Package: rols
Authors: Laurent Gatto [email protected], with contributions from Tiago Chedraoui Silva.
Modified: 2016-10-17 16:19:09
Compiled: Wed Jan 25 19:06:52 2017
The Ontology Lookup Service (OLS) [1, 2] is originally spin-off of the PRoteomics IDEntifications database (PRIDE) service, located at the EBI, and is now developed and maintained by the Samples, Phenotypes and Ontologies team at EMBL-EBI.
The OLS provides a REST interface to hundreds of ontologies from a single location with a unified output format. The rols package make this possible from within R. Do do so, it relies on the httr package to query the REST interface, and access and retrieve data.
There are 162 ontologies available in the OLS, listed in the table below. Their name is to be use to defined which ontology to query.
The rols package is build around a few classes that enable to query the OLS and retrieve, store and manipulate data. Each of these classes are described in more details in their respective manual pages. We start by loading the package.
library("rols")The Ontology and Ontologies classes can store information about single of multiple ontologies. The latter can be easily subset using [ and [[, as one would for lists.
ol <- Ontologies()
ol## Object of class 'Ontologies' with 162 entries
## AEO, AERO ... OAE, OMPhead(olsNamespace(ol))## aeo aero agro ancestro apo atol
## "aeo" "aero" "agro" "ancestro" "apo" "atol"ol[["go"]]## Ontology: Gene Ontology (go)
## An ontology for describing the function of genes and gene products
## Loaded: 2017-01-25 Updated: 2017-01-25 Version: 2017-01-24
## 48222 terms 66 properties 0 individualsIt is also possible to initialise a single ontology
go <- Ontology("go")
go## Ontology: Gene Ontology (go)
## An ontology for describing the function of genes and gene products
## Loaded: 2017-01-25 Updated: 2017-01-25 Version: 2017-01-24
## 48222 terms 66 properties 0 individualsSingle ontology terms are stored in Term objects. When more terms need to be manipulated, they are stored as Terms objects. It is easy to obtain all terms of an ontology of interest, and the resulting Terms object can be subset using [ and [[, as one would for lists.
gotrms <- terms(go) ## or terms("go")
gotrms## Object of class 'Terms' with 48223 entries
## From the GO ontology
## GO:0005230, GO:0015276 ... GO:0032942, GO:0019987gotrms[1:10]## Object of class 'Terms' with 10 entries
## From the GO ontology
## GO:0005230, GO:0015276 ... GO:0032852, GO:0005234gotrms[["GO:0090575"]]## A Term from the GO ontology: GO:0090575
## Label: RNA polymerase II transcription factor complex
## A transcription factor complex that acts at promoters of genes
## transcribed by RNA polymerase II.It is also possible to initialise a single term
trm <- term(go, "GO:0090575")
termId(trm)## [1] "GO:0090575"termLabel(trm)## [1] "RNA polymerase II transcription factor complex"strwrap(termDesc(trm))## [1] "A transcription factor complex that acts at promoters of genes"
## [2] "transcribed by RNA polymerase II."It is then possible to extract the ancestors, descendants, parents and children terms. Each of these functions return a Terms object
parents(trm)## Object of class 'Terms' with 1 entries
## From the GO ontology
## GO:0044798children(trm)## Object of class 'Terms' with 20 entries
## From the GO ontology
## GO:0005675, GO:0005674 ... GO:0097221, GO:0036488Similarly, the partOf and derivesFrom functions return, for an input term, the terms it is a part of and derived from.
Properties (relationships) of single or multiple terms or complete ontologies can be queries with the properties method, as briefly illustrated below.
trm <- term("uberon", "UBERON:0002107")
trm## A Term from the UBERON ontology: UBERON:0002107
## Label: liver
## An exocrine gland which secretes bile and functions in metabolism
## of protein and carbohydrate and fat, synthesizes substances
## involved in the clotting of the blood, synthesizes vitamin A,
## detoxifies poisonous substances, stores glycogen, and breaks down
## worn-out erythrocytes[GO].p <- properties(trm)
p## Object of class 'Properties' with 1011 entries
## From the UBERON ontology
## digestive gland, abdomen element ... liver bud, liver primordiump[[1]]## A Property from the UBERON ontology: UBERON:0006925
## Label: digestive glandtermLabel(p[[1]])## [1] "digestive gland"A researcher might be interested in the trans-Golgi network. Searching the OLS is assured by the OlsSearch and olsSearch classes/functions. The first step is to defined the search query with OlsSearch, as shown below. This creates an search object of class OlsSearch that stores the query and its parameters. In records the number of requested results (default is 20) and the total number of possible results (there are 13688 results across all ontologies, in this case). At this stage, the results have not yet been downloaded, as shown by the 0 responses.
OlsSearch(q = "trans-golgi network")## Object of class 'OlsSearch':
## query: trans-golgi network
## requested: 20 (out of 13688)
## response(s): 013688 results are probably too many to be relevant. Below we show how to perform an exact search by setting exact = TRUE, and limiting the search the the GO ontology by specifying ontology = "GO", or doing both.
OlsSearch(q = "trans-golgi network", exact = TRUE)## Object of class 'OlsSearch':
## query: trans-golgi network
## requested: 20 (out of 7)
## response(s): 0OlsSearch(q = "trans-golgi network", ontology = "GO")## Object of class 'OlsSearch':
## ontolgy: GO
## query: trans-golgi network
## requested: 20 (out of 698)
## response(s): 0OlsSearch(q = "trans-golgi network", ontology = "GO", exact = TRUE)## Object of class 'OlsSearch':
## ontolgy: GO
## query: trans-golgi network
## requested: 20 (out of 1)
## response(s): 0One case set the rows argument to set the number of desired results.
OlsSearch(q = "trans-golgi network", ontology = "GO", rows = 200)## Object of class 'OlsSearch':
## ontolgy: GO
## query: trans-golgi network
## requested: 200 (out of 698)
## response(s): 0Alternatively, one can call the allRows function to request all results.
(tgnq <- OlsSearch(q = "trans-golgi network", ontology = "GO"))## Object of class 'OlsSearch':
## ontolgy: GO
## query: trans-golgi network
## requested: 20 (out of 698)
## response(s): 0(tgnq <- allRows(tgnq))## Object of class 'OlsSearch':
## ontolgy: GO
## query: trans-golgi network
## requested: 698 (out of 698)
## response(s): 0Let’s proceed with the exact search and retrieve the results. Even if we request the default 20 results, only the 7 relevant result will be retrieved. The olsSearch function updates the previously created object (called qry below) by adding the results to it.
qry <- OlsSearch(q = "trans-golgi network", exact = TRUE)
(qry <- olsSearch(qry))## Object of class 'OlsSearch':
## query: trans-golgi network
## requested: 20 (out of 7)
## response(s): 7We can now transform this search result object into a fully fledged Terms object or a data.frame.
(qtrms <- as(qry, "Terms"))## Object of class 'Terms' with 7 entries
## From 7 ontologies
## OMIT:0020822, GO:0005802 ... GO:0005802, GO:0005802(qdrf <- as(qry, "data.frame"))## id
## 1 omit:http://purl.obolibrary.org/obo/OMIT_0020822
## 2 go:http://purl.obolibrary.org/obo/GO_0005802
## 3 cco:http://purl.obolibrary.org/obo/GO_0005802
## 4 nbo:http://purl.obolibrary.org/obo/GO_0005802
## 5 gexo:http://purl.obolibrary.org/obo/GO_0005802
## 6 rexo:http://purl.obolibrary.org/obo/GO_0005802
## 7 reto:http://purl.obolibrary.org/obo/GO_0005802
## iri short_form obo_id
## 1 http://purl.obolibrary.org/obo/OMIT_0020822 OMIT_0020822 OMIT:0020822
## 2 http://purl.obolibrary.org/obo/GO_0005802 GO_0005802 GO:0005802
## 3 http://purl.obolibrary.org/obo/GO_0005802 GO_0005802 GO:0005802
## 4 http://purl.obolibrary.org/obo/GO_0005802 GO_0005802 GO:0005802
## 5 http://purl.obolibrary.org/obo/GO_0005802 GO_0005802 GO:0005802
## 6 http://purl.obolibrary.org/obo/GO_0005802 GO_0005802 GO:0005802
## 7 http://purl.obolibrary.org/obo/GO_0005802 GO_0005802 GO:0005802
## label ontology_name ontology_prefix type
## 1 trans-Golgi Network omit OMIT class
## 2 trans-Golgi network go GO class
## 3 trans-Golgi network cco CCO class
## 4 trans-Golgi network nbo NBO class
## 5 trans-Golgi network gexo GeXO individual
## 6 trans-Golgi network rexo ReXO individual
## 7 trans-Golgi network reto ReTO individual
## is_defining_ontology
## 1 TRUE
## 2 TRUE
## 3 FALSE
## 4 FALSE
## 5 FALSE
## 6 FALSE
## 7 FALSE
## description
## 1 NULL
## 2 The network of interconnected tubular and cisternal structures located within the Golgi apparatus on the side distal to the endoplasmic reticulum, from which secretory vesicles emerge. The trans-Golgi network is important in the later stages of protein secretion where it is thought to play a key role in the sorting and targeting of secreted proteins to the correct destination.
## 3 The network of interconnected tubular and cisternal structures located within the Golgi apparatus on the side distal to the endoplasmic reticulum, from which secretory vesicles emerge. The trans-Golgi network is important in the later stages of protein secretion where it is thought to play a key role in the sorting and targeting of secreted proteins to the correct destination.
## 4 The network of interconnected tubular and cisternal structures located within the Golgi apparatus on the side distal to the endoplasmic reticulum, from which secretory vesicles emerge. The trans-Golgi network is important in the later stages of protein secretion where it is thought to play a key role in the sorting and targeting of secreted proteins to the correct destination.
## 5 The network of interconnected tubular and cisternal structures located within the Golgi apparatus on the side distal to the endoplasmic reticulum, from which secretory vesicles emerge. The trans-Golgi network is important in the later stages of protein secretion where it is thought to play a key role in the sorting and targeting of secreted proteins to the correct destination.
## 6 The network of interconnected tubular and cisternal structures located within the Golgi apparatus on the side distal to the endoplasmic reticulum, from which secretory vesicles emerge. The trans-Golgi network is important in the later stages of protein secretion where it is thought to play a key role in the sorting and targeting of secreted proteins to the correct destination.
## 7 The network of interconnected tubular and cisternal structures located within the Golgi apparatus on the side distal to the endoplasmic reticulum, from which secretory vesicles emerge. The trans-Golgi network is important in the later stages of protein secretion where it is thought to play a key role in the sorting and targeting of secreted proteins to the correct destination.In this case, we can see that we actually retrieve the same term used across different ontologies. In such cases, it might be useful to keep only non-redundant term instances. In this case, this would have been equivalent to searching the omit, go ontology
qtrms <- unique(qtrms)
termOntology(qtrms)## OMIT:0020822 GO:0005802
## "omit" "go"termNamespace(qtrms)## $`OMIT:0020822`
## NULL
##
## $`GO:0005802`
## [1] "cellular_component"Below, we execute the same query using the GO.db package.
library("GO.db")
GOTERM[["GO:0005802"]]## GOID: GO:0005802
## Term: trans-Golgi network
## Ontology: CC
## Definition: The network of interconnected tubular and cisternal
## structures located within the Golgi apparatus on the side
## distal to the endoplasmic reticulum, from which secretory
## vesicles emerge. The trans-Golgi network is important in the
## later stages of protein secretion where it is thought to play
## a key role in the sorting and targeting of secreted proteins
## to the correct destination.
## Synonym: Golgi trans face
## Synonym: Golgi trans-face
## Synonym: late Golgi
## Synonym: maturing face
## Synonym: TGN
## Synonym: trans face
## Synonym: trans Golgi networkIt is possible to observe different results with rols and r Biocpkg("GO.db"), as a result of the different ways they access the data. rols or r Biocpkg("biomaRt") perform direct online queries, while GO.db and other annotation packages use database snapshot that are updated every release.
Both approaches have advantages. While online queries allow to obtain the latest up-to-date information, such approaches rely on network availability and quality. If reproducibility is a major issue, the version of the database to be queried can easily be controlled with off-line approaches. In the case of rols, although the load date of a specific ontology can be queried with olsVersion, it is not possible to query a specific version of an ontology.
rols 2.0 has substantially changed. While the table below shows some correspondence between the old and new interface, this is not always the case. The new interface relies on the Ontology/Ontologies, Term/Terms and OlsSearch classes, that need to be instantiated and can then be queried, as described above.
| version < 1.99 | version >= 1.99 |
|---|---|
ontologyLoadDate |
olsLoaded and olsUpdated |
ontologyNames |
Ontologies |
olsVersion |
olsVersion |
allIds |
terms |
isIdObsolete |
isObsolete |
rootId |
olsRoot |
olsQuery |
OlsSearch and olsSearch |
Not all functionality is currently available. If there is anything that you need but not available in the new version, please contact the maintained by opening an issue on the package development site.
The CVParam class is used to handle controlled vocabulary. It can be used for user-defined parameters
CVParam(name = "A user param", value = "the value")## [, , A user param, the value]or official controlled vocabulary (which triggers a query to the OLS service)
CVParam(label = "MS", accession = "MS:1000073")## [MS, MS:1000073, electrospray ionization, ]CVParam(label = "MS", name ="electrospray ionization")## [MS, MS:1000073, electrospray ionization, ]CVParam(label = "MS", name ="ESI") ## using a synonym## [MS, MS:1000073, ESI, ]See ?CVParam for more details and examples.
## R version 3.3.2 (2016-10-31)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 16.04.1 LTS
##
## attached base packages:
## [1] parallel stats4 stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] DT_0.2 rols_2.2.5 GO.db_3.4.0
## [4] AnnotationDbi_1.36.1 IRanges_2.8.1 S4Vectors_0.12.1
## [7] Biobase_2.34.0 BiocGenerics_0.20.0 BiocStyle_2.2.1
##
## loaded via a namespace (and not attached):
## [1] Rcpp_0.12.9 knitr_1.15.1 magrittr_1.5
## [4] progress_1.1.2 R6_2.2.0 stringr_1.1.0
## [7] httr_1.2.1 tools_3.3.2 DBI_0.5-1
## [10] htmltools_0.3.5 assertthat_0.1 yaml_2.1.14
## [13] rprojroot_1.2 digest_0.6.11 htmlwidgets_0.8
## [16] curl_2.3 memoise_1.0.0 evaluate_0.10
## [19] RSQLite_1.1-2 rmarkdown_1.3 stringi_1.1.2
## [22] prettyunits_1.0.2 backports_1.0.5 jsonlite_1.2