maigesPack (version 1.36.0)

activeNet: Functional classification of gene networks

Description

This function calculate a statistic for each gene network in each biological condition that measure the profile of activation of the network in that condition. Also the function measures the significance of the results.

Usage

activeNet(data=NULL, samples=NULL, sLabelID="Classification", type="Rpearson", bRep=1000, alternative = "greater", adjP="none")

Arguments

data

object of class maiges to be used to functionally classify gene networks stored in Paths slot.

sLabelID

character string specifying identification of sample label to be used.

samples

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

type

character string giving the type of correlation to be calculated. May be 'Rpearson' (default), 'pearson', 'kendall', 'spearman' or 'MI'.

bRep

integer number specifying the bootstraps to be done in the correlation test.

alternative

character string specifying the alternative hypotheses. May be 'greater' (default) to test the activity of the networks in accordance to the to the graph or 'less' to test the activity of the network antagonic to the graph.

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.

Value

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

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.maigesActNet and image.maigesActNet methods to display the results of this analysis.

See Also

activeNetScoreHTML, maigesActNet, plot.maigesActNet, image.maigesActNet, mt.rawp2adjp

Examples

## Loading the dataset
data(gastro)

## Doing functional classification of gene networks for sample Label
## given by 'Tissue'
gastro.net = activeNet(gastro.summ, sLabelID="Tissue")