A ground truth based comparative study on detecting epistatic SNPs

Li Chen, Guoqiang Yu, David J. Miller, Lei Song, Carl Langefeld, David Herrington, Yongmei Liu, Yue Wang

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    12 Scopus citations

    Abstract

    Genome-wide association studies (GWAS) have been widely applied to identify informative SNPs associated with common and complex diseases. Besides single-SNP analysis, the interaction between SNPs is believed to play an important role in disease risk due to the complex networking of genetic regulations. While many approaches have been proposed for detecting SNP interactions, the relative performance and merits of these methods in practice are largely unclear. In this paper, a ground-truth based comparative study is reported involving 9 popular SNP detection methods using realistic simulation datasets. The results provide general characteristics and guidelines on these methods that may be informative to the biological investigators.

    Original languageEnglish (US)
    Title of host publicationProceedings - 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2009
    Pages26-31
    Number of pages6
    DOIs
    StatePublished - 2009
    Event2009 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2009 - Washington, DC, United States
    Duration: Nov 1 2009Nov 4 2009

    Publication series

    NameProceedings - 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2009

    Other

    Other2009 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2009
    CountryUnited States
    CityWashington, DC
    Period11/1/0911/4/09

    All Science Journal Classification (ASJC) codes

    • Biomedical Engineering
    • Health Informatics
    • Health Information Management

    Fingerprint Dive into the research topics of 'A ground truth based comparative study on detecting epistatic SNPs'. Together they form a unique fingerprint.

    Cite this