I'm helping a colleague analyse RNA-seq data to find differentially expressed genes. There are 4 conditions with 3 biological replicates each and we are interested in all possible pairwise comparisons. Unfortunately they made a big mistake by pooling RNA from each of the three biological replicates and sequencing as a single sample (i.e. they did not individually barcode each replicate). My colleague was using DESeq1 and was able to generate a list of diff expressed genes by analysing the data assuming no biological replicates. I encouraged using DESeq2 however this results in no differentially expressed genes being identified. I explained that without knowledge of gene expression variation its unlikely that anything can be done to statistically improve these results.
My question is, is there any technique/alternate method of analysis that the community could suggest? Or is their experiment essentially ruined?