Thanks for your quick response. I'll check WGCNA.
Hi,
I have treatment-control time course RNA-seq data. I have 7 time points for both control and treatment. Currently, I already use edgeR to identify the differentially expressed genes considering the RNA-seq data as time course data.
I got around 2000 DE genes. Then I'd like to construct co-express network to classify these DE genes for functional analysis. The problem is I have two time courses. How should I treat the data when constructing the co-expression gene? Or what methods or tools should I use for such datasets? Thanks.
1 answer
I suppose you simply want to work on the genes' correlation across the time points for each condition. So, I believe you should draw one co-express network for each condition (two networks in total for control and treatment). Then, you can compare the differences in the co-express networks.
As for method, I believe WGCNA suits your purpose well.
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