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 |