regressionplot {globaltest} | R Documentation |

## Regression Plot for Global Test

### Description

Produces a plot which can be used to visualize the
effect of specific samples on the test result produced by
`globaltest`

.

### Usage

regressionplot(gt, geneset, sampleid, ...)

### Arguments

`gt` |
The output of a call to `globaltest` . |

`geneset` |
The name or number of the geneset to be plotted
(only necessary if multiple genesets were tested). |

`sampleid` |
An optional vector of names or numbers of the samples of interest. |

`...` |
Any extra arguments will be forwarded to the plotting function. |

### Details

The regressionplot plots, for all pairs of samples, the
covariance between the expression patterns against the covariance
between their clinical outcomes. Each point in the plot therefore
represents a pair of samples. A regression line is fitted through
the samples, which visualizes the test result of the function
`globaltest`

. A steeply increasing slope indicates a
high (possibly significant) value of the test statistic.

An optional argument `sampleid`

can be supplied, giving
sample numbers of possibly outlying arrays. In this case, all
pairs of arrays involving one of the arrays in `sampleid`

is
marked as a red cross, while the other pairs are marked as a blue
dot. The blue line which is fitted through all points can now be
compared to a red dotted line which is fitted though only the red
crosses.

### Value

`NULL`

(no output).

### Note

Regressionplot does not work if the adjusted version of
globaltest was used.

### Author(s)

Jelle Goeman: j.j.goeman@lumc.nl; Jan Oosting

### References

J. J. Goeman, S. A. van de Geer, F. de Kort and J. C.
van Houwelingen, 2004, *A global test for groups of genes:
testing association with a clinical outcome*,
*Bioinformatics* 20 (1) 93–99. See also the How To
Globaltest.pdf included with this package.

### See Also

`globaltest`

, `sampleplot`

,
`geneplot`

.

### Examples

if (interactive()) {
data(exampleX) # Expression data (40 samples; 1000 genes)
data(exampleY) # Clinical outcome for the 40 samples
pathway <- 1:25 # A pathway contains genes 1 to 25
gt <- globaltest(exampleX, exampleY, test.genes = pathway)
gt
regressionplot(gt)
regressionplot(gt, sampleid = 40)
}

[Package

*globaltest* version 3.2.0

Index]