PT  - JOURNAL ARTICLE
AU  - Martin, Lana S.
AU  - Eskin, Eleazar
TI  - Review: Population Structure in Genetic Studies: Confounding Factors and Mixed Models
AID  - 10.1101/092106
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 092106
4099  - http://biorxiv.org/content/early/2016/12/07/092106.short
4100  - http://biorxiv.org/content/early/2016/12/07/092106.full
AB  - A genome-wide association study (GWAS) seeks to identify genetic variants that contribute to the development and progression of a specific disease. Over the past 10 years, new approaches using mixed models have emerged to mitigate the deleterious effects of population structure and relatedness in association studies. However, developing GWAS techniques to effectively test for association while correcting for population structure is a computational and statistical challenge. Our review motivates the problem of population structure in association studies using laboratory mouse strains and how it can cause false positives associations. We then motivate mixed models in the context of unmodeled factors.