activeMod: Functional classification of gene groups
In maigesPack: Functions to handle cDNA microarray data, including several methods of data analysis

Description Usage Arguments Details Value Author(s) References See Also Examples

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

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

`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.

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).

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

Gustavo H. Esteves <gesteves@vision.ime.usp.br>

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)

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

## 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)