golubInfo

Details are given of the classifying factors for the 72
 columns of the Golub data set.

datasets

Cross-validated linear discriminant calculations determine
the optimum number of features. Test and training scores from
successive cross-validation steps determine, via a principal
components calculation, a low-dimensional global space onto which test
scores are projected, in order to plot them. Further functions are
included that are intended for didactic use. The package implements,
and extends, methods described in J.H. Maindonald and C.J. Burden (2005)
<https://journal.austms.org.au/V46/CTAC2004/Main/home.html>.

John Maindonald

hddplot

Use Known Groups in High-Dimensional Data to Derive Scores for
Plots

golubInfo function

A data frame with 72 observations on the following 6 variables,
that identifies the samples (observations) in the data set <code>Golub</code><dl>
 <dt><code>Samples</code></dt>
<dd>a numeric vector: sample number</dd> <dt><code>BM.PB</code></dt>
<dd>a factor with levels <code>BM</code> (from bone marrow) 
<code>PB</code> (from peripheral blood)</dd> <dt><code>Gender</code></dt>
<dd>a factor with levels <code>F</code> <code>M</code></dd> <dt><code>Source</code></dt>
<dd>a factor with levels <code>CALGB</code> <code>CCG</code> <code>DFCI</code> <code>St-Jude</code>. These are the hospitals from which the sample came</dd> <dt><code>tissue.mf</code></dt>
<dd>a factor with levels <code>BM:NA</code> <code>BM:f</code> <code>BM:m</code> <code>PB:NA</code> <code>PB:f</code> <code>PB:m</code>. This factor identifies the
several combinations of <code>source</code> and <code>Gender</code></dd> <dt><code>cancer</code></dt>
<dd>a factor with levels <code>allB</code> <code>allT</code> <code>aml</code>
There are two types of Acute Lymphoblastic Leukemia (<code>allB</code> and 
<code>allT</code>), plus Acute Myoblastic Leukemia (<code>aml</code>)</dd> 
</dl>

Format

Classifying factors for the 72 columns of the Golub data set — golubInfo

A data frame with 72 observations on the following 6 variables,
that identifies the samples (observations) in the data set <code>Golub</code><dl>
 <dt><code>Samples</code></dt>
<dd>a numeric vector: sample number</dd>

 <dt><code>BM.PB</code></dt>
<dd>a factor with levels <code>BM</code> (from bone marrow) 
<code>PB</code> (from peripheral blood)</dd>

 <dt><code>Gender</code></dt>
<dd>a factor with levels <code>F</code> <code>M</code></dd>

 <dt><code>Source</code></dt>
<dd>a factor with levels <code>CALGB</code> <code>CCG</code> <code>DFCI</code> <code>St-Jude</code>. These are the hospitals from which the sample came</dd>

 <dt><code>tissue.mf</code></dt>
<dd>a factor with levels <code>BM:NA</code> <code>BM:f</code> <code>BM:m</code> <code>PB:NA</code> <code>PB:f</code> <code>PB:m</code>. This factor identifies the
several combinations of <code>source</code> and <code>Gender</code></dd>

 <dt><code>cancer</code></dt>
<dd>a factor with levels <code>allB</code> <code>allT</code> <code>aml</code>
There are two types of Acute Lymphoblastic Leukemia (<code>allB</code> and 
<code>allT</code>), plus Acute Myoblastic Leukemia (<code>aml</code>)</dd>

 
</dl>

golubInfo: Classifying factors for the 72 columns of the Golub data set

Description

Usage

Arguments

Format

References

Examples