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-rw-r--r--scripts/wgcna_analysis.R16
1 files changed, 15 insertions, 1 deletions
diff --git a/scripts/wgcna_analysis.R b/scripts/wgcna_analysis.R
index 17b3537..a5cbbe3 100644
--- a/scripts/wgcna_analysis.R
+++ b/scripts/wgcna_analysis.R
@@ -6,11 +6,15 @@ library(rjson)
options(stringsAsFactors = FALSE);
-imgDir = Sys.getenv("GENERATED_IMAGE_DIR")
+cat("Running the wgcna analysis script\n")
+
# load expression data **assumes from json files row(traits)(columns info+samples)
# pass the file_path as arg
# pass the file path to read json data
+
+
+
args = commandArgs(trailingOnly=TRUE)
if (length(args)==0) {
@@ -21,6 +25,7 @@ if (length(args)==0) {
}
inputData <- fromJSON(file = json_file_path)
+imgDir = inputData$TMPDIR
trait_sample_data <- do.call(rbind, inputData$trait_sample_data)
@@ -83,6 +88,11 @@ network <- blockwiseModules(dataExpr,
+cat("Generated network \n")
+
+network
+
+
genImageRandStr <- function(prefix){
randStr <- paste(prefix,stri_rand_strings(1, 9, pattern = "[A-Za-z0-9]"),sep="_")
@@ -95,6 +105,10 @@ mergedColors <- labels2colors(network$colors)
imageLoc <- file.path(imgDir,genImageRandStr("WGCNAoutput"))
png(imageLoc,width=1000,height=600,type='cairo-png')
+
+cat("Generating the CLuster dendrogram\n")
+
+
plotDendroAndColors(network$dendrograms[[1]],mergedColors[network$blockGenes[[1]]],
"Module colors",
dendroLabels = FALSE, hang = 0.03,