Adjusting for gene-specific covariates to improve RNA-seq analysis.

ABSTRACT:

Summary

This article suggests a novel positive false discovery rate (pFDR) controlling method for testing gene-specific hypotheses using a gene-specific covariate variable, such as gene length. We suppose the null probability depends on the covariate variable. In this context, we propose a rejection rule that accounts for heterogeneity among tests by using two distinct types of null probabilities. We establish a pFDR estimator for a given rejection rule by following Storey's q-value framework. A condition on a type 1 error posterior probability is provided that equivalently characterizes our rejection rule. We also present a suitable procedure for selecting a tuning parameter through cross-validation that maximizes the expected number of hypotheses declared significant. A simulatio

SUBMITTER: Jeon H 

PROVIDER: S-EPMC10460482 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature