Hi,
I have run some of my own data through the CRISPRanalyzeR and caRpools stat.DESeq or stat.wilcox functions and I seem to get different results.
Could you please suggest some explanations? Are there some additional normalisation steps executed before these functions are called?
Intriguingly, in deseq the baseMean columns have pretty much the same values, while foldchanges are different (also the rank of the genes changes). (This also suggest to me this is not due to problems with gene aggregation?)
In the Wilcoxson analysis, also the treated and untreated columns are very different (with values two order of magnitude higher CRISPRanalyzeR).
Hi, I have run some of my own data through the CRISPRanalyzeR and caRpools stat.DESeq or stat.wilcox functions and I seem to get different results. Could you please suggest some explanations? Are there some additional normalisation steps executed before these functions are called?
Intriguingly, in deseq the baseMean columns have pretty much the same values, while foldchanges are different (also the rank of the genes changes). (This also suggest to me this is not due to problems with gene aggregation?)
In the Wilcoxson analysis, also the treated and untreated columns are very different (with values two order of magnitude higher CRISPRanalyzeR).
I would be every grateful for your advice.
Patrycja