Toggle Main Menu Toggle Search

Open Access padlockePrints

A General framework for two-stage analysis of genome-wide association studies and its application to case-control studies

Lookup NU author(s): Professor James WasonORCiD


Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Two-stage analyses of genome-wide association studies have been proposed as a means to improving power for designs including family-based association and gene-environment interaction testing. In these analyses, all markers are first screened via a statistic that may not be robust to an underlying assumption, and the markers thus selected are then analyzed in a second stage with a test that is independent from the first stage and is robust to the assumption in question. We give a general formulation of two-stage designs and show how one can use this formulation both to derive existing methods and to improve upon them, opening up a range of possible further applications. We show how using simple regression models in conjunction with external data such as average trait values can improve the power of genome-wide association studies. We focus on case-control studies and show how it is possible to use allele frequencies derived from an external reference to derive a powerful two-stage analysis. An illustration involving the Wellcome Trust Case-Control Consortium data shows several genome-wide-significant associations, subsequently validated, that were not significant in the standard analysis. We give some analytic properties of the methods and discuss some underlying principles. © 2012 by The American Society of Human Genetics. All rights reserved.

Publication metadata

Author(s): Wason JMS, Dudbridge F

Publication type: Article

Publication status: Published

Journal: American Journal of Human Genetics

Year: 2012

Volume: 90

Issue: 5

Pages: 760-773

Print publication date: 04/05/2012

Online publication date: 03/05/2012

ISSN (print): 0002-9297

ISSN (electronic): 1537-6605

Publisher: Cell Press


DOI: 10.1016/j.ajhg.2012.03.007

PubMed id: 22560088


Altmetrics provided by Altmetric