VIGoR: 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).

Getting started

Package details

AuthorAkio Onogi and Hiroyoshi Iwata
MaintainerAkio Onogi <>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
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VIGoR documentation built on May 2, 2019, 2:37 a.m.