Variational Bayesian Inference for Genome-Wide Regression

Conducts linear regression using variational Bayesian inference, particularly optimized for genome-wide association mapping and whole-genome prediction which use a number of DNA markers as the explanatory variables. Provides seven regression models which select the important variables (i.e., the variables related to response variables) among the given explanatory variables in different ways (i.e., model structures).


Reference manual

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1.0 by Akio Onogi, 4 years ago

Browse source code at

Authors: Akio Onogi and Hiroyoshi Iwata

Documentation:   PDF Manual  

MIT + file LICENSE license

See at CRAN