R: GO enrichment methods

GOEnrich.folder-methods {R3CPET}

R Documentation

GO enrichment methods

Description

This helper methods can be called to do GO enrichment by using the DAVID web service.

GOEnrich.networks can be used to do a GO enrichment of the chromatin maintainer networks.

GOEnrich.folder can be called to do a GO enrichment on the gene-list files generated by the method outputGenesPerClusterToDir.

There is a 5 secs delay between each request to not avoid being rejected by the server.

Usage

## S4 method for signature 'character'
GOEnrich.folder(folder, fdr=0.05,GOlimit=20)

## S4 method for signature 'ChromMaintainers'
GOEnrich.networks(object, fdr=0.05, GOlimit= 5,path="")

Arguments

`folder`	name of the folder that contains the gene-list files. The files are supposed to have a `.txt` extension. The first column of each file is supposed to contain the genes EntrezID.
`object`	a `"ChromMaintainers"` objects with the `topNodes` already calculated.
`fdr`	cut-off value GO terms with fdr value <= fdr will be considered. Benjamini-Hochberg FDR is used.
`GOlimit`	the number of top GO terms to return.
`path`	the path where to store the generated plot (pdf file). if not specified the plot will be displayed.

Value

Returns a list of data.frame that contain the GO results for each file (or network).

Author(s)

Mohamed Nadhir Djekidel (nde12@mails.tsinghua.edu.cn)

References

http://david.abcc.ncifcrf.gov/ (DAVID website)

Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID Bioinformatics Resources. Nature Protoc. 2009;4(1):44-57.

Examples

    ## get the different datasets path
    petFile <- file.path(system.file("example",package="R3CPET"),"HepG2_interactions.txt")  
    tfbsFile <- file.path(system.file("example",package="R3CPET"),"HepG2_TF.txt.gz")  

 ## Not run: 

    x <- ChiapetExperimentData(pet = petFile, tfbs=  tfbsFile, IsBed = FALSE, ppiType="HPRD", filter= TRUE) 
    ## build the different indexes
    x <- createIndexes(x)
  
    ## build networks connecting each interacting regions
    nets<- buildNetworks(x)

    ## infer the networks
    hlda<- InferNetworks(nets)

    ## Get the list of genes in each cluster by default 
    ## a folder ClustersGenes will be created
    outputGenesPerClusterToDir(hlda,x)

    ## GO enrichment 
    GOEnrich.folder(folder="ClustersGenes/")


## End(Not run)

[Package R3CPET version 1.20.0 Index]