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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 |
Reference manual: | assignPOP.pdf |
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 |
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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.