obj=seu, assay="RNA", slot="data", var_group="cluster", vec_features=head(VariableFeatures(seu)))
+#' @examples ##p <- plot_vlnGrid(seurat_obj=seu, assay="RNA", slot="data", var_group="cluster", vec_features=head(VariableFeatures(seu)))
 plot_vlnGrid = function(seurat_obj,
                         assay,
                         slot,

R/reduce_dimensions.R

@@ -8,20 +8,20 @@
 #' @return integer number of dimensions, <= max_dim
 #' @export
 #'
-#' @examples estimate_dimensions(seurat_obj)
-dim_red_est <- function(x,
-                        max_dim=75,
-                        seed.use=12345) {
+#' @examples ##estimate_dimensions(seurat_obj)
+estimate_dimensions <- function(x,
+                       max_dim=75,
+                       seed.use=12345) {
 
-  if(is(x, "SingleCellExperiment")) {
-    x <- as.Seurat(x)
-  }
+ if(is(x, "SingleCellExperiment")) {
+   x <- as.Seurat(x)
+ }
 
-  x %>% RunPCA(., npcs=max_dim, seed.use=seed.use, verbose = F) -> x
+ x %>% RunPCA(., npcs=max_dim, seed.use=seed.use, verbose = F) -> x
 
-  dims <- round(as.numeric(intrinsicDimension::maxLikGlobalDimEst(data = x@reductions$pca[, 1:max_dim], k = 20)))
+ dims <- round(as.numeric(intrinsicDimension::maxLikGlobalDimEst(data = x@reductions$pca[, 1:max_dim], k = 20)))
 
-  return(dims)
+ return(dims)
 }
 
 

R/remap.R

@@ -13,7 +13,7 @@
 #' @return an object of the same format as dataIn with new gene names
 #' @export
 #'
-#' @examples df_data_remapped = map_genes(dataIn=df_data, colRemap="genes", df_mapping=fread("./mapping/hgnc_ensembl.csv"), replace=T)
+#' @examples ## df_data_remapped = remap(dataIn=df_data, colRemap="genes", df_mapping=fread("./mapping/hgnc_ensembl.csv"), replace=T)
 remap <- function(dataIn,
                  colRemap = NULL,
                  df_mapping,

SCOPfunctions.Rproj

@@ -18,3 +18,4 @@ StripTrailingWhitespace: Yes
 BuildType: Package
 PackageUseDevtools: Yes
 PackageInstallArgs: --no-multiarch --with-keep.source
+PackageRoxygenize: rd,collate,namespace,vignette