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.

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Package
assignPOP
Type
Package
Title
Population Assignment using Genetic, Non-Genetic or Integrated Data in a Machine Learning Framework
Version
1.1.4
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
Description
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.
URL
Depends
R (>= 2.3.2)
Imports
caret, doParallel, e1071, foreach, ggplot2, MASS, parallel, randomForest, reshape2, stringr, tree,
Suggests
gtable, iterators, klaR, stringi, knitr, rmarkdown, testthat
License
GPL (>= 2)
RoxygenNote
5.0.1
NeedsCompilation
no
Packaged
2018-03-13 00:15:14 UTC; Alex
Repository
CRAN
Date/Publication
2018-03-13 04:22:15 UTC

install.packages('assignPOP')

1.1.4

6 months ago

https://github.com/alexkychen/assignPOP

Kuan-Yu (Alex) Chen

GPL (>= 2)

Depends on

R (>= 2.3.2)

Imports

caret, doParallel, e1071, foreach, ggplot2, MASS, parallel, randomForest, reshape2, stringr, tree,

Suggests

gtable, iterators, klaR, stringi, knitr, rmarkdown, testthat

Discussions