Package: IPLGP 2.0.5

Ping-Yuan Chung

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.

Authors:Ping-Yuan Chung [cre], Chen-Tuo Liao [aut]

IPLGP_2.0.5.tar.gz
IPLGP_2.0.5.zip(r-4.5)IPLGP_2.0.5.zip(r-4.4)IPLGP_2.0.5.zip(r-4.3)
IPLGP_2.0.5.tgz(r-4.4-any)IPLGP_2.0.5.tgz(r-4.3-any)
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IPLGP.pdf |IPLGP.html
IPLGP/json (API)

# Install 'IPLGP' in R:
install.packages('IPLGP', repos = c('https://py-chung.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/py-chung/iplgp/issues

On CRAN:

10 exports 1 stars 0.87 score 33 dependencies 578 downloads

Last updated 1 months agofrom:7b3628c1a6. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 04 2024
R-4.5-winOKSep 04 2024
R-4.5-linuxOKSep 04 2024
R-4.4-winOKSep 04 2024
R-4.4-macOKSep 04 2024
R-4.3-winOKSep 04 2024
R-4.3-macOKSep 04 2024

Exports:GA.DscoreGBLUP.fitgeno.doutput.bestoutput.gainphe.sdsimu.gametesimu.GDOsimu.GEBVGDsimu.GEBVO

Dependencies:clicolorspacecrayonfansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadilloRcppProgressrlangscalessommertibbleutf8vctrsviridisLitewithr