expose q-cutoff as parameter

common/cp_enrichment.R

@@ -13,6 +13,8 @@ Options:
 --overlay_expr_data Tsv with overlay data for the kegg pathways
 --list_id_col Column containing the grouping variable to speparate different lists [default: ]
 --project <project_prefix>   Name to prefix all generated result files [default: ]
+--qcutoff <qcutoff>             Use a q-value cutoff of 0.01 instead of a q-value cutoff [default: 0.01]
+
 '
 
 opts <- docopt(doc, commandArgs(TRUE)) ## does not work when spining
@@ -54,11 +56,20 @@ if(!is.null(opts$overlay_expr_data)){
 resultsBaseName <- if(str_length(opts$project)>0) paste0(opts$project, ".") else basename(opts$gene_lists_tsv) %>% trim_ext("txt") #%>% paste0(".")
 #resultsBaseName=basename(opts$gene_lists_tsv) %>% trim_ext("txt") #%>% paste0(".")
 
+
+## TODO  expose as argument
+#pCutoff <- 0.05
+#qCutoff <- 0.01
+qCutoff <- as.numeric(opts$qcutoff)
+
+
 reload_dplyr()
 
 ########################################################################################################################
 #' ## Enrichment Analysis
 
+#' Run configuration was
+vec2df(unlist(opts)) %>% filter(!str_detect(name, "^[<-]")) %>% kable()
 
 #' This analysis was performed using [clusterProfiler](http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html). The following ontologies were tested: Kegg, Go, Reactome, Dose,
 
@@ -141,11 +152,6 @@ glMapped <- glMappedRaw %>% filter(!is.na(entrez_gene_id)) %>% select(-ensembl_g
     #    group_by_(cluster)
     group_by_(.dots=group_col %>% ac)
 
-## TODO  expose as argument
-
-#pCutoff <- 0.05
-qCutoff <- 0.01
-
 
 ## retain just 1500 genes at max per group
 #glMappedSub <- glMapped %>% do({shuffle(.) %>% head(1500)})