BGGE: Bayesian Genomic Linear Models Applied to GE Genome Selection
Application of genome prediction for a continuous variable, focused
on genotype by environment (GE) genomic selection models (GS). It consists a group of functions
that help to create regression kernels for some GE genomic models proposed by Jarquín et al. (2014) <doi:10.1007/s00122-013-2243-1>
and Lopez-Cruz et al. (2015) <doi:10.1534/g3.114.016097>. Also, it computes genomic predictions based on Bayesian approaches.
The prediction function uses an orthogonal transformation of the data and specific priors
present by Cuevas et al. (2014) <doi:10.1534/g3.114.013094>.
| Version: |
0.6.5 |
| Depends: |
R (≥ 3.1.1) |
| Imports: |
stats |
| Suggests: |
BGLR, coda |
| Published: |
2018-08-10 |
| Author: |
Italo Granato [aut, cre],
Luna-Vázquez Francisco J. [aut],
Cuevas Jaime [aut] |
| Maintainer: |
Italo Granato <italo.granato at gmail.com> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| Materials: |
NEWS |
| CRAN checks: |
BGGE results |
Documentation:
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