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Response to "Neglecting normalization impact in semi-synthetic RNA-seq data simulation generates artificial false
Xinzhou Ge1,2, Yumei Li3,4, Wei Li5
1Department of Statistics and Data Science, University of California, Los Angeles, CA, 90095, USA.
Abstract:
Two correspondences raised concerns or comments about our analyses regarding exaggerated false positives found by differential expression (DE) methods. Here, we discuss the points they raise and explain why we agree or disagree with these points. We add new analysis to confirm that the Wilcoxon rank-sum test remains the most robust method compared to the other five DE methods (DESeq2, edgeR, limma-voom, dearseq, and NOISeq) in two-condition DE analyses after considering normalization and winsorization, the data preprocessing steps discussed in the two correspondences.

