multi_kmeans_gen

Clustering, or cluster analysis, is a widely used technique in bioinformatics to identify groups of similar biological data points. Consensus clustering is an extension to clustering algorithms that aims to construct a robust result from those clustering features that are invariant under different sources of variation. For the reference, please cite the following paper: Yousefi, Melograna, et. al., (2023) <doi:10.3389/fmicb.2023.1170391>.

Behnam Yousefi

ConsensusClustering

Consensus Clustering

multi_kmeans_gen function

<dl><dt>X</dt>
<dd>input data Nsample x Nfeatures</dd>
<dt>rep</dt>
<dd>number of repeats</dd>
<dt>range.k</dt>
<dd>vector of minimum and maximum values for k <code>c(min, max)</code></dd>
<dt>method</dt>
<dd>method for the choice of k at each repeat <code>c("random", "silhouette")</code></dd></dl>

Arguments

Multiple K-means generation — multi_kmeans_gen

<dl>

<dt>X</dt>
<dd>input data Nsample x Nfeatures</dd>


<dt>rep</dt>
<dd>number of repeats</dd>


<dt>range.k</dt>
<dd>vector of minimum and maximum values for k <code>c(min, max)</code></dd>


<dt>method</dt>
<dd>method for the choice of k at each repeat <code>c("random", "silhouette")</code></dd>

</dl>

multi_kmeans_gen: Multiple K-means generation

Description

Usage

Value

Arguments

Details

Examples