Non-parametric genetic prediction of complex traits with latent Dirichlet process regression models

Nature Communications

Volumn 8, Issue 1, 2017, Pages

  Zeng, Ping ^a,b   Zhou, Xiang ^b  

^a XUZHOU MEDICAL UNIVERSITY   (China)

^b UNIVERSITY OF MICHIGAN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GENE; GENETIC ANALYSIS; GENOMICS; GENOTYPE; MEDICINE; PLANT BREEDING; PREDICTION; REGRESSION ANALYSIS; SOFTWARE;

CLINICAL ARTICLE; CONTROLLED STUDY; EFFECT SIZE; HUMAN; PREDICTION; SIMULATION; ALGORITHM; ANIMAL; BAYES THEOREM; BIOLOGICAL MODEL; BIOLOGY; BOVINE; COMPUTER SIMULATION; GENETIC SELECTION; GENETIC VARIATION; GENETICS; GENOMICS; GENOTYPE; MAIZE; MULTIFACTORIAL INHERITANCE; PHENOTYPE; PROCEDURES; REGRESSION ANALYSIS; SOFTWARE; SPECIES DIFFERENCE;

ANIMALIA;

ALGORITHMS; ANIMALS; BAYES THEOREM; CATTLE; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; GENETIC VARIATION; GENOMICS; GENOTYPE; HUMANS; MODELS, GENETIC; MULTIFACTORIAL INHERITANCE; PHENOTYPE; REGRESSION ANALYSIS; SELECTION, GENETIC; SOFTWARE; SPECIES SPECIFICITY; ZEA MAYS;

EID: 85028927957     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/s41467-017-00470-2     Document Type: Article

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