Query large scale microarray compendium datasets using a model-based bayesian approach with variable selection.

ABSTRACT: In microarray gene expression data analysis, it is often of interest to identify genes that share similar expression profiles with a particular gene such as a key regulatory protein. Multiple studies have been conducted using various correlation measures to identify co-expressed genes. While working well for small datasets, the heterogeneity introduced from increased sample size inevitably reduces the sensitivity and specificity of these approaches. This is because most co-expression relationships do not extend to all experimental conditions. With the rapid increase in the size of microarray datasets, identifying functionally related genes from large and diverse microarray gene expression datasets is a key challenge. We develop a model-based gene expression query algorithm built under the

SUBMITTER: Hu M 

PROVIDER: S-EPMC2637418 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature