Joint modeling of genetically correlated diseases and functional annotations increases accuracy of polygenic risk prediction

• Yiming Hu,

  Affiliation Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America

  http://orcid.org/0000-0002-0988-1030

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• Qiongshi Lu,

  Affiliation Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America

  http://orcid.org/0000-0002-4514-0969

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• Wei Liu,

  Affiliation Peking University, Beijing, China

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• Yuhua Zhang,

  Affiliation Shanghai Jiao Tong University, Shanghai, China

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• Mo Li,

  Affiliation Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America

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• Hongyu Zhao

  * E-mail: hongyu.zhao@yale.edu

  Affiliations Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America, Program of Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America, Department of Genetics, Yale University School of Medicine, New Haven, Connecticut, United States of America, Clinical Epidemiology Research Center (CERC), Veterans Affairs (VA) Cooperative Studies Program, VA Connecticut Healthcare System, West Haven, Connecticut, United States of America

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