BGLRR - Bayesian Generalized Linear Regression in R. V 2.1

Version 5.0

Francisco Rodríguez; Paulino Pérez; Gustavo de los Campos; Gregorio Alvarado; Ángela Pacheco; José Crossa; Juan Burgueño, 2017, "BGLRR - Bayesian Generalized Linear Regression in R. V 2.1", https://hdl.handle.net/11529/10848, CIMMYT Research Data & Software Repository Network, V5

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Description	BGLR is a software to simplify the selection of input files and parameters to perform Bayesian Generalized Linear Regression using R (statistacal software). BGLR provides predictions, GWAS analysis and analysis of reaction norm model described in reference [1]. It allows the inclusion of markers information, relationship matrix (pedigree), environmental covariables, and other variables as fixed or random effects. (2017-01-07)
Subject	Agricultural Sciences
Keyword	BGLR, Bayesian regression, genome selection, predictive model

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	README_BGLR-R.txt Plain Text - 3.7 KB - Jul 11, 2018 - 270 Downloads MD5: 3e8e22f64b1e4600fe17e1b6694c223a	Download
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Citation Metadata

Dataset Persistent ID	hdl:11529/10848
Publication Date	2017-01-07
Title	BGLRR - Bayesian Generalized Linear Regression in R. V 2.1
Other ID	BGLR
Author	Francisco Rodríguez (Biometrics and Statistics Unit, CIMMYT) Paulino Pérez (Biometrics and Statistics Unit, CIMMYT - Colegio de Postgraduados) Gustavo de los Campos (Biometrics and Statistics Unit, CIMMYT - Michigan State University) Gregorio Alvarado (Biometrics and Statistics Unit, CIMMYT) Ángela Pacheco (Biometrics and Statistics Unit, CIMMYTBiometrics and Statistics Unit, CIMMYT) José Crossa (Biometrics and Statistics Unit, CIMMYT) Juan Burgueño (Biometrics and Statistics Unit, CIMMYT)
Contact	Use email button above to contact. Juan Burgueño (BSU - CIMMYT)
Description	BGLR is a software to simplify the selection of input files and parameters to perform Bayesian Generalized Linear Regression using R (statistacal software). BGLR provides predictions, GWAS analysis and analysis of reaction norm model described in reference [1]. It allows the inclusion of markers information, relationship matrix (pedigree), environmental covariables, and other variables as fixed or random effects. (2017-01-07)
Subject	Agricultural Sciences
Keyword	BGLR Bayesian regression genome selection predictive model
Language	English
Producer	International Maize and Wheat Improvement Center (CIMMYT) http://www.cimmyt.org/
Production Date	2017-01-07
Distributor	International Maize and Wheat Improvement Center (CIMMYT) http://www.cimmyt.org/
Distribution Date	2017-01-07
Deposit Date	2017-01-07

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This program is based in some components from Java, developed by ORACLE AMERICA, INC. and R, developed by Kurt Hornik. Any Java component of this program is hereby licensed under the Oracle Binary Code License Agreement for the Java SE Platform Products and JavaFX made available by Oracle (available at http://www.oracle.com/technetwork/java/javase/terms/license/index.html). Any R component of this progra m as well as the program as a whole developed by CIMMYT are hereby licensed as per the terms of the GNU General Public License version 3(available at http://www.gnu.org/licenses/gpl-3.0.html), as specified below.

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.

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