<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Identification of Parental Lines via Genomic Prediction</dc:title>
  <dc:title>R package IPLGP version 2.0.5</dc:title>
  <dc:description>
    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) &lt;doi:10.1371/journal.pone.0243159&gt;. 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.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Imports: ggplot2, sommer, grDevices, stats</dc:relation>
  <dc:creator>Ping-Yuan Chung &lt;r06621204@ntu.edu.tw&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Ping-Yuan Chung [cre],
  Chen-Tuo Liao [aut]</dc:contributor>
  <dc:rights>GPL-2</dc:rights>
  <dc:date>2024-08-01</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=IPLGP</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.IPLGP</dc:identifier>
</oai_dc:dc>
