I got a RNA-seq data from the extraction of cellular droplet. Thanks to extraction method, a fraction of cytosol material : droplets, mixed with RNA and protein are separated from the whole cytosol. And now I want to do a comparison between all RNA in cell and RNA present in droplet like organelles in cytosols.
After deseq2 analysis, 78% of genes are differentially "expressed" . I put "expressed" here because those genes are not really expressed differently, they just concentrate at a special cellular organelle or enriched at that special organelle. the RNA's composition in this organelle is not the same as whole transcriptome in cell
And my concern is about that Deseq2 make an assumption about the majority of genes shoud not be differentially expressed. So with this huge percentage of differentially "expressed" gene, is deseq2 statistical model still good?
if a data is naturally very different between control and sample, can we still use deseq2 for the statistical analysis? any bias for the p value?