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Last data update: 2014.03.03

R: Functional classification of gene networks

activeNet

R Documentation

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.

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.

Value

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

Author(s)

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

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")

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(maigesPack)
Loading required package: convert
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: limma

Attaching package: 'limma'

The following object is masked from 'package:BiocGenerics':

    plotMA

Loading required package: marray
Loading required package: graph
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/maigesPack/activeNet.Rd_%03d_medium.png", width=480, height=480)
> ### Name: activeNet
> ### Title: Functional classification of gene networks
> ### Aliases: activeNet
> ### Keywords: methods
> 
> ### ** 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")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>