get.eigen.molecule

A method for identifying pattern changes between 2
experimental conditions in correlation networks (e.g., gene
co-expression networks), which builds on a commonly used association
measure, such as Pearson's correlation coefficient. This package
includes functions to calculate correlation matrices for
high-dimensional dataset and to test differential correlation, which
means the changes in the correlation relationship among variables
(e.g., genes and metabolites) between 2 experimental conditions.

Atsushi Fukushima

DiffCorr

Analyzing and Visualizing Differential Correlation Networks in
Biological Data

Kozo Nishida

get.eigen.molecule function

<dl><dt>data</dt>
<dd>a data matrix ([data.frame object] row: molecules,
col: samples or replicates)</dd>
<dt>groups</dt>
<dd>a vector of group memberships as returned by cutree</dd>
<dt>whichgroups</dt>
<dd>a vector of group numbers to examine</dd>
<dt>methods</dt>
<dd>c("svd", "nipals", "rnipals", "bpca", "ppca"). See also pca() function in pcaMethods package</dd>
<dt>n</dt>
<dd>top n principal components</dd></dl>

Arguments

Author

Get eigen molecule — get.eigen.molecule

<dl>

<dt>data</dt>
<dd>a data matrix ([data.frame object] row: molecules,
col: samples or replicates)</dd>


<dt>groups</dt>
<dd>a vector of group memberships as returned by cutree</dd>


<dt>whichgroups</dt>
<dd>a vector of group numbers to examine</dd>


<dt>methods</dt>
<dd>c("svd", "nipals", "rnipals", "bpca", "ppca"). See also pca() function in pcaMethods package</dd>


<dt>n</dt>
<dd>top n principal components</dd>

</dl>

get.eigen.molecule: Get eigen molecule

Description

Usage

Value

Arguments

Author

Examples