The Robustness of Generalized Estimating Equations for Association Tests in Extended Family DataSuktitipat B.a,c,d · Mathias R.A.b · Vaidya D.b · Yanek L.R.b · Young J.H.b · Becker L.C.b · Becker D.M.b · Wilson A.F.a · Fallin M.D.b, c
aGenometrics Section, Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, bDepartment of Medicine, Johns Hopkins Medical Institutions, and cDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md., USA; dDepartment of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
M. Daniele Fallin, PhD
615 N. Wolfe Street
Baltimore, MD 21205 (USA)
Tel. +1 410 955 3643, E-Mail firstname.lastname@example.org
Do you have an account?
Variance components analysis (VCA), the traditional method for handling correlations within families in genetic association studies, is computationally intensive for genome-wide analyses, and the computational burden of VCA increases with family size and the number of genetic markers. Alternative approaches that do not require the computation of familial correlations are preferable, provided that they do not inflate type I error or decrease power. We performed a simulation study to evaluate practical alternatives to VCA that use regression with generalized estimating equations (GEE) in extended family data. We compared the properties of linear regression with GEE applied to an entire extended family structure (GEE-EXT) and GEE applied to nuclear family structures split from these extended families (GEE-SPL) to variance components likelihood-based methods (FastAssoc). GEE-EXT was evaluated with and without robust variance estimators to estimate the standard errors. We observed similar average type I error rates from GEE-EXT and FastAssoc compared to GEE-SPL. Type I error rates for the GEE-EXT method with a robust variance estimator were marginally higher than the nominal rate when the minor allele frequency (MAF) was <0.1, but were close to the nominal rate when the MAF was ≥0.2. All methods gave consistent effect estimates and had similar power. In summary, the GEE framework with the robust variance estimator, the computationally fastest and least data management-intensive approach, appears to work well in extended families and thus provides a reasonable alternative to full variance components approaches for extended pedigrees in a genome-wide association study setting.
© 2012 S. Karger AG, Basel
Article / Publication Details
Copyright / Drug Dosage / DisclaimerCopyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher or, in the case of photocopying, direct payment of a specified fee to the Copyright Clearance Center.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.