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SHEsisPCA: A GPU-Based Software to Correct for Population Stratification that Efficiently Accelerates the Process for Handling Genome-Wide Datasets

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作者单位 Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders(Ministry of Education), Shanghai Jiao Tong University,Shanghai 200230, China; Institute of Social Cognitive and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai 200240, China;School of Bio-medical Engineering, Shanghai Jiao Tong University, Shanghai 200230, China ^[1] Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders(Ministry of Education), Shanghai Jiao Tong University,Shanghai 200230, China; Institute of Social Cognitive and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai 200240, China ^[2] Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders(Ministry of Education), Shanghai Jiao Tong University,Shanghai 200230, China; Institute of Social Cognitive and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai 200240, China;Shanghai Changning Mental Health Center, Shanghai 200042, China ^[3]

关键词 Population stratification Principal component analysis Graphic processing unit Cluster Matched cases and controls Genetic studies

栏目名称

Method

发布时间 2015-10-08（万方平台首次上网日期，不代表论文的发表时间）

基金项目

:This work was supported by the National Key Basic Research Program of China (973 Program) :No.2015CB559100 :the National High Technology Research and Development Program of China (863 Program) :Nos.2012AA02A515 and 2012AA021802 the Natural Science Foundation of China （(Nos.31325014.81130022.81272302 and 81421061)） the National Program for Support of Top-Notch Young Professionals,the Program of Shanghai Subject Chief Scientist （(No.15XD1502200)） "Shu Guang" project supported by Shanghai Municipal Education Commission and Shanghai Education Development Foundation （(No.12SG17)）