4 months ago by
The short answer is no. The reason we are doing DE in the first place is to find those genes :-)
- If you are using a well establised, well tested (benchmarked) tool - and your p-value distribution looks good (for more information on this take a look at this blog) there is a good chance you have a good set.
- Please note that with datasets like TCGA breast cancer (or single cell data) you have so many samples that you have the power to detect very small changes. Therefore I would recomend to also use a cutoff on effect size (in this case the absolute log2FC). This can even be done in the statistical test (testing abs(log2FC) > x instead of the default abs(log2FC) > 0) in a number of tools.
- Lastly you can as Grant suggest do validations - this can both be experimental such as qPCR or by analysing other similar datasets.