Correction for multiple testing in candidate-gene methylation studies.

ABSTRACT: Aim: We compared the performance of multiple testing corrections for candidate gene methylation studies, namely Sidak (accurate Bonferroni), false-discovery rate and three adjustments that incorporate the correlation between CpGs: extreme tail theory (ETT), Gao et al. (GEA), and Li and Ji methods. Materials & methods: The experiment-wide type 1 error rate was examined in simulations based on Illumina EPIC and 450K data. Results: For high-correlation genes, Sidak and false-discovery rate corrections were conservative while the Li and Ji method was liberal. The GEA method tended to be conservative unless a threshold parameter was adjusted. The ETT yielded an appropriate type 1 error rate. Conclusion: For genes with substantial correlation across measured Cp

SUBMITTER: Zhou Z 

PROVIDER: S-EPMC7132638 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature