diff options
| -rw-r--r-- | scripts/wgcna_analysis.R | 18 |
1 files changed, 12 insertions, 6 deletions
diff --git a/scripts/wgcna_analysis.R b/scripts/wgcna_analysis.R index 390bee4..267cd86 100644 --- a/scripts/wgcna_analysis.R +++ b/scripts/wgcna_analysis.R @@ -1,3 +1,5 @@ + + library(WGCNA); library(stringi); @@ -6,6 +8,7 @@ options(stringsAsFactors = FALSE); imgDir = Sys.getenv("GENERATED_IMAGE_DIR") # load expression data **assumes csv format row(traits)(columns info+samples) +# pass the file_path as arg inputData <- read.csv(file = "wgcna_data.csv") @@ -13,26 +16,29 @@ inputData <- read.csv(file = "wgcna_data.csv") dataExpr <- as.data.frame(t(inputData)); -# data cleaning +## data cleaning gsg = goodSamplesGenes(dataExpr, verbose = 3); - +# https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/ if (!gsg$allOK) { -# Optionally, print the gene and sample names that were removed: if (sum(!gsg$goodGenes)>0) -printFlush(paste("Removing genes:", paste(names(datExpr0)[!gsg$goodGenes], collapse = ", "))); +printFlush(paste("Removing genes:", paste(names(dataExpr)[!gsg$goodGenes], collapse = ", "))); if (sum(!gsg$goodSamples)>0) -printFlush(paste("Removing samples:", paste(rownames(datExpr0)[!gsg$goodSamples], collapse = ", "))); +printFlush(paste("Removing samples:", paste(rownames(dataExpr)[!gsg$goodSamples], collapse = ", "))); # Remove the offending genes and samples from the data: dataExpr <- dataExpr[gsg$goodSamples, gsg$goodGenes] } -# network constructions and modules +## network constructions and modules + +# Allow multi-threading within WGCNA +enableWGCNAThreads() # choose softthreshhold (Calculate soft threshold) +# xtodo allow users to pass args powers <- c(c(1:10), seq(from = 12, to=20, by=2)) sft <- pickSoftThreshold(dataExpr, powerVector = powers, verbose = 5) |