首页 | 本学科首页   官方微博 | 高级检索  
   检索      


Efficient mixed model approach for large-scale genome-wide association studies of ordinal categorical phenotypes
Authors:Wenjian Bi  Wei Zhou  Rounak Dey  Bhramar Mukherjee  Joshua N Sampson  Seunggeun Lee
Institution:1. Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA;2. Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA;3. Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA;4. Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA;5. Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA;6. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA;7. Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD 20892, USA;8. Graduate School of Data Science, Seoul National University, Seoul 08826, Republic of Korea
Abstract:
Keywords:genome-wide association studies  GWAS  phenome-wide association studies  PheWAS  ordinal categorical data  mixed model approach  proportional odds logistic mixed model  POLMM  UK Biobank  saddlepoint approximation  unbalanced phenotypic distribution  food and other preferences  genetic relationship matrix  GRM
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号