• Login
    View Item 
    •   Home
    • Office of Sponsored Research (OSR)
    • KAUST Funded Research
    • Publications Acknowledging KAUST Support
    • View Item
    •   Home
    • Office of Sponsored Research (OSR)
    • KAUST Funded Research
    • Publications Acknowledging KAUST Support
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of KAUSTCommunitiesIssue DateSubmit DateThis CollectionIssue DateSubmit Date

    My Account

    Login

    Quick Links

    Open Access PolicyORCID LibguideTheses and Dissertations LibguideSubmit an Item

    Statistics

    Display statistics

    A fast multilocus test with adaptive SNP selection for large-scale genetic-association studies

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Type
    Article
    Authors
    Zhang, Han
    Shi, Jianxin
    Liang, Faming
    Wheeler, William
    Stolzenberg-Solomon, Rachael
    Yu, Kai
    KAUST Grant Number
    KUS-C1-016-04
    Date
    2013-09-11
    Online Publication Date
    2013-09-11
    Print Publication Date
    2014-05
    Permanent link to this record
    http://hdl.handle.net/10754/597265
    
    Metadata
    Show full item record
    Abstract
    As increasing evidence suggests that multiple correlated genetic variants could jointly influence the outcome, a multilocus test that aggregates association evidence across multiple genetic markers in a considered gene or a genomic region may be more powerful than a single-marker test for detecting susceptibility loci. We propose a multilocus test, AdaJoint, which adopts a variable selection procedure to identify a subset of genetic markers that jointly show the strongest association signal, and defines the test statistic based on the selected genetic markers. The P-value from the AdaJoint test is evaluated by a computationally efficient algorithm that effectively adjusts for multiple-comparison, and is hundreds of times faster than the standard permutation method. Simulation studies demonstrate that AdaJoint has the most robust performance among several commonly used multilocus tests. We perform multilocus analysis of over 26,000 genes/regions on two genome-wide association studies of pancreatic cancer. Compared with its competitors, AdaJoint identifies a much stronger association between the gene CLPTM1L and pancreatic cancer risk (6.0 × 10(-8)), with the signal optimally captured by two correlated single-nucleotide polymorphisms (SNPs). Finally, we show AdaJoint as a powerful tool for mapping cis-regulating methylation quantitative trait loci on normal breast tissues, and find many CpG sites whose methylation levels are jointly regulated by multiple SNPs nearby.
    Citation
    Zhang H, Shi J, Liang F, Wheeler W, Stolzenberg-Solomon R, et al. (2013) A fast multilocus test with adaptive SNP selection for large-scale genetic-association studies. European Journal of Human Genetics 22: 696–702. Available: http://dx.doi.org/10.1038/ejhg.2013.201.
    Sponsors
    We thank three anonymous referees for their helpful comments. This study utilized the high-performance computational capabilities of the Biowulf Linux cluster at the National Institutes of Health, Bethesda, MD. (http://biowulf.nih.gov). The work of H Zhang, J Shi, R Stolzenberg-Solomon and K Yu were supported by the Intramural Program of the National Institutes of Health and the National Cancer Institute. The work of F Liang was supported in part by the National Science Foundation (DMS-0607755, CMMI-0926803); and the award (KUS-C1-016-04) made by the King Abdullah University of Science and Technology.
    Publisher
    Springer Nature
    Journal
    European Journal of Human Genetics
    DOI
    10.1038/ejhg.2013.201
    PubMed ID
    24022295
    PubMed Central ID
    PMC3992564
    ae974a485f413a2113503eed53cd6c53
    10.1038/ejhg.2013.201
    Scopus Count
    Collections
    Publications Acknowledging KAUST Support

    entitlement

    Related articles

    • Polymorphisms involving gain or loss of CpG sites are significantly enriched in trait-associated SNPs.
    • Authors: Zhou D, Li Z, Yu D, Wan L, Zhu Y, Lai M, Zhang D
    • Issue date: 2015 Nov 24
    • pLARmEB: integration of least angle regression with empirical Bayes for multilocus genome-wide association studies.
    • Authors: Zhang J, Feng JY, Ni YL, Wen YJ, Niu Y, Tamba CL, Yue C, Song Q, Zhang YM
    • Issue date: 2017 Jun
    • Genome-wide associations between genetic and epigenetic variation influence mRNA expression and insulin secretion in human pancreatic islets.
    • Authors: Olsson AH, Volkov P, Bacos K, Dayeh T, Hall E, Nilsson EA, Ladenvall C, Rönn T, Ling C
    • Issue date: 2014 Nov
    • Genetic control of individual differences in gene-specific methylation in human brain.
    • Authors: Zhang D, Cheng L, Badner JA, Chen C, Chen Q, Luo W, Craig DW, Redman M, Gershon ES, Liu C
    • Issue date: 2010 Mar 12
    • Mapping eQTL by leveraging multiple tissues and DNA methylation.
    • Authors: Acharya CR, Owzar K, Allen AS
    • Issue date: 2017 Oct 18
    DSpace software copyright © 2002-2023  DuraSpace
    Quick Guide | Contact Us | KAUST University Library
    Open Repository is a service hosted by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items. For anonymous users the allowed maximum amount is 50 search results.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.