Using Maximal Segmental Score in Genome-Wide Association Studies

Ying Chao Lin, Ching Lin Hsiao, Ai Ru Hsieh, Ie Bin Lian, Cathy S.J. Fann

研究成果: Article同行評審

3 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁(從 - 到)594-601
頁數8
期刊Genetic Epidemiology
36
發行號6
DOIs
出版狀態Published - 2012 九月 1

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Genetics(clinical)

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