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COE: A General Approach for Efficient Genome-Wide Two-Locus Epistasis Test in Disease Association Study

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Research in Computational Molecular Biology (RECOMB 2009)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 5541))

Abstract

The availability of high density single nucleotide polymorphisms (SNPs) data has made genome-wide association study computationally challenging. Two-locus epistasis (gene-gene interaction) detection has attracted great research interest as a promising method for genetic analysis of complex diseases. In this paper, we propose a general approach, COE, for efficient large scale gene-gene interaction analysis, which supports a wide range of tests. In particular, we show that many commonly used statistics are convex functions. From the observed values of the events in two-locus association test, we can develop an upper bound of the test value. Such an upper bound only depends on single-locus test and the genotype of the SNP-pair. We thus group and index SNP-pairs by their genotypes. This indexing structure can benefit the computation of all convex statistics. Utilizing the upper bound and the indexing structure, we can prune most of the SNP-pairs without compromising the optimality of the result. Our approach is especially efficient for large permutation test. Extensive experiments demonstrate that our approach provides orders of magnitude performance improvement over the brute force approach.

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Authors and Affiliations

  1. Department of Computer Science, University of North Carolina at Chapel Hill, USA

    Xiang Zhang, Feng Pan & Wei Wang

  2. Department of Genetics, University of North Carolina at Chapel Hill, USA

    Yuying Xie

  3. Department of Biostatistics, University of North Carolina at Chapel Hill, USA

    Fei Zou

Authors
  1. Xiang Zhang
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  2. Feng Pan
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  3. Yuying Xie
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  4. Fei Zou
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  5. Wei Wang
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Editor information

Editors and Affiliations

  1. Computer Science Department, James H. Clark Center, 318 Campus Drive, RM S266, CA 94305-5428,, Stanford, USA

    Serafim Batzoglou

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© 2009 Springer-Verlag Berlin Heidelberg

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Zhang, X., Pan, F., Xie, Y., Zou, F., Wang, W. (2009). COE: A General Approach for Efficient Genome-Wide Two-Locus Epistasis Test in Disease Association Study. In: Batzoglou, S. (eds) Research in Computational Molecular Biology. RECOMB 2009. Lecture Notes in Computer Science(), vol 5541. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02008-7_19

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  • DOI: https://doi.org/10.1007/978-3-642-02008-7_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02007-0

  • Online ISBN: 978-3-642-02008-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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