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).

AuthorAkio Onogi and Hiroyoshi Iwata
Date of publication2015-05-20 15:38:58
MaintainerAkio Onogi <onogiakio@gmail.com>
LicenseMIT + file LICENSE
Version1.0

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Files

VIGoR
VIGoR/src
VIGoR/src/vigorr.h
VIGoR/src/vigorr.c
VIGoR/src/MT.h
VIGoR/NAMESPACE
VIGoR/data
VIGoR/data/sampledata.RData
VIGoR/R
VIGoR/R/vigor.R VIGoR/R/hyperpara.R
VIGoR/MD5
VIGoR/DESCRIPTION
VIGoR/man
VIGoR/man/Covariates.Rd VIGoR/man/hyperpara.Rd VIGoR/man/Geno.Rd VIGoR/man/Pheno.Rd VIGoR/man/vigor.Rd
VIGoR/LICENSE

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