Using the theory of added-variable plot for linear mixed models to decompose genetic effects in family data

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Citações na Scopus
2
Tipo de produção
article
Data de publicação
2014
DOI
Scopus
Web of Science
PubMed
Título da Revista
ISSN da Revista
Título do Volume
Editora
WALTER DE GRUYTER GMBH
Autores
GIOLO, Suely R.
ANDRADE, Mariza de
SOLER, Julia P.
Citação
STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY, v.13, n.3, p.359-378, 2014
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
Effective analytical tools are highly desirable for data analysis and for making the biological link between genotypic and phenotypic measures. In family data it is important to reconcile the methods that explain the phenotypic variability through fixed genetic effects and ones that estimate variance components using classical heritability methods. Thus, in this paper, we propose a method based on added-variable plot for polygenic linear mixed models applied to genome wide association studies in family-based designs. Our goal is to be able to discriminate genetic predictor variables in effects due to random polygenic and residual components. We also propose an index to detect influential families for each predictor variable identified with genetic effect. We assess the performance of our proposed method using our own family simulated data and the Genetic Analysis Workshop 17 family simulated data.
Palavras-chave
association analysis, influential families, polygenic models, variance components
URI
https://observatorio.fm.usp.br/handle/OPI/7874
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Coleções
Artigos e Materiais de Revistas Científicas - LIM/13
Artigos e Materiais de Revistas Científicas - HC/InCor