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EHPGS is a GS-based approach to identify potential parental lines and superior hybrid combinations from a breeding population composed of hybrids produced by a half diallel mating design.

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spcspin/EHPGS

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EHPGS

EHPGS is a GS-based approach to identify potential parental lines and superior hybrid combinations from a breeding population composed of hybrids produced by a half diallel mating design.

Installation

The EHPGS can be installed from GitHub:

library(devtools)
install_github("spcspin/EHPGS", dependencies = TRUE, force = TRUE)

Main functions

  • kinship: Function for calculate relationship matrix.
  • BGS: Function for Bayesian Gibbs sampling algorithm.
  • EHPGS: Function for evaluation of hybrid performance in plant breeding via genomic selection.

Example dataset

The test dataset provided in this package is the pumpkin dataset which was published by Wu et al. (2019) <doi.org/10.3835/plantgenome2018.10.0082>.

Authors

  • Szu-Ping Chen
    • Author, maintainer
    • E-mail: R09621108@ntu.edu.tw
    • Department of Agronomy, National Taiwan University, Taipei, Taiwan
  • Chih-Wei Tung
  • Pei-Hsien Wang
    • Author
    • E-mail: R09621206@ntu.edu.tw
    • Department of Agronomy, National Taiwan University, Taipei, Taiwan
  • Chen-Tuo Liao
    • Author, thesis advisor
    • E-mail: ctliao@ntu.edu.tw
    • Department of Agronomy, National Taiwan University, Taipei, Taiwan

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EHPGS is a GS-based approach to identify potential parental lines and superior hybrid combinations from a breeding population composed of hybrids produced by a half diallel mating design.

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