GLOGS: a fast and powerful method for GWAS of binary traits with risk covariates in related populations.

ABSTRACT:

Summary

Mixed model-based approaches to genome-wide association studies (GWAS) of binary traits in related individuals can account for non-genetic risk factors in an integrated manner. However, they are technically challenging. GLOGS (Genome-wide LOGistic mixed model/Score test) addresses such challenges with efficient statistical procedures and a parallel implementation. GLOGS has high power relative to alternative approaches as risk covariate effects increase, and can complete a GWAS in minutes.

Availability

Source code and documentation are provided at http://www.bioinformatics.org/~stanhope/GLOGS.

SUBMITTER: Stanhope SA 

PROVIDER: S-EPMC3356846 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature