Hi! This has been a conundrum for me these past months. There are some packages like cqn (conditional quantile normalization) and EDASeq that can be used to normalize for sample-specific gene GC content and/or length biases, which can alter functional enrichment analysis results.
My question is, when is it appropiate to use these normalization techniques? I have some GSEA results that change drastically after normalizing with
cqn, going from 17 to 109 significant GO terms, but I'm not really sure if it's correct to do this.
Thanks for reading :)