newBlockInformation

BlockInformation

This function creates a list storing information about dividing data into blocks, as well as about possibly
excluding genes or samples with excessive numbers of missing data.

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

newBlockInformation function

<dl> <dt>blocks</dt>
<dd>A vector giving block labels. It is assumed to be a numeric vector with block labels consecutive integers
starting at 1.</dd> <dt>goodSamplesAndGenes</dt>
<dd>A list returned by <code>goodSamplesGenes</code> or <code>goodSamplesGenesMS</code>.</dd></dl>

Arguments

Author

Create a list holding information about dividing data into blocks — newBlockInformation

<dl>

 <dt>blocks</dt>
<dd>A vector giving block labels. It is assumed to be a numeric vector with block labels consecutive integers
starting at 1.</dd>

 <dt>goodSamplesAndGenes</dt>
<dd>A list returned by <code>goodSamplesGenes</code> or <code>goodSamplesGenesMS</code>.</dd>

</dl>

Create a list holding information about dividing data into blocks

newBlockInformation: Create a list holding information about dividing data into blocks

Description

Usage

Value

Arguments

Author

See Also