Abstract
Family based association studies are employed less often than case-control designs in the search for disease-predisposing genes. The optimal statistical genetic approach for complex pedigrees is unclear when evaluating both common and rare variants. We examined the empirical power and type I error rates of 2 common approaches, the measured genotype approach and family-based association testing, through simulations from a set of multigenerational pedigrees. Overall, these results suggest that much larger sample sizes will be required for family-based studies and that power was better using MGA compared to FBAT. Taking into account computational time and potential bias, a 2-step strategy is recommended with FBAT followed by MGA.
Document Type
Article
Publication Date
6-17-2014
Digital Object Identifier (DOI)
http://dx.doi.org/10.1186/1753-6561-8-S1-S26
Funding Information
This work was supported in part by NIH grants 8P20GM103436-12 (DWF, KN), K25AG043546 (DWF), NS36695 (LD, LJM), AI070235 (HH, LJM, TBM), AI066738 (LJM), HL111459 (LJM, VP), T32-ES10957 (ESA), K12 HD001097-16 (BGK), K01HL103165 (TBM).
The GAW18 whole genome sequence data were provided by the T2D-GENES Consortium, which is supported by NIH grants U01 DK085524, U01 DK085584, U01 DK085501, U01 DK085526, and U01 DK085545. The other genetic and phenotypic data for GAW18 were provided by the San Antonio Family Heart Study and San Antonio Family Diabetes/Gallbladder Study, which are supported by NIH grants P01 HL045222, R01 DK047482, and R01 DK053889. The Genetic Analysis Workshop is supported by NIH grant R01 GM031575.
Related Content
This proceeding is from Genetic Analysis Workshop 18: Human Sequence Data in Extended Pedigrees, held in Stevenson, Washington from October 13-17, 2012.
More proceedings from this conference are available at: http://bmcproc.biomedcentral.com/articles/supplements/volume-8-supplement-1
Repository Citation
Fardo, David W.; Zhang, Xue; Ding, Lili; He, Hua; Kurowski, Brad; Alexander, Eileen S.; Mersha, Tesfaye B.; Pilipenko, Valentina; Kottyan, Leah; Nandakumar, Kannabiran; and Martin, Lisa, "On Family-Based Genome-Wide Association Studies with Large Pedigrees: Observations and Recommendations" (2014). Biostatistics Faculty Publications. 16.
https://uknowledge.uky.edu/biostatistics_facpub/16
Notes/Citation Information
Published in BMC Proceedings, v. 8, supplement 1, article S26, p. 1-5.
© Fardo et al.; licensee BioMed Central Ltd. 2014
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.