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OPPL-Galaxy, a Galaxy tool for enhancing ontology exploitation as part of bioinformatics workflows.

Aranguren ME, Fernández-Breis JT, Mungall C, Antezana E, González AR, Wilkinson MD - J Biomed Semantics (2013)

Bottom Line: Use cases are provided in order to demonstrate OPPL-Galaxy's capability for enriching, modifying and querying biomedical ontologies.Coupling OPPL-Galaxy with other bioinformatics tools of the Galaxy framework results in a system that is more than the sum of its parts.OPPL-Galaxy opens a new dimension of analyses and exploitation of biomedical ontologies, including automated reasoning, paving the way towards advanced biological data analyses.

View Article: PubMed Central - HTML - PubMed

Affiliation: Ontology Engineering Group, School of Computer Science, Technical University of Madrid (UPM), Boadilla del Monte, 28660, Spain. mikel.egana.aranguren@upm.es.

ABSTRACT

Background: Biomedical ontologies are key elements for building up the Life Sciences Semantic Web. Reusing and building biomedical ontologies requires flexible and versatile tools to manipulate them efficiently, in particular for enriching their axiomatic content. The Ontology Pre Processor Language (OPPL) is an OWL-based language for automating the changes to be performed in an ontology. OPPL augments the ontologists' toolbox by providing a more efficient, and less error-prone, mechanism for enriching a biomedical ontology than that obtained by a manual treatment.

Results: We present OPPL-Galaxy, a wrapper for using OPPL within Galaxy. The functionality delivered by OPPL (i.e. automated ontology manipulation) can be combined with the tools and workflows devised within the Galaxy framework, resulting in an enhancement of OPPL. Use cases are provided in order to demonstrate OPPL-Galaxy's capability for enriching, modifying and querying biomedical ontologies.

Conclusions: Coupling OPPL-Galaxy with other bioinformatics tools of the Galaxy framework results in a system that is more than the sum of its parts. OPPL-Galaxy opens a new dimension of analyses and exploitation of biomedical ontologies, including automated reasoning, paving the way towards advanced biological data analyses.

No MeSH data available.


Selective extraction of modules from GO for term enrichment (as shown in Galaxy). In this workflow a reduced GAF is obtained by querying GO (i.e., extracting a module) and comparing the retrieved GO terms with the GO terms from the GAF. The resulting reduced GAF is used to perform an enrichment analysis with GO::TermFinder.
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Figure 11: Selective extraction of modules from GO for term enrichment (as shown in Galaxy). In this workflow a reduced GAF is obtained by querying GO (i.e., extracting a module) and comparing the retrieved GO terms with the GO terms from the GAF. The resulting reduced GAF is used to perform an enrichment analysis with GO::TermFinder.

Mentions: OPPL-Galaxy can be combined with OWL-Query-Galaxy to extract a module (Figure 11). The extent of such module can specified with OPPL-Galaxy, for example by adding transitivity to the regulates object property (as a result the module holds more terms):


OPPL-Galaxy, a Galaxy tool for enhancing ontology exploitation as part of bioinformatics workflows.

Aranguren ME, Fernández-Breis JT, Mungall C, Antezana E, González AR, Wilkinson MD - J Biomed Semantics (2013)

Selective extraction of modules from GO for term enrichment (as shown in Galaxy). In this workflow a reduced GAF is obtained by querying GO (i.e., extracting a module) and comparing the retrieved GO terms with the GO terms from the GAF. The resulting reduced GAF is used to perform an enrichment analysis with GO::TermFinder.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3643862&req=5

Figure 11: Selective extraction of modules from GO for term enrichment (as shown in Galaxy). In this workflow a reduced GAF is obtained by querying GO (i.e., extracting a module) and comparing the retrieved GO terms with the GO terms from the GAF. The resulting reduced GAF is used to perform an enrichment analysis with GO::TermFinder.
Mentions: OPPL-Galaxy can be combined with OWL-Query-Galaxy to extract a module (Figure 11). The extent of such module can specified with OPPL-Galaxy, for example by adding transitivity to the regulates object property (as a result the module holds more terms):

Bottom Line: Use cases are provided in order to demonstrate OPPL-Galaxy's capability for enriching, modifying and querying biomedical ontologies.Coupling OPPL-Galaxy with other bioinformatics tools of the Galaxy framework results in a system that is more than the sum of its parts.OPPL-Galaxy opens a new dimension of analyses and exploitation of biomedical ontologies, including automated reasoning, paving the way towards advanced biological data analyses.

View Article: PubMed Central - HTML - PubMed

Affiliation: Ontology Engineering Group, School of Computer Science, Technical University of Madrid (UPM), Boadilla del Monte, 28660, Spain. mikel.egana.aranguren@upm.es.

ABSTRACT

Background: Biomedical ontologies are key elements for building up the Life Sciences Semantic Web. Reusing and building biomedical ontologies requires flexible and versatile tools to manipulate them efficiently, in particular for enriching their axiomatic content. The Ontology Pre Processor Language (OPPL) is an OWL-based language for automating the changes to be performed in an ontology. OPPL augments the ontologists' toolbox by providing a more efficient, and less error-prone, mechanism for enriching a biomedical ontology than that obtained by a manual treatment.

Results: We present OPPL-Galaxy, a wrapper for using OPPL within Galaxy. The functionality delivered by OPPL (i.e. automated ontology manipulation) can be combined with the tools and workflows devised within the Galaxy framework, resulting in an enhancement of OPPL. Use cases are provided in order to demonstrate OPPL-Galaxy's capability for enriching, modifying and querying biomedical ontologies.

Conclusions: Coupling OPPL-Galaxy with other bioinformatics tools of the Galaxy framework results in a system that is more than the sum of its parts. OPPL-Galaxy opens a new dimension of analyses and exploitation of biomedical ontologies, including automated reasoning, paving the way towards advanced biological data analyses.

No MeSH data available.