Dealing with genetic (sub)structure in GWAS

Author: Y. Aulchenko
Submitted: Friday 6th of July 2012 10:03:46 AM
Submitted by: egf
Language: English
Content type: Learning resource
Educational levels: qc2, qc3


Genome-Wide Association Studies (GWAS) is a powerful tool for identifying loci involved in the control of complex traits. In most GWAS, study participants are assumed to be unrelated and coming from a single population. However, even for carefully designed studies, some degree of relatedness and population stratification is expected. This problem is even more pronounced in studies embed in genetically isolated populations. The genetic origin of study participants acts as a confounder, which, if not accounted for properly, induces false-positives and reduces power of genetic association analysis. In this talk, I will review statistical methods used to account for sub-structure in genetic association analyses, with an emphasize on one of the most flexible and powerful methods -- mixed-models (MM) based variance components approach. I will describe several statistical and computational approaches allowing substantial speed-up in MM-based computations.


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Original version - English

abstract confounding_bologna_web_5220.pdf

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Y. Aulchenko. Dealing with genetic (sub)structure in GWAS. EUROGENE portal. July 2012. online:



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