ME_inf

put sample names as rownames in WGCNA module eigenvalue data.frame.

Functions designed to connect disease-related differential proteins and
co-expression network. It provides the basic statics analysis included t test, ANOVA analysis.
The network construction is not offered by the package, you can used 'WGCNA' package which you
can learn in Peter et al. (2008) <doi:10.1186/1471-2105-9-559>. It also provides module analysis
included PCA analysis, two enrichment analysis, Planner maximally filtered graph extraction and
hub analysis.

Kefu Liu

DDPNA

Disease-Drived Differential Proteins Co-Expression Network
Analysis

ME_inf function

<dl> <dt>MEs</dt>
<dd>module eigenvalue which is calculated in WGCNA package.</dd> <dt>data</dt>
<dd>protein quantification data. column is sample. row is protein ID.</dd> <dt>intensity.type</dt>
<dd>quantification data type, which can help extract sample name.
 This must be (an abbreviation of) one of the strings "<code>LFQ</code>","<code>intensity</code>","<code>iBAQ</code>","<code>none</code>".</dd> <dt>rowname</dt>
<dd>sample names when "<code>intensity.type</code>" is "<code>none</code>", rowname will be used.</dd></dl>

Arguments

Author

module eigengenes information — ME_inf

<dl>

 <dt>MEs</dt>
<dd>module eigenvalue which is calculated in WGCNA package.</dd>

 <dt>data</dt>
<dd>protein quantification data. column is sample. row is protein ID.</dd>

 <dt>intensity.type</dt>
<dd>quantification data type, which can help extract sample name.
 This must be (an abbreviation of) one of the strings "<code>LFQ</code>","<code>intensity</code>","<code>iBAQ</code>","<code>none</code>".</dd>

 <dt>rowname</dt>
<dd>sample names when "<code>intensity.type</code>" is "<code>none</code>", rowname will be used.</dd>

</dl>

ME_inf: module eigengenes information

Description

Usage

Arguments

Author

Examples