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Bioinformatics Advance Access published online on October 16, 2009
Bioinformatics, doi:10.1093/bioinformatics/btp596
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© The Author (2009). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

INTERSNP: Genome-wide Interaction Analysis Guided by A Priori Information

Christine Herold 1, Michael Steffens 1, Felix F. Brockschmidt 2, Max P. Baur 1,3 and Tim Becker 1

1Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn, Sigmund-Freud-Str. 25, D-53105 Bonn, Germany.
2Institute of Human Genetics, Department of Genomics, Life & Brain Center, University of Bonn, Bonn,Germany.
3German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany

To whom correspondence should be addressed. Dr. Tim Becker, E-mail: becker{at}imbie.meb.uni-bonn.de


  Abstract

Summary: Genome-wide association studies (GWAS) have lead to the identification of hundreds of genomic regions associated with complex diseases. Nevertheless, a large fraction of their heritability remains unexplained. Interaction between genetic variants is one of several putative explanations for the "case of missing heritability" and, therefore, a compelling next analysis step. However, genomewide interaction analysis (GWIA) of all pairs of SNPs from a standard marker panel is computationally unfeasible without massive parallelization. Furthermore, GWIA of all SNP triples is utopian. In order to overcome these computational constraints, we present a GWIA approach that selects combinations of SNPs for interaction analysis based on a priori information. Sources of information are statistical evidence (single marker association at a moderate level), genetic relevance (genomic location) and biologic relevance (SNP function class and pathway information). We introduce the software package INTERSNP that implements a logistic regression framework as well as log-linear models for joint analysis of multiple SNPs. Automatic handling of SNP annotation and pathways from the KEGG database is provided. In addition, Monte-Carlo simulations to judge genome-wide significance are implemented. We introduce various meaningful GWIA strategies that can be conducted using INTERSNP. Typical examples are, for instance, the analysis of all pairs of nonsynonymous SNPs, or, the analysis of all combinations of three SNPs that lie in a common pathway and that are among the top 50,000 single-marker results. We demonstrate the feasibility of these and other GWIA strategies by application to a GWAS data set and discuss promising results.

Availability: The software is available at http://intersnp.meb.uni-bonn.de

Contact: herold{at}imbie.meb.uni-bonn.de; becker{at}imbie.meb.uni-bonn.de

Associate Editor: Dr. Jeffrey Barrett

Received on August 3, 2009; revised on September 4, 2009; accepted on September 23, 2009

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