Learn R Programming

assignPOP (version 1.3.0)

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

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.

Copy Link

Version

Install

install.packages('assignPOP')

Monthly Downloads

609

Version

1.3.0

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Maintainer

Kuan-Yu Chen

Last Published

March 13th, 2024

Functions in assignPOP (1.3.0)

check.loci

Check which loci frequently have high Fst across training sets
membership.plot

Make a membership probability plot using results from K-fold cross-validation (ggplot2 style)
assign.kfold

Population assignment test using K-fold cross-validation
assign.matrix

Make an assignment maxtrix from cross-validation results
accuracy.kfold

Estimate assignment accuracies of K-fold cross-validation results
compile.data

Compile genetic and other non-genetic data
assign.MC

Population assignment test using Monte-Carlo cross-validation
accuracy.MC

Estimate assignment accuracies of Monte-Carlo cross-validation results
accuracy.plot

Make a boxplot (ggplot2 style) of assignment accuracy from cross-validation results
assign.X

Perform a population assignment test on unknown individuals using known data
reduce.allele

Remove low variance alleles (dimensionality reduction)
read.Genepop

Read GENEPOP format file
read.Structure

Read Structure format file