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Last data update: 2014.03.03

R: Functional classification of gene groups

activeMod

R Documentation

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.

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).

Value

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

Author(s)

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

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)

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)

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.
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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/activeMod.Rd_%03d_medium.png", width=480, height=480)
> ### Name: activeMod
> ### Title: Functional classification of gene groups
> ### Aliases: activeMod
> ### Keywords: methods
> 
> ### ** 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)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>