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assignPOP: Population Assignment using Genetic, Non-Genetic or Integrated Data in a Machine Learning Framework

Use Monte-Carlo and K-fold cross-validation coupled with machine- learning classification algorithms to perform population assignment, with functionalities of evaluating discriminatory power of independent training samples, identifying informative loci, reducing data dimensionality for genomic data, integrating genetic and non-genetic data, and visualizing results.

Version: 1.3.0
Depends: R (≥ 2.3.2)
Imports: caret, doParallel, e1071, foreach, ggplot2, MASS, parallel, randomForest, reshape2, stringr, tree, rlang
Suggests: gtable, iterators, klaR, stringi, knitr, rmarkdown, testthat
Published: 2024-03-13
DOI: 10.32614/CRAN.package.assignPOP
Author: Kuan-Yu (Alex) Chen [aut, cre], Elizabeth A. Marschall [aut], Michael G. Sovic [aut], Anthony C. Fries [aut], H. Lisle Gibbs [aut], Stuart A. Ludsin [aut]
Maintainer: Kuan-Yu (Alex) Chen <alexkychen at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/alexkychen/assignPOP
NeedsCompilation: no
CRAN checks: assignPOP results

Documentation:

Reference manual: assignPOP.pdf

Downloads:

Package source: assignPOP_1.3.0.tar.gz
Windows binaries: r-devel: assignPOP_1.3.0.zip, r-release: assignPOP_1.3.0.zip, r-oldrel: assignPOP_1.3.0.zip
macOS binaries: r-release (arm64): assignPOP_1.3.0.tgz, r-oldrel (arm64): assignPOP_1.3.0.tgz, r-release (x86_64): assignPOP_1.3.0.tgz, r-oldrel (x86_64): assignPOP_1.3.0.tgz
Old sources: assignPOP archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=assignPOP to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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