ontologyIndex is the foundation of the ‘ontologyX’ packages:
ontologyIndex, for representing ontologies as R objects and enabling simple queries,ontologySimilarity, for computing semantic similarity between ontological terms and annotations,ontologyPlot for visualising sets of ontological terms with various graphical options.The functionality of the ontologyIndex package is centered around ontology_index objects: simple R representations of ontologies as lists and vectors of term properties (ID, label, etc.) which are named by term so that simple look-ups by term can be performed. Ontologies encoded in OBO format can be read into R as ontology_indexes using the function get_ontology (see the vignette ‘Creating an ontology_index’). Ontologies in OWL syntax can be converted to OBO format using freely available software (e.g. the ROBOT command line tool: https://github.com/ontodev/robot). The package comes with three such ready-made ontology_index objects: hpo, mpo and go, encapsulating the Human Phenotype Ontology (HPO), Mammalian Phenotype Ontology (MPO) and Gene Ontology (GO) respectively, each loadable with data. Here we’ll demonstrate the package using the HPO.
library(ontologyIndex)
data(hpo)The ontology_index object is just a list of ‘vectors and lists’ of term properties, indexed by the IDs of the terms:
## property class
## 1 id character
## 2 name character
## 3 parents list
## 4 children list
## 5 ancestors list
## 6 obsolete logicalThe properties which all ontology_index objects contain are id, name, parents, children and ancestors as these are the properties which the functions in the ontologyIndex package operate on. However, additional properties per term - for example custom annotation, or whatever terms are tagged with in the original OBO file - can also be read in and queried in the same way (see the vignette ‘Creating an ontology_index’).
The children and ancestors properties are determined by the parent property, with the ancestors of a term derived by propagating the ‘is parent’ relation (i.e. with the terms for which the relation holds given in the parent property). When reading an ontology_index from an OBO file, the ‘is parent’ relation defaults to “is_a”. However, this can be set to any relation or combination of relations (e.g. “part_of” or both “is_a” and “part_of” - see ‘Creating an ontology_index’ and ?get_ontology for more details). Usage of phrases involving ‘ancestors’ and ‘descendants’ of terms in this document and in the names of functions exported by the package refer to the hierarchy determined by this parent property.
You can use the function get_term_property to query the ontology_index object, and retrieve a particular attribute for a single term. For instance:
get_term_property(ontology=hpo, property="ancestors", term="HP:0001873", as_names=TRUE)## HP:0000001
## "All"
## HP:0000118
## "Phenotypic abnormality"
## HP:0001871
## "Abnormality of blood and blood-forming tissues"
## HP:0001872
## "Abnormality of thrombocytes"
## HP:0011875
## "Abnormal platelet morphology"
## HP:0011873
## "Abnormal platelet count"
## HP:0001873
## "Thrombocytopenia"However you can also look up properties for a given term using [ and [[ as appropriate, since an ontology_index just a list. This is the best way to use the ontology_index if you are operating on multiple terms as it’s faster.
hpo$name["HP:0001873"]## HP:0001873
## "Thrombocytopenia"hpo$id[grep(x=hpo$name, pattern="Thrombocytopenia")]## HP:0001873
## "HP:0001873"hpo$ancestors[["HP:0001873"]]## HP:0000001 HP:0000118 HP:0001871 HP:0001872 HP:0011875 HP:0011873
## "HP:0000001" "HP:0000118" "HP:0001871" "HP:0001872" "HP:0011875" "HP:0011873"
## HP:0001873
## "HP:0001873"hpo$name[hpo$ancestors[["HP:0001873"]]]## HP:0000001
## "All"
## HP:0000118
## "Phenotypic abnormality"
## HP:0001871
## "Abnormality of blood and blood-forming tissues"
## HP:0001872
## "Abnormality of thrombocytes"
## HP:0011875
## "Abnormal platelet morphology"
## HP:0011873
## "Abnormal platelet count"
## HP:0001873
## "Thrombocytopenia"A set of terms (i.e. a character vector of term IDs) may contain redundant terms. The function minimal_set removes such terms leaving a minimal set in the sense of the ontology’s directed acyclic graph.
terms <- c("HP:0001871", "HP:0001873", "HP:0011877")
hpo$name[terms]## HP:0001871
## "Abnormality of blood and blood-forming tissues"
## HP:0001873
## "Thrombocytopenia"
## HP:0011877
## "Increased mean platelet volume"minimal <- minimal_set(hpo, terms)
hpo$name[minimal]## HP:0001873 HP:0011877
## "Thrombocytopenia" "Increased mean platelet volume"To find all the ancestors of a set of terms, i.e. all the terms which are an ancestor of any term in the given set, one can use the get_ancestors function:
get_ancestors(hpo, c("HP:0001873", "HP:0011877"))## [1] "HP:0000001" "HP:0000118" "HP:0001871" "HP:0001872" "HP:0011875"
## [6] "HP:0011873" "HP:0001873" "HP:0011876" "HP:0011877"There are functions which allow set operations with respect to descendancy: intersection_with_descendants, exclude_descendants and prune_descendants. Each function accepts a set of terms terms and a set of root terms roots.
intersection_with_descendants transforms terms by retaining only those which are either in the set roots or amongst the descendants of a term in roots.exclude_descendants transforms terms by removing terms which are either in the set roots or amongst the descendants of a term in roots.prune_descendants transforms terms by replacing terms which are either in the set roots or amongst the descendants of a term in roots with the associated set of terms in roots.For more details see the help page for the individual functions, e.g. ?exclude_descendants. Note that to perform analagous operations with respect to sets of ancestors, one can use the get_ancestors function in conjunction with the base R set functions, e.g. setdiff and intersect.
The packages ontologySimilarity and ontologyPlot can be used to calculate semantic similarity between and visualise terms and sets of terms respectively: see the corresponding vignettes for more details.