A unified mixed-model method for association mapping that accounts for multiple levels of relatedness.
Nat Genet
; 38(2): 203-8, 2006 Feb.
Article
en En
| MEDLINE
| ID: mdl-16380716
ABSTRACT
As population structure can result in spurious associations, it has constrained the use of association studies in human and plant genetics. Association mapping, however, holds great promise if true signals of functional association can be separated from the vast number of false signals generated by population structure. We have developed a unified mixed-model approach to account for multiple levels of relatedness simultaneously as detected by random genetic markers. We applied this new approach to two samples a family-based sample of 14 human families, for quantitative gene expression dissection, and a sample of 277 diverse maize inbred lines with complex familial relationships and population structure, for quantitative trait dissection. Our method demonstrates improved control of both type I and type II error rates over other methods. As this new method crosses the boundary between family-based and structured association samples, it provides a powerful complement to currently available methods for association mapping.
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Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Técnicas Genéticas
/
Zea mays
/
Herencia
/
Modelos Genéticos
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Nat Genet
Asunto de la revista:
GENETICA MEDICA
Año:
2006
Tipo del documento:
Article
País de afiliación:
Estados Unidos