Joint modeling of genetically correlated diseases and functional annotations increases accuracy of polygenic risk prediction-Reference-Cited by-同舟云学术

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

Published:2017-06-09 Issue:6 Volume:13 Page:e1006836
ISSN:1553-7404
Container-title:PLOS Genetics
language:en
Short-container-title:PLoS Genet

Author:

Hu Yiming^ORCID,Lu Qiongshi^ORCID,Liu Wei,Zhang Yuhua,Li Mo,Zhao Hongyu

Funder

National Institutes of Health

VA Cooperative Studies Program of the Department of Veterans Affairs, Office of Research and Development

Yale World Scholars Program

Publisher

Public Library of Science (PLoS)

Subject

Cancer Research,Genetics (clinical),Genetics,Molecular Biology,Ecology, Evolution, Behavior and Systematics

Reference36 articles.

1. Developing and evaluating polygenic risk prediction models for stratified disease prevention;N Chatterjee;Nat Rev Genet,2016

2. Improving genetic risk prediction by leveraging pleiotropy;C Li;Human genetics,2014

3. Joint analysis of psychiatric disorders increases accuracy of risk prediction for schizophrenia, bipolar disorder, and major depressive disorder;R Maier;The American Journal of Human Genetics,2015

4. Risk classification with an adaptive naive bayes kernel machine model;J Minnier;Journal of the American Statistical Association,2015

5. MultiBLUP: improved SNP-based prediction for complex traits;D Speed;Genome research,2014

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