get_anno_genes {GOfuncR} | R Documentation

## Get genes that are annotated to GO-categories

### Description

Given a vector of GO-IDs, e.g. c('GO:0072025','GO:0072221') this function returns all genes that are annotated to those GO-categories. This includes genes that are annotated to any of the child nodes of a GO-category.

### Usage

    get_anno_genes(go_ids, database = 'Homo.sapiens', genes = NULL, annotations = NULL,
        term_df = NULL, graph_path_df = NULL, godir = NULL)

### Arguments

`go_ids` | character() vector of GO-IDs, e.g. c('GO:0051082', 'GO:0042254').
`database` | optional character() defining an OrganismDb or OrgDb annotation package from Bioconductor, like 'Mus.musculus' (mouse) or 'org.Pt.eg.db' (chimp).
`genes` | optional character() vector of gene-symbols. If defined, only annotations of those genes are returned.
`annotations` | optional data.frame() with two character() columns: gene-symbols and GO-categories. Alternative to 'database'.
`term_df` | optional data.frame() with an ontology 'term' table. Alternative to the default integrated GO-graph or `godir`. Also needs `graph_path_df`.
`graph_path_df` | optional data.frame() with an ontology 'graph_path' table. Alternative to the default integrated GO-graph or `godir`. Also needs `term_df`.
`godir` | optional character() specifying a directory that contains the ontology tables 'term.txt' and 'graph_path.txt'. Alternative to the default integrated GO-graph or `term_df` + `graph_path_df`.

### Details

Besides the default 'Homo.sapiens', also other OrganismDb or OrgDb packages from Bioconductor, like 'Mus.musculus' (mouse) or 'org.Pt.eg.db' (chimp), can be used. It is also possible to directly provide a data.frame() with annotations, which is then searched for the input GO-categories and their child nodes.

By default the package's integrated GO-graph is used to find child nodes, but a custom ontology can be defined, too. For details on how to use a custom ontology with `term_df` + `graph_path_df` or `godir` please refer to the package's vignette. The advantage of `term_df` + `graph_path_df` over `godir` is that the latter reads the files 'term.txt' and 'graph_path.txt' from disk and therefore takes longer.

### Value

A data.frame() with two columns: GO-IDs (character()) and the annotated genes (character()). The output is ordered by GO-ID and gene-symbol.

### Author(s)

Steffi Grote

### References

[1] Ashburner, M. et al. (2000). Gene Ontology: tool for the unification of biology. Nature Genetics 25, 25-29.

### See Also

`get_anno_categories`
`get_ids`
`get_names`
`get_child_nodes`
`get_parent_nodes`

### Examples

    ## find all genes that are annotated to GO:0000109
    ## ("nucleotide-excision repair complex")
    get_anno_genes(go_ids='GO:0000109')

    ## find out wich genes from a set of genes
    ## are annotated to some GO-categories
    genes = c('AGTR1', 'ANO1', 'CALB1', 'GYG1', 'PAX2')
    gos = c('GO:0001558', 'GO:0005536', 'GO:0072205', 'GO:0006821')
    anno_genes = get_anno_genes(go_ids=gos, genes=genes)
    # add the names and domains of the GO-categories
    cbind(anno_genes ,get_names(anno_genes$go_id)[,2:3])

    ## find all annotations to GO-categories containing 'serotonin receptor'
    sero_ids = get_ids('serotonin receptor')
    sero_anno = get_anno_genes(go_ids=sero_ids$go_id)
    # merge with names of GO-categories
    head(merge(sero_ids, sero_anno))

[Package GOfuncR version 1.2.0 Index]