WGCNA module and traits correlation
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17 months ago

Hi All, I have a question about the WGCNA module and traits correlation. This is the heatmap I had. enter image description here The trait is kind of exposure time, from the heatmap, there's one "lightblue" module indicated high correlation (red) with correlation coefficient 0.89, very small p value.After getting this heatmap, I output my "lightblue" module and input it to the cytoscape to visualize the network. My question is that this module is only for the 2h exposure network or for all the time points network together? My goal is to compare the 2h exposure to baseline. I only have 6 samples for each timepoint, it is not reasonable (too small) to sperate the time point for the heatmap and network.

Any suggestions would be appreciated.

cytoscape traits module WGCNA • 1.3k views
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Entering edit mode
17 months ago
LChart 3.9k

The The above correlations reflect the correlation between the module eigengene within each exposure time, and whatever your response trait is -- it is not clear from your post.

The network you have is the consensus network across all timepoints; while the network activity (summarized by the module eigengene) varies from timepoint to timepoint.

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Thanks for your quick response. Really appreciate it. For the network visualization, I exported my network output with the "lightblue1" module, which corresponded the 2h high correlation module. Based on you explanation, the network would be the consensus network across all timepoints. Do we have any way to see the difference network between baseline and 2h?

Select module

module = "lightblue1"

Select module probes

probes = colnames(datExpr) inModule = (moduleColors==module) modProbes = probes[inModule]

Select the corresponding Topological Overlap

modTOM = TOM[inModule, inModule] dimnames(modTOM) = list(modProbes, modProbes)

cyt = exportNetworkToCytoscape(modTOM, edgeFile = paste("CytoscapeInput-edges-", paste(module, collapse="-"), ".txt", sep=""), nodeFile = paste("CytoscapeInput-nodes-", paste(module, collapse="-"), ".txt", sep=""), weighted = TRUE, threshold = 0.02, nodeNames = modProbes, nodeAttr = moduleColors[inModule])

Thanks again!

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Do we have any way to see the difference network between baseline and 2h?

No, you can't. You would need a network for the baseline and a network for the 2h, and then run a differential network analysis

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My 2h and baseline only have 6 samples, respectively. Do you think it is not robust or reasonable for the analysis? Because, when I check the soft thresholding power with 6 samples, the R square is very low, less than 0.65.

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you can't build a network with 6 samples

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Thanks for your reply. This is helpful.

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