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authorAlexander Kabui2021-09-14 22:42:43 +0300
committerAlexander Kabui2021-09-14 22:42:43 +0300
commit42c120dff2b3cac8a6b6546ebab9daf021aac11a (patch)
tree558f2bb6f7f8a1279d80ee2e38030e165808f9d5
parent49fdd614d4b18f7d28126e4ebbf3adca57f0416f (diff)
downloadgenenetwork3-42c120dff2b3cac8a6b6546ebab9daf021aac11a.tar.gz
compute the softthreshhold
-rw-r--r--scripts/wgcna_analysis.R14
1 files changed, 11 insertions, 3 deletions
diff --git a/scripts/wgcna_analysis.R b/scripts/wgcna_analysis.R
index 8e90d7d..cb93492 100644
--- a/scripts/wgcna_analysis.R
+++ b/scripts/wgcna_analysis.R
@@ -5,15 +5,12 @@ stringsAsFactors = FALSE
# load expression data **assumes csv format row(traits)(columns info+samples)
-
wgcnaRawData <- read.csv(file = "wgcna_data.csv")
# transform expressionData
dataExpr <- as.data.frame(t(wgcnaRawData));
-
-
# data cleaning
# adopted from docs
@@ -32,6 +29,17 @@ printFlush(paste("Removing samples:", paste(rownames(datExpr0)[!gsg$goodSamples]
dataExpr <- dataExpr[gsg$goodSamples, gsg$goodGenes]
}
+# network constructions and modules
+
+# choose softthreshhold (Calculate soft threshold if the user specified the)
+
+powers = c(c(1:10), seq(from = 12, to=20, by=2))
+sft = pickSoftThreshold(dataExpr, powerVector = powers, verbose = 5)
+
+
+
+
+