README.md

In JamesYuDai/HDMT: A Multiple Testing Procedure for High-Dimensional Mediation Hypotheses

HDMT

An R package implementing the multiple-testing procedure for high-dimensional mediation analyses

Mediation analysis is of rising interest in clinical trials and epidemiology. The advance of high-throughput technologies has made it possible to interrogate molecular phenotypes such as gene expression and DNA methylation in a genome-wide fashion, some of which may act as intermediaries of treatment, external exposures and life-style risk factors in the etiological pathway to diseases or traits. When testing for mediation in high-dimensional studies, properly controlling the type I error rate remains a challenge due to the composite null hypothesis.

Among existing methods, the joint significance (JS) test is an intersection-union test using the maximum p-value for testing the two parameters, though a naive significance rule based on the uniform null p-value distribution (JS-uniform) may yield an overly conservative type I error rate and therefore low power. This is particularly a concern for high-dimensional mediation hypotheses for genome-wide molecular intermediaries such as DNA methylation.

In this R package we develop a multiple-testing procedure that accurately controls the family-wise error rate (FWER) and the false discovery rate (FDR) for testing high-dimensional mediation composite null hypotheses. The core of our procedure is based on estimating the proportions of three types of component null hypotheses and deriving the corresponding mixture distribution (JS-mixture) of null p-values.

The R package has the following functions - null_estimation(): compute the three null proportions - adjust_quantile(): compute the adjusted null quantiles for the input p-values, using the mixture null distribution - fdr_est(): compute the false discovery rate of the input p-values - fwer_est(): compute the family-wise error rate of the input p-values - correct_qqplot(): draw the q-q plots using the corrected null quantiles.

JamesYuDai/HDMT documentation built on Feb. 18, 2022, 3:42 a.m.