The lack of random effects in the original DEseq2 R package was a huge oversight that causes false positives in cases of genotypically driven expression in experiments with multiple samples per donor. Fixing this here would require swapping sklearn for statsmodels, but it would be worth it for such a critical feature. Let me know how I can help.
The lack of random effects in the original DEseq2 R package was a huge oversight that causes false positives in cases of genotypically driven expression in experiments with multiple samples per donor. Fixing this here would require swapping sklearn for statsmodels, but it would be worth it for such a critical feature. Let me know how I can help.