adj_mat

Covert data matrix to adjacency matrix

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

adj_mat function

<dl><dt>X</dt>
<dd>a matrix of samples by features.</dd>
<dt>method</dt>
<dd>method for distance calculation:
<code>"euclidian"</code>, <code>"cosine"</code>, <code>"maximum"</code>, <code>"manhattan"</code>,
<code>"canberra"</code>, <code>"binary"</code>, <code>"minkowski"</code>,</dd></dl>

Arguments

Covert data matrix to adjacency matrix — adj_mat

<dl>

<dt>X</dt>
<dd>a matrix of samples by features.</dd>


<dt>method</dt>
<dd>method for distance calculation:
<code>"euclidian"</code>, <code>"cosine"</code>, <code>"maximum"</code>, <code>"manhattan"</code>,
<code>"canberra"</code>, <code>"binary"</code>, <code>"minkowski"</code>,</dd>

</dl>

adj_mat: Covert data matrix to adjacency matrix

Description

Usage

Value

Arguments

Examples