build_GO_SS-methods: build GO Semantic Similarity object.

In abrionne/ViSEAGO: ViSEAGO: Easier data mining of biological functions organized into clusters using Gene Ontology and semantic similarity

Description

Compute the Information content (IC) on the given ontology, and create a GO_SS-class object required by compute_SS_distances method to compute GO semantic similarity between enriched GO terms or groups of terms.

Usage

build_GO_SS(gene2GO, enrich_GO_terms)

## S4 method for signature 'gene2GO,enrich_GO_terms'
build_GO_SS(gene2GO, enrich_GO_terms)

Arguments

gene2GO	a gene2GO-class object from annotate method.
enrich_GO_terms	a enrich_GO_terms-class from merge_enrich_terms method.

Details

This method use annotate and merge_enrich_terms output objects (see Arguments), and compute the Information content (IC) using the internal code of godata function from GOSemSim package.

Value

a GO_SS-class object required by compute_SS_distances.

References

Alexa A, Rahnenfuhrer J, Lengauer T. Improved scoring of functional groups from gene expression data by decorrelating GO graph structure. Bioinformatics 2006; 22:1600-1607.

Guangchuang Yu, Fei Li, Yide Qin, Xiaochen Bo, Yibo Wu and Shengqi Wang. GOSemSim: an R package for measuring semantic similarity among GO terms and gene products. Bioinformatics 2010 26(7):976-978.

Herve Pages, Marc Carlson, Seth Falcon and Nianhua Li (2017). AnnotationDbi: Annotation Database Interface. R package version 1.38.0.

See Also

Other GO_semantic_similarity: GO_SS-class, compute_SS_distances

Examples

## Not run: 
###################
# initialyse object for compute GO Semantic Similarity
myGOs<-ViSEAGO::build_GO_SS(
    myGENE2GO,
    BP_sResults
)

## End(Not run)
###################
# load data example
utils::data(
    myGOs,
    package="ViSEAGO"
)

abrionne/ViSEAGO documentation built on June 13, 2019, 2:27 p.m.