using WGCNA, positive or negative corrlation between genes composing modules.
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pharamac • 0
@a342a86d
Last seen 17 months ago
Hong Kong

Hello. I am trying to find a module using WGCNA and visualize the module network.

What I'm curious about is that I don't know how to find the correlation between "genes" that make up a module. Weight also represents correlation in terms of co-occurences(or co-expression), but it always has a positive value, so I wonder how to find a relationship between genes, which negatively correlated.

Finally I want to draw Networks having edges, Red representing Negative correlation and Blue showing Positive correlation. I am stucked with this so long times. Please help me.

I appreciate your comments.

correlation wgcna network • 949 views
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To find the positive and negative correlations between genes in a WGCNA module, calculate the correlation coefficients between gene expression profiles. Visualize the module network using a tool like Cytoscape, using blue edges for positive correlations and red edges for negative correlations. You can visit: https://github.com/Lindseynicer/omegle/WGCNA_tutorial

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@795d8150
Last seen 5 months ago
United States

According to a BMC Bioinformatics article, WGCNA can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. However, I could not find any information on how to find the correlation between genes that make up a module.

Regarding your question about how to find a relationship between genes that are negatively correlated, one possible solution is to use a combination of signed and unsigned WGCNA (csuWGCNA), which combines the signed and unsigned methods and improves the detection of negative correlations. According to a bioRxiv article, csuWGCNA was applied in 14 simulated datasets, six ground truth datasets, and two large human brain datasets.

Finally, you want to draw networks having edges, red representing negative correlation, and blue showing positive correlation. One possible solution is to use Cytoscape, which is a free and open-source software platform for visualizing molecular interaction networks and biological pathways. According to a GitHub repository, you can export the network files for visualization in Cytoscape and correlate the modules with external traits (discrete type), correlate the modules with external traits (continuous type), and further investigate particular module-trait relationships. You can also visualize the networks using scatterplots or bubble plots.

Reference: https://bmcbioinformatics.biomedcentral.com/articles/smash karts10.1186/1471-2105-9-559 and https://github.com/Lindseynicer/WGCNA_tutorial

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