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author | Alexander Kabui | 2021-09-27 15:15:28 +0300 |
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committer | Alexander Kabui | 2021-09-27 15:15:28 +0300 |
commit | 6f25b8e2b1d1a34c054d325b1c37b303529b8827 (patch) | |
tree | f067038677002555325af043a0ecd300e984003d /scripts | |
parent | 7dbb0e6d27cdb0923e94685cf44d244dd8a2e105 (diff) | |
download | genenetwork3-6f25b8e2b1d1a34c054d325b1c37b303529b8827.tar.gz |
remove unnecessary comments and variables
Diffstat (limited to 'scripts')
-rw-r--r-- | scripts/wgcna_analysis.R | 18 |
1 files changed, 4 insertions, 14 deletions
diff --git a/scripts/wgcna_analysis.R b/scripts/wgcna_analysis.R index e641652..17b3537 100644 --- a/scripts/wgcna_analysis.R +++ b/scripts/wgcna_analysis.R @@ -23,24 +23,14 @@ if (length(args)==0) { inputData <- fromJSON(file = json_file_path) -# parse the json data input - -minModuleSize <-inputData$minModuleSize - -TOMtype <-inputData$TOMtype - -corType <-inputData$corType -# - trait_sample_data <- do.call(rbind, inputData$trait_sample_data) dataExpr <- data.frame(apply(trait_sample_data, 2, function(x) as.numeric(as.character(x)))) # transform expressionData dataExpr <- data.frame(t(dataExpr)) -gsg = goodSamplesGenes(dataExpr, verbose = 3); +gsg = goodSamplesGenes(dataExpr, verbose = 3) -# https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/ if (!gsg$allOK) { if (sum(!gsg$goodGenes)>0) @@ -75,18 +65,18 @@ if (is.na(sft$powerEstimate)){ # pass user options network <- blockwiseModules(dataExpr, #similarity matrix options - corType = corType, + corType = inputData$corType, #adjacency matrix options power = powerEst, networkType = "unsigned", #TOM options - TOMtype = TOMtype, + TOMtype = inputData$TOMtype, #module indentification verbose = 3, - minmodulesSize = minModuleSize, + minmodulesSize = inputData$minModuleSize, deepSplit = 3, PamRespectsDendro = FALSE ) |