I have three time courses RNA-seq data, each with 7 time points. Let's say: A0-A6, B0-B6 and C0-C6. Group A is the control. Group B and C are the treatment. Experiments were practiced in different chamber. A0, B0 and C0 should have the same expression pattern because there was no treatment. B1 and C1 should have the same expression pattern because at this time point they have the same treatment.
I extracted the FPKM value for each sample and constructed the co-expression gene network. I found that for some of the modules. A0, B0 and C0 have distinct expression patterns. B1 and C1 also have distinct expression patterns.
So I think probably there are con-founding factors I need to remove. What I think of is 1) A, B and C were in different chambers; 2) when constructing the RNA-seq library, they were constructed in different time or by different technician.
How can I to remove the con-founding factors to keep A0, B0 and C0 have similar expression pattern and B1 and C1 have similar expression pattern? I'm going to use DESeq2 to identify DEGs.
Can anyone give me some suggestions for the data analysis. Thanks.