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:
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)
IPLGP_2.0.5.tar.gz(r-4.5-noble)IPLGP_2.0.5.tar.gz(r-4.4-noble)
IPLGP_2.0.5.tgz(r-4.4-emscripten)IPLGP_2.0.5.tgz(r-4.3-emscripten)
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')) |
Bug tracker:https://github.com/py-chung/iplgp/issues
Last updated 4 months agofrom:7b3628c1a6. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 03 2024 |
R-4.5-win | OK | Nov 03 2024 |
R-4.5-linux | OK | Nov 03 2024 |
R-4.4-win | OK | Nov 03 2024 |
R-4.4-mac | OK | Nov 03 2024 |
R-4.3-win | OK | Nov 03 2024 |
R-4.3-mac | OK | Nov 03 2024 |
Exports:GA.DscoreGBLUP.fitgeno.doutput.bestoutput.gainphe.sdsimu.gametesimu.GDOsimu.GEBVGDsimu.GEBVO
Dependencies:clicolorspacecrayonfansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadilloRcppProgressrlangscalessommertibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Search For A Subset With The Highest D-score | GA.Dscore |
Muti-trait GBLUP Model | GBLUP.fit |
Generate the Genetic Design Matrix with dominance Effect | geno.d |
Summary For The Best Individuals | output.best |
Summary For Genetic Gain | output.gain |
Standardize Phenotypic Values | phe.sd |
Simulate The Genotype Of A Gamete | simu.gamete |
Simulate Progeny with GD-O Strategy | simu.GDO |
Simulate Progeny with GEBV-GD Strategy | simu.GEBVGD |
Simulate Progeny with GEBV-O Strategy | simu.GEBVO |