BGGE (0.6.5)

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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 Jarqun et al. (2014) and Lopez-Cruz et al. (2015) . 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) .

Maintainer: Italo Granato
Author(s): Italo Granato [aut, cre], Luna-Vzquez Francisco J. [aut], Cuevas Jaime [aut]

License: GPL-3

Uses: coda, BGLR

Released over 1 year ago.

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