Only_ruv parameter

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KellisLab · Jun 11, 2024 · b2472f6 · b2472f6
1 parent 2b95d44
commit b2472f6
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Showing 2 changed files with 14 additions and 2 deletions.
diff --git a/R/deg.R b/R/deg.R
@@ -216,7 +216,7 @@ deg.prepare <- function(se, pathology, case, control, sample.col, filter_only_ca
 deg <- function(se, pathology, case, control, covariates,
                 method, output=NULL,
                 sample.col="Sample", cpm.cutoff=10,
-                filter_only_case_control=TRUE, NRUV=0,
+                filter_only_case_control=TRUE, NRUV=0, only_ruv=TRUE,
                 min.total.counts.per.sample=100, IQR.factor=1.5,
                 outlier.covariates=c("log1p_total_counts", "n_genes_by_counts", "pct_counts_mt", "pct_counts_ribo"),
                 verbose=TRUE,
@@ -237,7 +237,7 @@ deg <- function(se, pathology, case, control, covariates,
         se = deg.ruvseq(se, pathology=pathology, covariates=covariates, sample.col=sample.col, NRUV=NRUV, verbose=verbose)
         covariates = c(covariates, paste0("RUV_", 1:NRUV))
         covariates = covariates[covariates %in% names(SummarizedExperiment::colData(se))]
-        if (length(covariates) > 0) {
+        if ((length(covariates) > 0) && only_ruv) {
             covariates = covariates[grep("^RUV_[0-9]+$", covariates)]
         }
     }

diff --git a/scripts/deg.R b/scripts/deg.R
@@ -42,6 +42,7 @@ get_args <- function(args) {
     params$min.total.counts.per.sample = 100
     params$ncores = as.integer(Sys.getenv("OMP_NUM_THREADS", getOption("mc.cores", 2)))
     params$genes = NULL
+    params$only_ruv = TRUE
     i = 1
     help = function() {
         cat("deg.R [options]
@@ -64,6 +65,8 @@ options:
   -g, --genes File containing genes to use, one per line
   --cpm-cutoff Counts per million cutoff for filtering genes.
   --min-total-counts Number of total counts required per cell
+  --keep-covariates After RUV, keep the original covariates (not enabled by default)
+  --only-ruv After RUV, remove original covariates (enabled by default)
   --iqr-factor Number of IQR above 75% away from outlier covariates to be a bad sample.
   --outlier-covariates Covariates (in colData/.obs) to be used as covariates for pseudobulk outlier detection. If not present, or not calculated by benj::calculate_qc_metrics, will be thrown out.
 ")
@@ -115,6 +118,14 @@ options:
             i = i + 1
             params$case = args[[i]]
             i = i + 1
+        } else if (arg == "--keep-covariates") {
+            i = i + 1
+            params$only_ruv = FALSE
+            i = i + 1
+        } else if (arg == "--only-ruv") {
+            i = i + 1
+            params$only_ruv = TRUE
+            i = i + 1
         } else if (arg == "--control") {
             i = i + 1
             params$control = args[[i]]
@@ -215,4 +226,5 @@ adata = benj::deg(adata,
                   verbose=params$verbose,
                   min.total.counts.per.sample=params$min.total.counts.per.sample,
                   IQR.factor=params$IQR.factor,
+                  only_ruv=params$only_ruv,
                   outlier.covariates=params$outlier.covariates)