Population structure in genetic studies: Confounding factors and mixed models.
PLoS Genet
; 14(12): e1007309, 2018 12.
Article
en En
| MEDLINE
| ID: mdl-30589851
ABSTRACT
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 accurately test for association while correcting for population structure is a computational and statistical challenge. Using laboratory mouse strains as an example, our review characterizes the problem of population structure in association studies and describes how it can cause false positive associations. We then motivate mixed models in the context of unmodeled factors.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Estudio de Asociación del Genoma Completo
/
Genética de Población
/
Modelos Genéticos
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Animals
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Female
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Humans
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Male
Idioma:
En
Revista:
PLoS Genet
Asunto de la revista:
GENETICA
Año:
2018
Tipo del documento:
Article
País de afiliación:
Estados Unidos