annFUN {topGO} | R Documentation |
These functions are used to compile a list of GO terms and their mappings to gene identifiers.
annFUN.hgu(whichOnto, feasibleGenes = NULL, affyLib) annFUN.gene2GO(whichOnto, feasibleGenes = NULL, gene2GO) annFUN.GO2genes(whichOnto, feasibleGenes = NULL, GO2genes)
whichOnto |
character string specifying one of the three GO
ontologies: "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 all gene identifiers
will be used. |
affyLib |
character string containing the name of the Affymetrix chip. |
gene2GO |
named list of character vectors. The list names are genes identifiers. For each gene the character vector contains the GO terms IDs it maps to. Only the most specific annotations are required. |
GO2genes |
named list of character vectors. The list names are GO terms IDs. For each GO the character vector contains the genes identifiers which are mapped to it. Only the most specific annotations are required. |
The function annFUN.hgu
should be used when the gene
identifiers are Affymetrix IDs. It 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"
.
The functions annFUN.gene2GO
and annFUN.GO2genes
are
used when the user provide his own annotations.
All these function restrict the GO terms to the ones belonging to the specified ontology.
A named(GO terms IDs) list of character vectors.
Adrian Alexa
library(hgu133a) set.seed(111) ## generate a gene list and the GO annotations numGenes <- 50 selGenes <- sample(ls(hgu133aGO), numGenes) 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 go2genes <- annFUN.gene2GO(whichOnto = "CC", gene2GO = gene2GO) ## generate a GO list with the genes annotations numGO <- 30 selGO <- sample(ls(hgu133aGO2PROBE), numGO) 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)