Question: WGCNA signed vs unsigned network
gravatar for krushnach80
17 months ago by
krushnach80500 wrote:

How to choose between signed vs unsigned network ?

sft=pickSoftThreshold(datExpr,dataIsExpr = TRUE,powerVector = powers,corFnc = cor,corOptions = list(use = 'p'),networkType = "signed")

adj= adjacency(datExpr,type = "unsigned", power = softPower)

TOM=TOMsimilarityFromExpr(datExpr,networkType = "signed", TOMType = "unsigned", power = softPower)

These are the three lines where i have to defined signed or unsigned type i read through Peter Langfelder blog but still im not much clear about

Any suggestion would be highly appreciated

rna-seq R • 1.8k views
ADD COMMENTlink modified 17 months ago by Tao300 • written 17 months ago by krushnach80500
gravatar for Tao
17 months ago by
Tao300 wrote:

I think the "sign" represents the sign of weight on the edges. If you care about the sign, for example sign represents positive or negative regulation between two nodes, then you need to choose "signed". On the other hand, if the weight just represent the strength of relatedness between two nodes, you might don't care positive or negative, so you need to choose "unsigned". That really depends on your needs.

ADD COMMENTlink written 17 months ago by Tao300

okay so i have cell lypes like stem cells and their downstream differentiated cells i m trying co-expression network .So what would you suggest me to do ?I have cell types like HSC,CMP,GMP,Monocyte, granulocytes etc..all together 20 samples..

Should I go for signed or unsigned ?

Any suggestion would be really helpful

ADD REPLYlink written 17 months ago by krushnach80500

For co-expression network, I would prefer unsigned weight. But you can try both, to find out which result looks more meaningful.

ADD REPLYlink written 17 months ago by Tao300
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