IPLGP: Identification of Parental Lines via Genomic Prediction

Combining genomic prediction with Monte Carlo simulation, three different strategies are implemented to select parental lines for multiple traits in plant breeding. The selection strategies include (i) GEBV-O considers only genomic estimated breeding values (GEBVs) of the candidate individuals; (ii) GD-O considers only genomic diversity (GD) of the candidate individuals; and (iii) GEBV-GD considers both GEBV and GD. The above method can be seen in Chung PY, Liao CT (2020) <doi:10.1371/journal.pone.0243159>. Multi-trait genomic best linear unbiased prediction (MT-GBLUP) model is used to simultaneously estimate GEBVs of the target traits, and then a selection index is adopted to evaluate the composite performance of an individual.

Version:	2.0.5
Imports:	ggplot2, sommer, grDevices, stats
Published:	2024-08-01
DOI:	10.32614/CRAN.package.IPLGP
Author:	Ping-Yuan Chung [cre], Chen-Tuo Liao [aut]
Maintainer:	Ping-Yuan Chung <r06621204 at ntu.edu.tw>
BugReports:	https://github.com/py-chung/IPLGP/issues
License:	GPL-2
URL:	https://github.com/py-chung/IPLGP
NeedsCompilation:	no
CRAN checks:	IPLGP results

Documentation:

Reference manual:

IPLGP.pdf

Downloads:

Package source:	IPLGP_2.0.5.tar.gz
Windows binaries:	r-devel: IPLGP_2.0.5.zip, r-release: IPLGP_2.0.5.zip, r-oldrel: IPLGP_2.0.5.zip
macOS binaries:	r-release (arm64): IPLGP_2.0.5.tgz, r-oldrel (arm64): IPLGP_2.0.5.tgz, r-release (x86_64): IPLGP_2.0.5.tgz, r-oldrel (x86_64): IPLGP_2.0.5.tgz
Old sources:	IPLGP archive

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