A Bayesian linear mixed model for prediction of complex traits | Zendy

Yang Hai | Zendy; Yalu Wen | Zendy

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A Bayesian linear mixed model for prediction of complex traits

Author(s) -

Yang Hai,

Yalu Wen

Publication year - 2020

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btaa1023

Subject(s) - bayes' theorem , computer science , bayesian probability , linear model , machine learning , linear regression , artificial intelligence , regression , mixed model , naive bayes classifier , data mining , statistics , mathematics , support vector machine

Accurate disease risk prediction is essential for precision medicine. Existing models either assume that diseases are caused by groups of predictors with small-to-moderate effects or a few isolated predictors with large effects. Their performance can be sensitive to the underlying disease mechanisms, which are usually unknown in advance.

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