Last data update: 2014.03.03

 R: Functions which map gene identifiers to GO terms
annFUNR Documentation

Functions which map gene identifiers to GO terms

Description

These functions are used to compile a list of GO terms such that each element in the list is a character vector containing all the gene identifiers that are mapped to the respective GO term.

Usage

annFUN.db(whichOnto, feasibleGenes = NULL, affyLib)
annFUN.org(whichOnto, feasibleGenes = NULL, mapping, ID = "entrez") 
annFUN(whichOnto, feasibleGenes = NULL, affyLib)
annFUN.gene2GO(whichOnto, feasibleGenes = NULL, gene2GO)
annFUN.GO2genes(whichOnto, feasibleGenes = NULL, GO2genes)
annFUN.file(whichOnto, feasibleGenes = NULL, file, ...)

readMappings(file, sep = "\t", IDsep = ",")
inverseList(l)

Arguments

whichOnto

character string specifying one of the three GO ontologies, namely: "BP", "MF", "CC"

feasibleGenes

character vector containing a subset of gene identifiers. Only these genes will be used to annotate GO terms. Default value is NULL which means that there are no genes filtered.

affyLib

character string containing the name of the Bioconductor annotaion package for a specific microarray chip.

gene2GO

named list of character vectors. The list names are genes identifiers. For each gene the character vector contains the GO identifiers it maps to. Only the most specific annotations are required.

GO2genes

named list of character vectors. The list names are GO identifiers. For each GO the character vector contains the genes identifiers which are mapped to it. Only the most specific annotations are required.

mapping

character string specifieng the name of the Bioconductor package containing the gene mappings for a specific organism. For example: mapping = "org.Hs.eg.db".

ID

character string specifing the gene identifier to use. Currently only the following identifiers can be used: c("entrez", "genbank", "alias", "ensembl", "symbol", "genename", "unigene")

file

character string specifing the file containing the annotations.

...

other parameters

sep

the character used to separate the columns in the CSV file

IDsep

the character used to separate the annotated entities

l

a list containing mappings

Details

All these function restrict the GO terms to the ones belonging to the specified ontology and to the genes listed in the feasibleGenes attribute (if not empty).

The function annFUN.db uses the mappings provided in the Bioconductor annotation data packages. For example, if the Affymetrix hgu133a chip it is used, then the user should set affyLib = "hgu133a.db".

The functions annFUN.gene2GO and annFUN.GO2genes are used when the user provide his own annotations either as a gene-to-GOs mapping, either as a GO-to-genes mapping.

The annFUN.org function is using the mappings from the "org.XX.XX" annotation packages. The function supports different gene identifiers.

The annFUN.file function will read the annotationsof the type gene2GO or GO2genes from a text file.

Value

A named(GO identifiers) list of character vectors.

Author(s)

Adrian Alexa

See Also

topGOdata-class

Examples


library(hgu133a.db)
set.seed(111)

## generate a gene list and the GO annotations
selGenes <- sample(ls(hgu133aGO), 50)
gene2GO <- lapply(mget(selGenes, envir = hgu133aGO), names)
gene2GO[sapply(gene2GO, is.null)] <- NA

## the annotation for the first three genes
gene2GO[1:3]

## inverting the annotations
G2g <- inverseList(gene2GO)

## inverting the annotations and selecting an ontology
go2genes <- annFUN.gene2GO(whichOnto = "CC", gene2GO = gene2GO)


## generate a GO list with the genes annotations
selGO <- sample(ls(hgu133aGO2PROBE), 30)
GO2gene <- lapply(mget(selGO, envir = hgu133aGO2PROBE), as.character)

GO2gene[1:3]

## select only the GO terms for a specific ontology
go2gene <- annFUN.GO2genes(whichOnto = "CC", GO2gene = GO2gene)


##################################################
## Using the org.XX.xx.db annotations
##################################################

## GO to Symbol mappings (only the BP ontology is used)
xx <- annFUN.org("BP", mapping = "org.Hs.eg.db", ID = "symbol")
head(xx)

## Not run: 

allGenes <- unique(unlist(xx))
myInterestedGenes <- sample(allGenes, 500)
geneList <- factor(as.integer(allGenes 
names(geneList) <- allGenes

GOdata <- new("topGOdata",
              ontology = "BP",
              allGenes = geneList,
              nodeSize = 5,
              annot = annFUN.org, 
              mapping = "org.Hs.eg.db",
              ID = "symbol") 

## End(Not run)

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(topGO)
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

Loading required package: graph
Loading required package: Biobase
Welcome to Bioconductor

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

Loading required package: GO.db
Loading required package: AnnotationDbi
Loading required package: stats4
Loading required package: IRanges
Loading required package: S4Vectors

Attaching package: 'S4Vectors'

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

    colMeans, colSums, expand.grid, rowMeans, rowSums


Loading required package: SparseM

Attaching package: 'SparseM'

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

    backsolve


groupGOTerms: 	GOBPTerm, GOMFTerm, GOCCTerm environments built.

Attaching package: 'topGO'

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

    members

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/topGO/annFUN.Rd_%03d_medium.png", width=480, height=480)
> ### Name: annFUN
> ### Title: Functions which map gene identifiers to GO terms
> ### Aliases: annFUN.db annFUN annFUN.GO2genes annFUN.gene2GO annFUN.file
> ###   annFUN.org inverseList readMappings
> ### Keywords: misc
> 
> ### ** Examples
> 
> 
> library(hgu133a.db)
Loading required package: org.Hs.eg.db


> set.seed(111)
> 
> ## generate a gene list and the GO annotations
> selGenes <- sample(ls(hgu133aGO), 50)
> gene2GO <- lapply(mget(selGenes, envir = hgu133aGO), names)
> gene2GO[sapply(gene2GO, is.null)] <- NA
> 
> ## the annotation for the first three genes
> gene2GO[1:3]
$`213834_at`
[1] "GO:0030036" "GO:0032012" "GO:0043547" "GO:0005737" "GO:0045211"
[6] "GO:0060077" "GO:0005086"

$`216818_s_at`
[1] "GO:0007186" "GO:0007608" "GO:0050911" "GO:0050911" "GO:0005886"
[6] "GO:0016021" "GO:0004930" "GO:0004984"

$`208759_at`
 [1] "GO:0002262" "GO:0006508" "GO:0006509" "GO:0006509" "GO:0007219"
 [6] "GO:0007220" "GO:0007411" "GO:0016485" "GO:0016485" "GO:0022617"
[11] "GO:0030198" "GO:0031293" "GO:0042098" "GO:0042987" "GO:0043065"
[16] "GO:0043085" "GO:0043085" "GO:0048011" "GO:0048013" "GO:0050435"
[21] "GO:0050673" "GO:0097190" "GO:0005765" "GO:0005783" "GO:0005783"
[26] "GO:0005794" "GO:0005794" "GO:0005886" "GO:0005887" "GO:0005887"
[31] "GO:0005925" "GO:0016020" "GO:0016021" "GO:0042470" "GO:0070062"
[36] "GO:0004175" "GO:0005515"

> 
> ## inverting the annotations
> G2g <- inverseList(gene2GO)
> 
> ## inverting the annotations and selecting an ontology
> go2genes <- annFUN.gene2GO(whichOnto = "CC", gene2GO = gene2GO)
> 
> 
> ## generate a GO list with the genes annotations
> selGO <- sample(ls(hgu133aGO2PROBE), 30)
> GO2gene <- lapply(mget(selGO, envir = hgu133aGO2PROBE), as.character)
> 
> GO2gene[1:3]
$`GO:0055001`
[1] "205897_at"   "213345_at"   "210329_s_at" "210330_at"   "213543_at"  
[6] "214492_at"   "207302_at"   "212849_at"   "212348_s_at"

$`GO:0043931`
[1] "200059_s_at" "215668_s_at" "215807_s_at" "205485_at"   "209561_at"  
[6] "218892_at"   "222101_s_at" "203528_at"   "219427_at"  

$`GO:0001743`
[1] "212849_at"

> 
> ## select only the GO terms for a specific ontology
> go2gene <- annFUN.GO2genes(whichOnto = "CC", GO2gene = GO2gene)
> 
> 
> ##################################################
> ## Using the org.XX.xx.db annotations
> ##################################################
> 
> ## GO to Symbol mappings (only the BP ontology is used)
> xx <- annFUN.org("BP", mapping = "org.Hs.eg.db", ID = "symbol")
> head(xx)
$`GO:0000002`
 [1] "SLC25A4"  "TYMP"     "MEF2A"    "MPV17"    "OPA1"     "LONP1"   
 [7] "AKT3"     "SLC25A36" "MRPL17"   "PIF1"     "SLC25A33" "MGME1"   

$`GO:0000003`
[1] "MMP23B" "WDR43" 

$`GO:0000011`
[1] "RBSN"

$`GO:0000012`
[1] "LIG4"         "TNP1"         "XRCC1"        "SIRT1"        "APTX"        
[6] "TDP1"         "APLF"         "LOC100133315"

$`GO:0000018`
[1] "IL7R"     "KPNA1"    "KPNA2"    "THOC1"    "ALYREF"   "SMARCAD1"

$`GO:0000019`
[1] "MRE11A" "RAD50" 

> 
> ## Not run: 
> ##D 
> ##D allGenes <- unique(unlist(xx))
> ##D myInterestedGenes <- sample(allGenes, 500)
> ##D geneList <- factor(as.integer(allGenes ##D 
> ##D names(geneList) <- allGenes
> ##D 
> ##D GOdata <- new("topGOdata",
> ##D               ontology = "BP",
> ##D               allGenes = geneList,
> ##D               nodeSize = 5,
> ##D               annot = annFUN.org, 
> ##D               mapping = "org.Hs.eg.db",
> ##D               ID = "symbol") 
> ## End(Not run)
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>


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