Bayesian optimal discovery procedure for simultaneous significance testing.

ABSTRACT:

Background

In high throughput screening, such as differential gene expression screening, drug sensitivity screening, and genome-wide RNAi screening, tens of thousands of tests need to be conducted simultaneously. However, the number of replicate measurements per test is extremely small, rarely exceeding 3. Several current approaches demonstrate that test statistics with shrinking variance estimates have more power over the traditional t statistic.

Results

We propose a Bayesian hierarchical model to incorporate the shrinkage concept by introducing a mixture structure on variance components. The estimates from the Bayesian model are utilized in the optimal discovery procedure (ODP) proposed by Storey in 2007, which was shown to have optimal performance in multiple significance

SUBMITTER: Cao J 

PROVIDER: S-EPMC2628883 | biostudies-literature | 2009 Jan

REPOSITORIES: biostudies-literature