WCGNA: Using Eigengenes when correlating modules to external features? What about PC2, PC3???
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Julieta • 0
Last seen 10 months ago

I'm doing a WCGNA analysis (signed network) on microbiome 16S data. I have transformed counts to centeres log-ratio transformed data (CLR) to address the compositional characteristics of the data and have obtained a pretty decent cluster (around 7 modules, 20 taxa each).

I correlated the different modules eigengenes to my features of interest using both bicor and pearson correlation measures. Overall, the results I'm getting make sense but I'm having some questions regarding the method: The % of variance explained of each eigengen is around 30%. Is this value normal? Is it ok that I'm using only the PC1 of the module as a summary of the module itself when variances explained of the PC1 are so low?


Network Transcriptomics MicrobiomeData RNASEQ WCGNA • 317 views

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