β-empirical Bayes inference and model diagnosis of microarray data.

ABSTRACT:

Background

Microarray data enables the high-throughput survey of mRNA expression profiles at the genomic level; however, he data presents a challenging statistical problem because of the large number of transcripts with small sample sizes that are obtained. To reduce the dimensionality, various Bayesian or empirical Bayes hierarchical models have been developed. However, because of the complexity of the microarray data, no model can explain the data fully. It is generally difficult to scrutinize the irregular patterns of expression that are not expected by the usual statistical gene by gene models.

Results

As an extension of empirical Bayes (EB) procedures, we have developed the β-empirical Bayes (β-EB) approach based on a β-likelihood measure which can be regarded as an 'ev

SUBMITTER: Mollah MM 

PROVIDER: S-EPMC3464654 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature