Sistema FMUSP-HC: Faculdade de Medicina da Universidade de São Paulo (FMUSP) e Hospital das Clínicas da FMUSPDUARTE, Nubia E.GIOLO, Suely R.PEREIRA, Alexandre C.ANDRADE, Mariza deSOLER, Julia P.2014-09-302014-09-302014STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY, v.13, n.3, p.359-378, 20142194-6302https://observatorio.fm.usp.br/handle/OPI/7874Effective 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.engrestrictedAccessassociation analysisinfluential familiespolygenic modelsvariance componentsassociation analysisquantitative traitsvariance-componentslinkage analysisregressionpedigreesarticleCopyright WALTER DE GRUYTER GMBH10.1515/sagmb-2013-0057Biochemistry & Molecular BiologyMathematical & Computational BiologyStatistics & Probability1544-6115