hubGeneSignificance

Calculate approximate hub gene significance for all modules in network.

 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

hubGeneSignificance function

<dl> <dt>datKME</dt>
<dd>a data frame (or a matrix-like object) containing eigengene-based connectivities of all
genes in the network.</dd> <dt>GS</dt>
<dd>a vector with one entry for every gene containing its gene significance.</dd></dl>

Arguments

Author

Hubgene significance — hubGeneSignificance

<dl>

 <dt>datKME</dt>
<dd>a data frame (or a matrix-like object) containing eigengene-based connectivities of all
genes in the network.</dd>

 <dt>GS</dt>
<dd>a vector with one entry for every gene containing its gene significance.</dd>

</dl>

Hubgene significance

hubGeneSignificance: Hubgene significance

Description

Usage

Value

Arguments

Author

Details

References