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DOI10.1038/s41467-017-02773-w
Non-parametric genetic prediction of complex traits with latent Dirichlet process regression models
Zeng, Ping1,2; Zhou, Xiang2,3
2017-09-06
发表期刊NATURE COMMUNICATIONS
ISSN2041-1723
出版年2017
卷号8
文章类型Article
语种英语
国家Peoples R China; USA
英文摘要

Using genotype data to perform accurate genetic prediction of complex traits can facilitate genomic selection in animal and plant breeding programs, and can aid in the development of personalized medicine in humans. Because most complex traits have a polygenic architecture, accurate genetic prediction often requires modeling all genetic variants together via polygenic methods. Here, we develop such a polygenic method, which we refer to as the latent Dirichlet process regression model. Dirichlet process regression is non-parametric in nature, relies on the Dirichlet process to flexibly and adaptively model the effect size distribution, and thus enjoys robust prediction performance across a broad spectrum of genetic architectures. We compare Dirichlet process regression with several commonly used prediction methods with simulations. We further apply Dirichlet process regression to predict gene expressions, to conduct PrediXcan based gene set test, to perform genomic selection of four traits in two species, and to predict eight complex traits in a human cohort.


领域资源环境
收录类别SCI-E
WOS记录号WOS:000409458000010
WOS关键词GENOME-WIDE ASSOCIATION ; BAYESIAN VARIABLE SELECTION ; RISK PREDICTION ; VARIATIONAL INFERENCE ; DAIRY-CATTLE ; HUMAN HEIGHT ; ACCURACY ; LOCI ; HERITABILITY ; ARCHITECTURE
WOS类目Multidisciplinary Sciences
WOS研究方向Science & Technology - Other Topics
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文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/203646
专题资源环境科学
作者单位1.Xuzhou Med Univ, Dept Epidemiol & Biostat, Xuzhou 221004, Jiangsu, Peoples R China;
2.Univ Michigan, Dept Biostat, Ann Arbor, MI 48109 USA;
3.Univ Michigan, Ctr Stat Genet, Ann Arbor, MI 48109 USA
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Zeng, Ping,Zhou, Xiang. Non-parametric genetic prediction of complex traits with latent Dirichlet process regression models[J]. NATURE COMMUNICATIONS,2017,8.
APA Zeng, Ping,&Zhou, Xiang.(2017).Non-parametric genetic prediction of complex traits with latent Dirichlet process regression models.NATURE COMMUNICATIONS,8.
MLA Zeng, Ping,et al."Non-parametric genetic prediction of complex traits with latent Dirichlet process regression models".NATURE COMMUNICATIONS 8(2017).
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