Prediction of human disease genes by human-mouse conserved coexpression analysis.

ABSTRACT:

Background

Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates.

Methodology/principal findings

We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression prof

SUBMITTER: Ala U 

PROVIDER: S-EPMC2268251 | biostudies-literature | 2008 Mar

REPOSITORIES: biostudies-literature