cutreeStaticColor

Cluster detection by a constant height cut of a hierarchical clustering dendrogram.

misc

Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data as originally described in Horvath and Zhang (2005) <doi:10.2202/1544-6115.1128> and Langfelder and Horvath (2008) <doi:10.1186/1471-2105-9-559>. Includes functions for rudimentary data cleaning, construction of correlation networks, module identification, summarization, and relating of variables and modules to sample traits. Also includes a number of utility functions for data manipulation and visualization.

Peter Langfelder

WGCNA

Weighted Correlation Network Analysis

Steve Horvath

Chaochao Cai

Jun Dong

Jeremy Miller

Lin Song

Andy Yip

Bin Zhang

cutreeStaticColor function

<dl> <dt>dendro</dt>
<dd>a hierarchical clustering dendrogram such as returned by <code><a href="/link/hclust?package=WGCNA&version=1.73" data-mini-rdoc="WGCNA::hclust">hclust</a></code>.</dd> <dt>cutHeight</dt>
<dd>height at which branches are to be cut.</dd> <dt>minSize</dt>
<dd>minimum number of object on a branch to be considered a cluster.</dd></dl>

Arguments

Author

Constant height tree cut using color labels — cutreeStaticColor

<dl>

 <dt>dendro</dt>
<dd>a hierarchical clustering dendrogram such as returned by <code><a href='https://rdrr.io/r/stats/hclust.html'>hclust</a></code>.</dd>

 <dt>cutHeight</dt>
<dd>height at which branches are to be cut.</dd>

 <dt>minSize</dt>
<dd>minimum number of object on a branch to be considered a cluster.</dd>

</dl>

Constant height tree cut using color labels

cutreeStaticColor: Constant height tree cut using color labels

Description

Usage

Value

Arguments

Author

Details

See Also