I have an RNA-seq dataset which comprises 4 different conditions, and 2 biological replicates per condition, like so:
cond1_1 cond1_2 cond2_1 cond2_2 cond3_1 cond3_2 cond4_1 cond4_2 gene1 gene2 gene3 gene4 gene5
Currently, I have been performing the
sizeFactors function, as well as the
estimateDispersions function on each table of 2 conditions (4 samples) at a time (the comparison in turn). I make the data frame pertaining ONLY to
comparison.X , then do
estimateDispersions, then run the negative binomial Test on those results.
I am wondering, however, if it is best to supply DESeq with all the samples to
estimateSizeFactors and estimateDispersions, and then run the paired-condition comparisons. Might this provide more information per gene, or would it be counterproductive?