download_Yeast_GO_mapping: downloads the Gene Ontology attributes mapped to Yeast genes

In pasculescu/ClusterJudge: Judging Quality of Clustering Methods using Mutual Information

Description

The Gene Ontology attributes are provided for example by the Saccharomyces Genome Database (SGD) as a zipped file with a wealth of information. The function filters from the file only the minimal information necessary: THe Gene Ontology attribute id (GOID) and the Yeast Gene Id (SGDID) for which the attribute applies

Usage

download_Yeast_GO_mapping(
    yeast.GO.url = "http://downloads.yeastgenome.org/curation/literature/gene_association.sgd.gz")

Arguments

yeast.GO.url

The web site address where the Yeast genes and their Gene Ontology attribute files is located.

Details

Only the unique associations between genes and their attributes are kept. In the original downloaded file there might be redundanies due to the different types of evidences used in the associations.

The downloaded file is expected to be in a tab delimited format with comment lines that start with the exclamation (!) caharacter. The commented lines are ignored. The expected column names can be obrtained by looking at the function code.

Value

a data.frame with two columns: SGDID - the ids of the Yeast gene names (these are the 'entities') GOID - the ids of the Gene Ontology attributes corresponding to the above genes

Note

since the download is time consuming, this package provides also as a dataset called Yeast.GO.assocs containing the associations already downloaded as of on Fenruary 2017.

For other species one can use specialized R and Bioconductor packages such as biomaRt (see the commented part in the example section).

Author(s)

Adrian Pasculescu

References

http://www.yeastgenome.org/ http://www.geneontology.org/

See Also

Yeast.GO.assocs help, ~~~

Examples

Yeast.GO.assocs <- download_Yeast_GO_mapping()

# For other species one can use specialized R and Bioconductor packages such as biomaRt 
# as in the following `toy` commented example:
#library(biomaRt)
#rn <-  useDataset("rnorvegicus_gene_ensembl", mart=useMart("ensembl"))
### exemplify for a limited set of  genes
#rgd.symbol=c("As3mt", "Borcs7", "Cyp17a1", "Wbp1l", "Sfxn2", "Arl3") 
#entity.attr=getBM(attributes=c('rgd_symbol','go_id'), filters='rgd_symbol', values=rgd.symbol, mart=rn)

pasculescu/ClusterJudge documentation built on May 29, 2019, 4:52 p.m.