MiningABs: mining associated biomarkers across multi-connected gene expression datasets.

ABSTRACT:

Background

Human disease often arises as a consequence of alterations in a set of associated genes rather than alterations to a set of unassociated individual genes. Most previous microarray-based meta-analyses identified disease-associated genes or biomarkers independent of genetic interactions. Therefore, in this study, we present the first meta-analysis method capable of taking gene combination effects into account to efficiently identify associated biomarkers (ABs) across different microarray platforms.

Results

We propose a new meta-analysis approach called MiningABs to mine ABs across different array-based datasets. The similarity between paired probe sequences is quantified as a bridge to connect these datasets together. The ABs can be subsequently identified from an "

SUBMITTER: Cheng CP 

PROVIDER: S-EPMC4068973 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature