淡江大學機構典藏:Item 987654321/117013
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/117013


    Title: Using maximal segmental score in genome-wide association studies
    Authors: YC, Lin;CL, Hsiao;Hsieh, Ai-Ru;IB, Lian;SJ, Fann Cathy
    Keywords: association test;multiple testing;GWAS;maximal segmental score
    Date: 2012-09
    Issue Date: 2019-09-17 12:11:40 (UTC+8)
    Publisher: Wiley Periodicals
    Abstract: Genome‐wide association studies (GWAS) have become the method of choice for identifying disease susceptibility genes in common disease genetics research. Despite successes in these studies, much of the heritability remains unexplained due to lack of power and low resolution. High‐density genotyping arrays can now screen more than 5 million genetic markers. As a result, multiple comparison has become an important issue especially in the era of next‐generation sequencing. We propose to use a two‐stage maximal segmental score procedure (MSS) which uses region‐specific empirical P‐values to identify genomic segments most likely harboring the disease gene. We develop scoring systems based on Fisher's P‐value combining method to convert locus‐specific significance levels into region‐specific scores. Through simulations, our result indicated that MSS increased the power to detect genetic association as compared with conventional methods provided type I error was at 5%. We demonstrated the application of MSS on a publicly available case‐control dataset of Parkinson's disease and replicated the findings in the literature. MSS provides an efficient exploratory tool for high‐density association data in the current era of next‐generation sequencing. R source codes to implement the MSS procedure are freely available at http://www.csjfann.ibms.sinica.edu.tw/EAG/program/programlist.htm.
    Relation: Genetic epidemiology 36(6), p.594–601
    DOI: 10.1002/gepi.21652
    Appears in Collections:[統計學系暨研究所] 期刊論文

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