reduce.allele

This function helps remove alleles that have low variance in the data set such that it can speed up further analyses for a large data set (e.g., &gt; 10K SNPs).

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.

Kuan-Yu Chen

assignPOP

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

reduce.allele function

<dl><dt>x</dt>
<dd>A returned object (a list) from the function read.genpop().</dd>
<dt>p</dt>
<dd>A threshold of variance for the alleles to be removed. For example, if p = 0.95 (default setting), an allele occupied more than 95 percents across all the samples will be removed.</dd></dl>

Arguments

Remove low variance alleles (dimensionality reduction) — reduce.allele

<dl>

<dt>x</dt>
<dd>A returned object (a list) from the function read.genpop().</dd>


<dt>p</dt>
<dd>A threshold of variance for the alleles to be removed. For example, if p = 0.95 (default setting), an allele occupied more than 95 percents across all the samples will be removed.</dd>

</dl>

reduce.allele: Remove low variance alleles (dimensionality reduction)

Description

Usage

Value

Arguments