Add scripts

exec/scflow_annotate_integrated.R

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+#!/usr/bin/env Rscript
+#' Annotate integrated, dims reduced and clustered sce object
+# Mahdi Moradi Marjaneh
+
+# ____________________________________________________________________________
+# Initialization ####
+
+options(mc.cores = future::availableCores())
+
+## ............................................................................
+## Load packages ####
+library(argparse)
+library(scFlow)
+
+## ............................................................................
+## Parse command-line arguments ####
+
+# create parser object
+parser <- ArgumentParser()
+
+# specify options
+required <- parser$add_argument_group("Required", "required arguments")
+optional <- parser$add_argument_group("Optional", "required arguments")
+
+required$add_argument(
+  "--sce_path",
+  help = "-path to the SingleCellExperiment",
+  metavar = "dir",
+  required = TRUE
+)
+
+required$add_argument(
+  "--categorical_covariates",
+  help = "-categorical covariates",
+  metavar = "individual,diagnosis,region,sex",
+  required = TRUE
+)
+
+### . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..
+### Pre-process args ####
+
+args <- parser$parse_args()
+args <- purrr::map(args, function(x) {
+if (length(x) == 1) {
+if (toupper(x) == "TRUE") {
+return(TRUE)
+}
+if (toupper(x) == "FALSE") {
+return(FALSE)
+}
+if (toupper(x) == "NULL") {
+return(NULL)
+}
+}
+return(x)
+})
+
+## ............................................................................
+## Annotate integrated sce ####
+
+sce <- read_sce(args$sce_path)
+
+sce <- annotate_integrated_sce(
+sce,
+categorical_covariates = args$categorical_covariates
+)
+
+dir.create(file.path(getwd(), "integration_report"))
+
+report_integrated_sce(
+  sce = sce,
+  report_folder_path = file.path(getwd(), "integration_report"),
+  report_file = "integrate_reduceDims_cluster_report_scflow",
+)
+
+print("Annotation complete, saving outputs..")
+
+## ............................................................................
+## Save Outputs ####
+
+# Save SingleCellExperiment
+write_sce(
+sce = sce,
+folder_path = file.path(getwd(), "integrated_sce")
+)

exec/scflow_cluster.r

@@ -0,0 +1,108 @@
+#!/usr/bin/env Rscript
+# Reduce dimensions for a SCE
+#  Combiz Khozoie <[email protected]>
+
+#   ____________________________________________________________________________
+#   Initialization                                                          ####
+
+options(mc.cores = future::availableCores())
+
+##  ............................................................................
+##  Load packages                                                           ####
+library(argparse)
+library(scFlow)
+library(parallel)
+library(SingleCellExperiment) # due to monocle3 missing namespace::
+library(knitr) # due to missing knitr:: namespace in the integrate report
+
+##  ............................................................................
+##  Parse command-line arguments                                            ####
+
+# create parser object
+parser <- ArgumentParser()
+
+# specify options
+required <- parser$add_argument_group("Required", "required arguments")
+optional <- parser$add_argument_group("Optional", "required arguments")
+
+required$add_argument(
+  "--sce_path",
+  help = "-path to the SingleCellExperiment",
+  metavar = "dir",
+  required = TRUE
+)
+
+required$add_argument(
+  "--cluster_method",
+  help = "method to use for clustering",
+  metavar = "louvain",
+  required = TRUE
+)
+
+required$add_argument(
+  "--reduction_method",
+  help = "reduced dimension embedding to use for clustering",
+  metavar = "UMAP",
+  required = TRUE
+)
+
+required$add_argument(
+  "--res",
+  type = "double",
+  default = 0.00001,
+  help = "clustering resolution",
+  metavar = "N",
+  required = TRUE
+)
+
+required$add_argument(
+  "--k",
+  type = "integer",
+  default = 100,
+  help = "the number of kNN",
+  metavar = "N",
+  required = TRUE
+)
+
+required$add_argument(
+  "--louvain_iter",
+  type = "integer",
+  default = 1,
+  help = "number of iterations used for Louvain clustering",
+  metavar = "N",
+  required = TRUE
+)
+
+### . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..
+### Pre-process args                                                        ####
+
+args <- parser$parse_args()
+
+##  ............................................................................
+##  Start                                                                   ####
+
+sce <- read_sce(args$sce_path, read_metadata = TRUE)
+
+sce <- cluster_sce(
+  sce,
+  cluster_method = args$cluster_method,
+  reduction_method = args$reduction_method,
+  res = args$res,
+  k = args$k,
+  louvain_iter = args$louvain_iter
+)
+
+##  ............................................................................
+##  Save Outputs                                                            ####
+
+# Save SingleCellExperiment
+write_sce(
+  sce = sce,
+  folder_path = file.path(getwd(), "clustered_sce"),
+  write_metadata = TRUE
+)
+
+##  ............................................................................
+##  Clean up                                                                ####
+
+# Clear biomart cache