Original Research ARTICLE
A Pragmatic Test for Detecting Association between a Dichotomous Trait and the Genotypes of Affected Families, Controls and Independent Cases
- 1Research Institute at Nationwide Children's Hospital, USA
- 2Departments of Statistics and Pediatrics, The Ohio State University, USA
The efficient analysis of hybrid designs [e.g. affected families, controls, and (optionally) independent cases] is attractive because it should have increased power to detect associations between genetic variants and disease. However, the computational complexity of such an analysis is not trivial, especially when the data contain pedigrees of arbitrary size and structure. To address this concern, we developed a pragmatic test for association that summarizes all of the available evidence in certain hybrid designs, irrespective of pedigree size or structure. Under the null hypothesis of no association, our proposed test statistic (POPFAM+) is the quadratic form of two correlated tests: a population-based test (e.g. wQLS), and a family-based test (e.g. PDT). We use the parametric bootstrap in conjunction with an estimate of the correlation to compute p-values, and we illustrate the potential for increased power when (1) the heritability of the trait is high; and, (2) the marker-specific association is driven by the over-representation of risk alleles in cases, and by the preferential transmission of risk alleles from heterozygous parents to their affected offspring. Based on simulation, we show that type I error is controlled, and that POPFAM+ is more powerful than wQLS or PDT alone. In a real data application, we used POPFAM+ to analyze 43 genes of a hybrid epilepsy study containing 85 affected families, 80 independent cases, 234 controls, and 118 reference samples from the International HapMap Project. The results of our analysis identified a promising epilepsy candidate gene for follow-up sequencing: malic enzyme 2 (ME2; min p<0.0084).
Keywords: Meta-analysis, Transmission disequilibrium, POPFAM+, Sequencing, Candidate gene association
Citation: Wang M and Stewart WC
Received: 05 Oct 2016;
Accepted: 06 Apr 2017.
Edited by:Mariza De Andrade, Mayo Clinic, USA
Reviewed by:Zhan Ye, Marshfield Clinic, USA
Karim Oualkacha, Université du Québec à Montréal, Canada
Copyright: © 2017 Wang and Stewart. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Meng Wang, Research Institute at Nationwide Children's Hospital, Columbus, USA, email@example.com