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Bioinformatics Advance Access originally published online on November 19, 2008
Bioinformatics 2009 25(1):132-133; doi:10.1093/bioinformatics/btn563
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

A multivariate test of association

Manuel A. R. Ferreira 1,2,3,4,5,* and Shaun M. Purcell 1,2,3,4,6,7

1Department of Psychiatry, Massachusetts General Hospital, 2Department of Psychiatry, Harvard Medical School, 3Center for Human Genetic Research, Massachusetts General Hospital, Boston, 4Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA, 5Genetic Epidemiology, Queensland Institute of Medical Research, QLD, Australia, 6Broad Institute of Harvard and MIT, Cambridge and 7Psychiatric & Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA

*To whom correspondence should be addressed.


  Abstract

Summary: Although genetic association studies often test multiple, related phenotypes, few formal multivariate tests of association are available. We describe a test of association that can be efficiently applied to large population-based designs.

Availability: A C++ implementation can be obtained from the authors.

Contact: manuel.ferreira{at}qimr.edu.au

Supplementary information: Supplementary figures are available at Bioinformatics online.

Associate Editor: Alex Bateman

Received on August 3, 2008; revised on October 22, 2008; accepted on October 24, 2008

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