Briefly, I want to identify differentially expressed genes from RNA-seq data using DESeq2.
I have three conditions and I want to compare the three conditions to each other.
Usually, I perform pairwise comparison building the dds file with the two conditions that I want to compare and subsequently I run DESeq2 on the dds object. I would like to ask if there are any differences between two approaches:
- Approach 1: perform separately each pairwise comparison as I described above
- Approach 2: perform the analysis including the three conditions in the dds object and then run the contrast function to extract the comparison that I want to analyse.
In particular, are there any differences between the two approaches in the normalization of count data and in the differential expression analysis? For example, if I have a condition with more variability than the other two conditions, this can affect the identification of differentially expressed genes in Approach 2? In addition, I was wondering if the Approach 1 is able to highlight more differences, even the smallest one between the conditions, in comparison with the results obtained from the Approach 2.