ldaPlot

The function takes as input the traits and group IDs and will perform a discriminate function analysis and visualize the results. For the pair-wise comparison of groups we use density histograms with points along the x-axis denoting the actual data, Figure 3 For multi-group comparisons we plot a bivariate scatter for all pairwise combinations of discriminate axes. The color of plotting symbols can be altered using the palette argument and the axes comparisons (with max n = number of groups - 1).

Code to support a systems biology research program from inception through publication.  The methods focus on dimension reduction approaches to detect patterns in complex, multivariate experimental data and places an emphasis on informative visualizations.  The goal for this project is to create a package that will evolve over time, thereby remaining relevant and reflective of current methods and techniques.  As a result, we encourage suggested additions to the package, both methodological and graphical.

Samuel V Scarpino

multiDimBio

Multivariate Analysis and Visualization for Biological Data

ldaPlot function

<dl> <dt>Data</dt>
<dd>A (non-empty), numeric matrix of data values</dd> <dt>Groups</dt>
<dd>A (non-empty), vector indicating group membership. Length(unique(Group))==2</dd> 	<dt>palette</dt>
<dd>A color palette for plotting. The default is 'Paired.' See colorbrewer2.org for alternatives.</dd> <dt>axes</dt>
<dd>A numeric vector describing which axes to compare. For example, axes=c(1,2) will on produce a single plot comparing the first and second axis.</dd></dl>

Arguments

A function to visualize the results of a discriminant analysis — ldaPlot

<dl>

 <dt>Data</dt>
<dd>A (non-empty), numeric matrix of data values</dd>

 <dt>Groups</dt>
<dd>A (non-empty), vector indicating group membership. Length(unique(Group))==2</dd>

 	<dt>palette</dt>
<dd>A color palette for plotting. The default is 'Paired.' See colorbrewer2.org for alternatives.</dd>

 <dt>axes</dt>
<dd>A numeric vector describing which axes to compare. For example, axes=c(1,2) will on produce a single plot comparing the first and second axis.</dd>

</dl>

ldaPlot: A function to visualize the results of a discriminant analysis

Description

Usage

Value

Arguments

See Also

Examples