Exaggerated false positives by popular differential expression methods when analyzing human population samples.
Genome Biol
; 23(1): 79, 2022 03 15.
Article
em En
| MEDLINE
| ID: mdl-35292087
ABSTRACT
When identifying differentially expressed genes between two conditions using human population RNA-seq samples, we found a phenomenon by permutation analysis:
two popular bioinformatics methods, DESeq2 and edgeR, have unexpectedly high false discovery rates. Expanding the analysis to limma-voom, NOISeq, dearseq, and Wilcoxon rank-sum test, we found that FDR control is often failed except for the Wilcoxon rank-sum test. Particularly, the actual FDRs of DESeq2 and edgeR sometimes exceed 20% when the target FDR is 5%. Based on these results, for population-level RNA-seq studies with large sample sizes, we recommend the Wilcoxon rank-sum test.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Biologia Computacional
/
Perfilação da Expressão Gênica
Limite:
Humans
Idioma:
En
Revista:
Genome Biol
Assunto da revista:
BIOLOGIA MOLECULAR
/
GENETICA
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Estados Unidos