get_tree_edges

Extract the edges from a set of clusterings

internal

Deciding what resolution to use can be a difficult question when
approaching a clustering analysis. One way to approach this problem is to
look at how samples move as the number of clusters increases. This package
allows you to produce clustering trees, a visualisation for interrogating
clusterings as resolution increases.

Luke Zappia

clustree

Visualise Clusterings at Different Resolutions

Alicia Oshlack

Andrea Rau

Paul Hoffman

get_tree_edges function

<dl><dt>clusterings</dt>
<dd>numeric matrix containing clustering information, each
column contains clustering at a separate resolution</dd>
<dt>prefix</dt>
<dd>string indicating columns containing clustering information</dd></dl>

Arguments

Get tree edges — get_tree_edges

<dl>

<dt>clusterings</dt>
<dd>numeric matrix containing clustering information, each
column contains clustering at a separate resolution</dd>


<dt>prefix</dt>
<dd>string indicating columns containing clustering information</dd>

</dl>

get_tree_edges: Get tree edges

Description

Usage

Value

Arguments