maigesPack (version 1.30.0)

activeMod: Functional classification of gene groups

Description

This function calculate profiles of expression for groups of genes in each sample of the dataset and for each biological condition (group of samples).

Usage

activeMod(data=NULL, gNameID="GeneName", samples=NULL, usePaths=FALSE, sLabelID="Classification", adjP="none", cutExp=1, cutPhiper=0.05)

Arguments

data

object of class maiges to be used to functionally classify gene groups stored in GeneGrps slot.

gNameID

character string specifying identification of gene label to be used.

sLabelID

idem to the previous argument for identification of sample label.

samples

a list with character vectors specifying the groups that must be compared.

usePaths

logical specifying if the pathways given in Paths slot must also be used, defaults to FALSE.

cutExp

real number specifying the cutoff for expression levels (to discretise the expression)

adjP

character string giving the type of p-value adjustment. May be 'Bonferroni', 'Holm', 'Hochberg', 'SidakSS', 'SidakSD', 'BH', 'BY' or 'none'. Defaults to 'none'. See function mt.rawp2adjp in package multtest for more details.

cutPhiper

p-value cutoff to select significant gene groups.

Value

The result of this function is an object of class maigesActMod.

Details

If the argument samples is NULL, all types defined by the sample label given by sLabelID are used. It is possible to use the plot.maigesActMod and image.maigesActMod to display the results of this analysis. This function is based in the method proposed by Segal et al. (2004).

References

Segal, E.; Friedman, N.; Koller, D. and Regev, A. A module map showing conditional activity of expression modules in cancer. Nature Genetics, 36, 1090-1098, 2004. (http://www.nature.com/ng/journal/v36/n10/abs/ng1434.html)

See Also

activeModScoreHTML, maigesActMod, plot.maigesActMod, image.maigesActMod, mt.rawp2adjp

Examples

## Loading a little dataset
data(gastro)

## Doing functional classification of gene groups for 'Tissue' sample label
gastro.mod = activeMod(gastro.summ, sLabelID="Tissue", cutExp=1,
  cutPhiper=0.05)

## Doing functional classification of gene groups together with the
## networks given by Paths slot for 'Tissue' sample label. Also we are
## using a cuttoff for p-value of hipergeometric test as 0.1
gastro.mod = activeMod(gastro.summ, sLabelID="Tissue", cutExp=1,
  cutPhiper=0.1, usePaths=TRUE)