| build_GO_SS {ViSEAGO} | R Documentation |
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.
build_GO_SS(gene2GO, enrich_GO_terms) ## S4 method for signature 'gene2GO,enrich_GO_terms' build_GO_SS(gene2GO, enrich_GO_terms)
gene2GO |
a |
enrich_GO_terms |
a |
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.
a GO_SS-class object required by compute_SS_distances.
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.
Other GO_semantic_similarity:
GO_SS-class,
compute_SS_distances()
## 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"
)