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author | Alexander Kabui | 2021-09-14 22:49:43 +0300 |
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committer | Alexander Kabui | 2021-09-14 22:49:43 +0300 |
commit | 1c98a10bf5015a85b856f9e937417d51ec05d781 (patch) | |
tree | e6cb57a5ef8bc0e7e7e69be1421c5a5856e3109f /scripts/wgcna_analysis.R | |
parent | 42c120dff2b3cac8a6b6546ebab9daf021aac11a (diff) | |
download | genenetwork3-1c98a10bf5015a85b856f9e937417d51ec05d781.tar.gz |
construct gene co-expression network & module detection
Diffstat (limited to 'scripts/wgcna_analysis.R')
-rw-r--r-- | scripts/wgcna_analysis.R | 23 |
1 files changed, 20 insertions, 3 deletions
diff --git a/scripts/wgcna_analysis.R b/scripts/wgcna_analysis.R index cb93492..29f0259 100644 --- a/scripts/wgcna_analysis.R +++ b/scripts/wgcna_analysis.R @@ -33,9 +33,26 @@ dataExpr <- dataExpr[gsg$goodSamples, gsg$goodGenes] # 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) - +powers <- c(c(1:10), seq(from = 12, to=20, by=2)) +sft <- pickSoftThreshold(dataExpr, powerVector = powers, verbose = 5) + +# pass user options +network <- blockwiseModules(dataExpr, + #similarity matrix options + corType = "pearson", + #adjacency matrix options + + power = sft$powerEstimate, + networkType = "unsigned", + #TOM options + TOMtype = "unsigned", + + #module indentification + + minmodulesSize = 30, + deepSplit = 5, + PamRespectsDendro = FALSE + ) |