my question is regarding the most common diff. expr. tools used (edger, deseq2, limma). As they are created before UMIs existed (where the overall set of data includes quite low copy numbers on all entries which seem like rare low expressed genes) did such data can be used with their statistical methods and normalization and get proper DEG results? I'm not a statistician but know that changing the scale of the data, dispersion, etc may cause bias in the results?