multi-core update

scSNViz/R/individual_snv_plots.R

@@ -43,6 +43,18 @@
 individual_snv_plots <- function(seurat_object, processed_snv, output_dir = NULL, slingshot = T,
                                  dimensionality_reduction = "UMAP", dynamic_cell_size = F, save_each_plot = F, enable_integrated = F) {
 
+
+  #OS checking
+  sys <- Sys.info()[['sysname']]
+  if (sys == "Linux" || sys == "Darwin"){
+    cores <- readline("How many cores would you like to use?: ")
+    cores <- as.numeric(cores)
+    if (cores > detectCores()){
+      stop(paste0("Invalid amount of cores, you have "), detectCores(), " cores.")
+    }
+  } else {
+    cores <- 1
+  }
   cat("\nGenerating individual SNV plots...\n")
 
   valid_reductions <- c("umap", "pca", "tsne")
@@ -279,7 +291,7 @@ individual_snv_plots <- function(seurat_object, processed_snv, output_dir = NULL
 
   counter = 0
   # function to save plots' json
-  plots_json <- lapply(snv_options, function(snv) {
+  plots_json <- mclapply(snv_options, function(snv) {
     plots <- generate_snv_plots(snv, title_color = 'blue')
     list(
       VAF = list(
@@ -294,7 +306,7 @@ individual_snv_plots <- function(seurat_object, processed_snv, output_dir = NULL
         id = paste0("plot_N_REF_", gsub(":", "_", snv)),
         json = plotly::plotly_json(plots[['N_REF']], jsonedit = F)
       )
-    )}
+    )}, mc.cores = cores
   )
 
   plots_json <- unlist(plots_json, recursive = F)
@@ -320,12 +332,13 @@ individual_snv_plots <- function(seurat_object, processed_snv, output_dir = NULL
       saveWidget(as_widget(plot), file = file_path, selfcontained = F, libdir = "lib")
     }
 
-    for (snv in snv_options) {
-      plots <- generate_snv_plots(snv, title_color = "black")
-      save_snv_plot(plots[["VAF"]], snv, "VAF")
-      save_snv_plot(plots[['N_VAR']], snv, "N_VAR")
-      save_snv_plot(plots[['N_REF']], snv, "N_REF")
-    }
+    mclapply(snv_options, function(snv) {
+    plots <- generate_snv_plots(snv, title_color = "black")
+    save_snv_plot(plots[["VAF"]], snv, "VAF")
+    save_snv_plot(plots[["N_VAR"]], snv, "N_VAR")
+    save_snv_plot(plots[["N_REF"]], snv, "N_REF")
+    }, mc.cores = cores)
+
   }
 
   ind_snv_out <- list()

scSNViz/R/plot_snv_data.R

@@ -82,6 +82,17 @@ plot_snv_data <- function(seurat_object, processed_snv, aggregated_snv, plot_dat
     if (slingshot==TRUE){print('Turning off the slingshot option - this is not available for integrated objects')}
     if (include_copykat==TRUE){print('Turning off the copykat option - this is not available for integrated objects')}
   }
+  #os checking
+  sys <- Sys.info()[['sysname']]
+  if (sys == "Linux" || sys == "Darwin"){
+    cores <- readline("How many cores would you like to use?")
+    cores <- as.numeric(cores)
+    if (cores > detectCores()){
+      stop(paste0("Invalid amount of cores, you have "), detectCores(), " cores.")
+    }
+  } else {
+    cores <- 1
+  }
 
   valid_reductions <- c("umap", "pca", "tsne")
   dimensionality_reduction <- tolower(dimensionality_reduction)
@@ -278,35 +289,43 @@ plot_snv_data <- function(seurat_object, processed_snv, aggregated_snv, plot_dat
 
   #plots <- list()
 
-  for (metric in names(plot_titles)) {
-    if (!metric %in% colnames(plot_data))
-      next
-
-    plot <- generate_plot(
-      metric = metric,
-      plot_data = plot_data,
-      dim_plotting = dim_plotting,
-      color_scale = color_scale,
-      reversescale_option = reversescale_option,
-      cell_border = cell_border,
-      color_undetected = color_undetected,
-      curves = curves,
-      disable_3d_axis = disable_3d_axis,
-      title = plot_titles[[metric]] #(duplicate title fix)
-    )
+generate_and_save_plot <- function(metric) {
+  if (!metric %in% colnames(plot_data))
+    return(NULL)
+
+  plot <- generate_plot(
+    metric = metric,
+    plot_data = plot_data,
+    dim_plotting = dim_plotting,
+    color_scale = color_scale,
+    reversescale_option = reversescale_option,
+    cell_border = cell_border,
+    color_undetected = color_undetected,
+    curves = curves,
+    disable_3d_axis = disable_3d_axis,
+    title = plot_titles[[metric]]
+  )
+
+  plot_name <- plot_titles[[metric]]
+  file_title <- gsub("[^a-zA-Z0-9]", "_", plot_name)
 
-    plot_name <- plot_titles[[metric]]
-    plots[[plot_name]] <- plot
-    #plots[[metric]] <- plot (changed naming of the plots in the output for easier matching in generate_report)
+  if (save_each_plot && !is.null(output_dir)) {
+    saveWidget(as_widget(plot), file = file.path(
+      output_dir, "SNV_data_plots", paste0(file_title, ".html")),
+      selfcontained = FALSE, libdir = "lib")
+  }
 
-    file_title <- gsub("[^a-zA-Z0-9]", "_", plot_titles[[metric]])
+  return(list(name = plot_name, plot = plot))
+}
 
-    if (save_each_plot && !is.null(output_dir)) {
-      saveWidget(as_widget(plot), file = file.path(
-        output_dir, "SNV_data_plots", paste0(file_title, ".html")),
-        selfcontained = F, libdir = "lib")
-    }
-  }
+# Parallel here
+results <- mclapply(names(plot_titles), generate_and_save_plot, mc.cores = cores)
+filtered_results <- Filter(Negate(is.null), results)
+new_plots <- setNames(
+  lapply(filtered_results, `[[`, "plot"),
+  sapply(filtered_results, `[[`, "name")
+)
+plots <- c(plots, new_plots)
 
   # INTEGRATED ORIG IDENT PLOT
 
@@ -544,7 +563,7 @@ plot_snv_data <- function(seurat_object, processed_snv, aggregated_snv, plot_dat
     options(bitmapType = "cairo")
     cat("Running CopyKat. This may take a while...\n")
     cts <- GetAssayData(seurat_object, layer = "counts", assay = "SCT")
-    ckt <- copykat(cts, sam.name = "sample_name")
+    ckt <- copykat(cts, sam.name = "sample_name", n.cores = cores)
     options(bitmapType = "C_X11")
     seurat_object[["karyotype"]] <- "Unknown"
     seurat_object[["karyotype"]][rownames(ckt$pred), ] <- ckt$pred[, 2]

scSNViz/README.md

@@ -28,7 +28,7 @@ install_github("HorvathLab/NGS", ref = "scSNViz_R_v1.0.0", subdir = "scSNViz")
 The input files are located in the input folder on github. The snv file is an output from SCReadCounts. The user may provide a .tsv file that is not from SCReadCounts as long as it is also a .tsv and contains the following columns: CHROM, POS, REF, ALT, ReadGroup, SNVCount, RefCount.
 ```
 load.lib<-c("scSNViz","SingleCellExperiment", "stringr", "HGNChelper", "Matrix", "umap", "Rtsne", "Seurat", "sctransform", "ggplot2", "readr",
-            "dplyr", "plotly", "htmlwidgets", "htmltools", "jsonlite", "glmGamPoi", "slingshot", "listviewer","openxlsx","randomcoloR") # the installation of ("glmGamPoi") is highly recommended
+            "dplyr", "plotly", "htmlwidgets", "htmltools", "jsonlite", "glmGamPoi", "slingshot", "listviewer","openxlsx","randomcoloR", "parallel") # the installation of ("glmGamPoi") is highly recommended
 
 install.lib <- load.lib[!load.lib %in% installed.packages()]
 for(lib in install.lib) install.packages(lib,dependencies=TRUE)