Costs and Benefits of Popular P-Value Correction Methods in Three Models of Quantitative Omic Experiments.

ABSTRACT: The multiple hypothesis testing problem is inherent in large-scale quantitative "omic" experiments such as mass spectrometry-based proteomics. Yet, tools for comparing the costs and benefits of different p-value correction methods under different experimental conditions are lacking. We performed thousands of simulations of omic experiments under a range of experimental conditions and applied correction using the Benjamini-Hochberg (BH), Bonferroni, and permutation-based false discovery proportion (FDP) estimation methods. The tremendous false discovery rate (FDR) benefit of correction was confirmed in a range of different contexts. No correction method can guarantee a low FDP in a single experiment, but the probability of a high FDP is small when a high number and proportion of corr

SUBMITTER: Shuken SR 

PROVIDER: S-EPMC10653731 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature