Hi,
I'd like to ask about your opinion on using pseudocounts in DE analysis, as some people say they're absolutely necessary some disagree ...
I've read all the vignettes - still no unclear, hence decided to test it on my data
I did comparison between DEseq, edgeR, BaySeq and cuffDiff on RNAseq data (these are tophat genes, HTseq tables, FDR = 10% for all)
please see the file
In case of condition 1 it seems clear DESeq performs best, but in condition 2 it appears most affected by pseudocounts detecting about 1600 in case 1, 2000 in case2 with only 1000 overlap
any suggestions?
I'd like to ask about your opinion on using pseudocounts in DE analysis, as some people say they're absolutely necessary some disagree ...
I've read all the vignettes - still no unclear, hence decided to test it on my data
I did comparison between DEseq, edgeR, BaySeq and cuffDiff on RNAseq data (these are tophat genes, HTseq tables, FDR = 10% for all)
please see the file
In case of condition 1 it seems clear DESeq performs best, but in condition 2 it appears most affected by pseudocounts detecting about 1600 in case 1, 2000 in case2 with only 1000 overlap
any suggestions?
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