Estimating the proportion of true null hypotheses with application in microarray data

Abstract

A new formulation for the proportion of true null hypotheses based on the sum of all p-values and the average of expected p-values under the false null hypotheses has been proposed in the current work. This formulation of the parameter of interest π 0 has also been used to construct a new estimator for the same. The proposed estimator removes the problem of choosing tuning parameters in the existing estimators. Though the formulation is quite general, computation of the new estimator requires use of an initial estimate of π 0. The issue of choosing an appropriate initial estimator is also discussed in this work. The current work assumes normality for the expression level of each gene and also assumes similar tests for all the hypotheses. Simulation study shows that, the proposed estimator performs better than its closest competitor over a substantial continuous subinterval of the parameter space, under independence and weak dependence among the gene expression levels. The proposed method of estimation is applied to two real gene expression level data-sets and the results are in line with what is obtained by the competing method.