Statistical analysis of differential gene expression relative to a fold change threshold on NanoString data of mouse odorant receptor genes.

ABSTRACT:

Background

A challenge in gene expression studies is the reliable identification of differentially expressed genes. In many high-throughput studies, genes are accepted as differentially expressed only if they satisfy simultaneously a p value criterion and a fold change criterion. A statistical method, TREAT, has been developed for microarray data to assess formally if fold changes are significantly higher than a predefined threshold. We have recently applied the NanoString digital platform to study expression of mouse odorant receptor genes, which form with 1,200 members the largest gene family in the mouse genome. Our objectives are, on these data, to decrease false discoveries when formally assessing the genes relative to a fold change threshold, and to provide a guided selection

SUBMITTER: Vaes E 

PROVIDER: S-EPMC4016238 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature