The 'miss rate' for the analysis of gene expression data

Abstract
Multiple testing issues are important in gene expression studies, where typically thousands of genes are compared over two or more experimental conditions. The false discovery rate has become a popular measure in this setting. Here we discuss a complementary measure, the ‘miss rate’, and show how to estimate it in practice.

This publication has 0 references indexed in Scilit: