Abstract
陈峰,柏建岭,赵杨,苟鹏程.全基因组关联研究中的统计分析方法[J].Chinese journal of Epidemiology,2011,32(4):400-404
全基因组关联研究中的统计分析方法
Statistical methodologies used in genome-wide association studies
Received:October 29, 2010  
DOI:
KeyWord: 全基冈组关联研究  质量控制  数据管理  统计分析
English Key Word: Geuome-wide association study  Quality control  Data management  Statistical analysis
FundProject:国家自然科学基金(30901232,81072389);江苏省高校自 然科学基金重大项目(1 0KJA33034)
Author NameAffiliationE-mail
Chen Feng Depanmem of Epidemiology and Health Statistics, School of Public Health, Nanjing Medical Unwersay. Nanjing 210029, China fengchen@njmu.edu.cn 
Bai jianling Depanmem of Epidemiology and Health Statistics, School of Public Health, Nanjing Medical Unwersay. Nanjing 210029, China  
Zhao Yang Depanmem of Epidemiology and Health Statistics, School of Public Health, Nanjing Medical Unwersay. Nanjing 210029, China  
Xun Pengcheng Depanmem of Epidemiology and Health Statistics, School of Public Health, Nanjing Medical Unwersay. Nanjing 210029, China  
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Abstract:
      随着人类基因组计划的完成,疾病的全基因组关联研究成为可能。该类研究的数据特点是:高维、小样本。面对浩瀚的数据,传统分析方法受到严重挑战。文中介绍全基因组关联研究中的数据分析策略和步骤,包括质量控制、分析、结果表示等,并对全基因组关联研究的局限性和目前统计分析方法的不足进行讨论。
English Abstract:
      In lieu of large samples of cases and/or controls with hundreds of markers spreading throughout the human ganome,researchers started to notice the dramatic increase of genome—wide association study(GWAS)for complex disorders.in the last 5 years.This paper highlights the statistical challenges in such huge—scale genetic studies,and introduces the analytical strategies and steps for handling GWAS data.Such issues as quality control of data,population stratification,methods available to data analysis and msults presentation,replication,as well as the limitations of GWAS studies and the challenges presenting for statistics,ale addressed.
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