A knowledge-based weighting framework to boost the power of genome-wide association studies.

ABSTRACT:

Background

We are moving to second-wave analysis of genome-wide association studies (GWAS), characterized by comprehensive bioinformatical and statistical evaluation of genetic associations. Existing biological knowledge is very valuable for GWAS, which may help improve their detection power particularly for disease susceptibility loci of moderate effect size. However, a challenging question is how to utilize available resources that are very heterogeneous to quantitatively evaluate the statistic significances.

Methodology/principal findings

We present a novel knowledge-based weighting framework to boost power of the GWAS and insightfully strengthen their explorative performance for follow-up replication and deep sequencing. Built upon diverse integrated biological knowledge

SUBMITTER: Li MX 

PROVIDER: S-EPMC3013112 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature