Univ. Bordeaux, INSERM Bordeaux Population Health Research Center, U1219, INRIA SISTM, Bordeaux, F-33000, France.
Vaccine Research Institute, Créteil, F-94000, France.
Genome Biol. 2024 Oct 30;25(1):281. doi: 10.1186/s13059-024-03231-9.
A recent study reported exaggerated false positives by popular differential expression methods when analyzing large population samples. We reproduce the differential expression analysis simulation results and identify a caveat in the data generation process. Data not truly generated under the null hypothesis led to incorrect comparisons of benchmark methods. We provide corrected simulation results that demonstrate the good performance of dearseq and argue against the superiority of the Wilcoxon rank-sum test as suggested in the previous study.
最近的一项研究报告称,在分析大型人群样本时,流行的差异表达方法得出了夸张的假阳性结果。我们重现了差异表达分析的模拟结果,并发现了数据生成过程中的一个注意事项。数据并非真正在零假设下生成,导致基准方法的比较出现错误。我们提供了经过修正的模拟结果,证明了 dearseq 的良好性能,并反驳了之前研究中提出的 Wilcoxon 秩和检验具有优越性的观点。