A noise-reduction GWAS analysis implicates altered regulation of neurite outgrowth and guidance in autism.

ABSTRACT:

Background

Genome-wide Association Studies (GWAS) have proved invaluable for the identification of disease susceptibility genes. However, the prioritization of candidate genes and regions for follow-up studies often proves difficult due to false-positive associations caused by statistical noise and multiple-testing. In order to address this issue, we propose the novel GWAS noise reduction (GWAS-NR) method as a way to increase the power to detect true associations in GWAS, particularly in complex diseases such as autism.

Methods

GWAS-NR utilizes a linear filter to identify genomic regions demonstrating correlation among association signals in multiple datasets. We used computer simulations to assess the ability of GWAS-NR to detect association against the commonly used joint

SUBMITTER: Hussman JP 

PROVIDER: S-EPMC3035032 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature