Dealing with genetic (sub)structure in GWAS

Contents

• Topics
• Abstract
• Preview
• Learning packages
• Similar resources
• Download
• Export
• Citation
• Keywords
• Rating

Topics

• Genetics + genomics
• Clinical/medical genetics
• Statistical genetics
• Statistical genetics > Genetic epidemiology > Gene discovery > Genome-wide
• Statistical genetics > Genetic epidemiology > Gene discovery > Genome-wide > Association (Genome-wide)

Abstract

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.

Preview

Learning packages

This resource is part of the following learning package:

• ESGM 1st Course on Molecular and Statistical Genetics of Consanguinity

Similar resources

Download

Original version - English

abstract confounding_bologna_web_5220.pdf

Export

IMS Metadata

Citation

Y. Aulchenko. Dealing with genetic (sub)structure in GWAS. EUROGENE portal. July 2012. online: http://eurogene.open.ac.uk/content/dealing-genetic-substructure-gwas

Keywords

additive, allele, association, base, confounder, correlation, drift, frequency, genetic isolates, genome, genome wide association, genotype, heritability, ibs, identity by descent, linkage disequilibrium, locus, marker, merlin, mixed model, pedigree, phenotype, polygenic, population, population isolate, power, quantitative trait, regression, segregation, selection, single nucleotide polymorphism, test statistics, threshold, trait, variant, variation, vector

Rating

Terms of use

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported License. Read more.