Hello dear people,
I have been working with this statistical program WGCNA for building coexpression network for a large microarray dataset. I have completed the initial network building procedure. I am trying to characterize the genes within the modules for enrichment in biological processes. (http://labs.genetics.ucla.edu/horvath/CoexpressionNetwork/Rpackages/WGCNA/)
I retreived all the genes for a module and initially tried to build heatmap to check visually whether coexpression can be appreciated, I also plotted the eigengene expression values as a quantification. Here lies the issue.
Coexpression is observed for about 65 percent of the genes.But there are the rest that behave in just the opposite fashion across samples (when plotted for their expression values) but still considered as coexpressing by the program. Considering that coexpression is based on correlations, I expected that genes behaving in opposite fashion would fall in different modules rather than the same. I have also gone through literature where I do not see this problem happening. Is there something I am missing here? Would anyone from your experience have any clue? I have tried this across two different datasets and spot the same problem.
If I may add, I have mostly been using default parameters set by the authors except for increasing the softpowerthreshold to 9 (from 6) , and lowering the mergecutheight to 0.1 from the default 0.25.
Thanks a lot for your kind replies.
best regards, mohan