title: Multivariate Gene-Based Association Test on Family Data in MGAS.
abstract: In analyses of unrelated individuals, the program multivariate gene-based association test by extended Simes (MGAS), which facilitates multivariate gene-based association testing, was shown to have correct Type I error rate and superior statistical power compared to other multivariate gene-based approaches. Here we show, through simulation, that MGAS can also be applied to data including genetically related subjects (e.g., family data), by using p value information obtained in Plink or in generalized estimating equations (with the 'exchangeable' working correlation matrix), both of which account for the family structure on a univariate single nucleotide polymorphism-based level by applying a sandwich correction of standard errors. We show that when applied to family-data, MGAS has correct Type I error rate, and given the details of the simulation setup, adequate power. Application of MGAS to seven eye measurement phenotypes showed statistically significant association with two genes that were not discovered in previous univariate analyses of a composite score. We conclude that MGAS is a useful and convenient tool for multivariate gene-based genome-wide association analysis in both unrelated and related individuals.
authors.affiliation: Department of Clinical Genetics, Section Complex Traits Genetics, VU Medical Center (VUmc), Neuroscience Campus Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands. c.vroom@vu.nl.
authors.forename: César-Reyer
authors.identifier: 0000-0001-8871-4777
authors.initials: CR
authors.lastname: Vroom
authors.affiliation: Department of Clinical Genetics, Section Complex Traits Genetics, VU Medical Center (VUmc), Neuroscience Campus Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands.|Department of Complex Traits Genetics, Center for Neurogenomics and Cognitive Research (CNCR), VU University, Neuroscience Campus Amsterdam, Amsterdam, The Netherlands.
authors.forename: Danielle
authors.initials: D
authors.lastname: Posthuma
authors.affiliation: Department of Psychiatry, The University of Hong Kong, Pokfulam, Hong Kong.|State Key Laboratory for Cognitive and Brain Sciences, The University of Hong Kong, Pokfulam, Hong Kong.|The Centre for Reproduction, Development and Growth, The University of Hong Kong, Pokfulam, Hong Kong.|The Centre for Genomic Sciences, The University of Hong Kong, Pokfulam, Hong Kong.
authors.forename: Miao-Xin
authors.initials: MX
authors.lastname: Li
authors.affiliation: Department of Biological Psychology, VU University Amsterdam, Van der Boechorststraat 1, 1081 BT, Amsterdam, The Netherlands.
authors.forename: Conor V
authors.initials: CV
authors.lastname: Dolan
authors.affiliation: Department of Clinical Genetics, Section Complex Traits Genetics, VU Medical Center (VUmc), Neuroscience Campus Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands.
authors.forename: Sophie
authors.initials: S
authors.lastname: van der Sluis
mesh_terms: D003198:Computer Simulation; D005190:Family; D055106:Genome-Wide Association Study; D006801:Humans; D015999:Multivariate Analysis; D009216:Myopia / Q000235:genetics
keywords: Family data; GATES; GWAS; Gene-based; MGAS; Multivariate; TATES