uncent.cordist

Calculating all pairwise distances using correlation distance

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

uncent.cordist function

<dl><dt>data</dt>
<dd>a data matrix ([data.frame object] row: metabolites,
col: samples or replicates)</dd>
<dt>absolute</dt>
<dd>TRUE means that absolute value of the correlation coefficient is used (Default: FALSE).</dd></dl>

Arguments

Author

Calculating all pairwise distances using correlation distance — uncent.cordist

<dl>

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


<dt>absolute</dt>
<dd>TRUE means that absolute value of the correlation coefficient is used (Default: FALSE).</dd>

</dl>

uncent.cordist: Calculating all pairwise distances using correlation distance

Description

Usage

Value

Arguments

Author

Details

Examples