Explorations into the Provenance of High Throughput Biomedical Experiments

McCusker, James P.; McGuinness, Deborah L.

doi:10.1007/978-3-642-17819-1_15

Cited by 6 publications

(5 citation statements)

References 20 publications

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“…McCusker et al [ 44 ] worked on representing the provenance of microarray experiments by converting the MicroArray Gene Expression Tabular (MAGE-Tab) format [ 45 ] into RDF. Mapping MAGE files into the Open Provenance Model (OPM) and the Proof Markup Language (PML), they demonstrated the feasibility by converting one experiment from the ArrayExpress database [ 46 ] as a step towards a vision of a uniform representation of provenance in a translational research pipeline.…”

Section: Discussionmentioning

confidence: 99%

linkedISA: semantic representation of ISA-Tab experimental metadata

et al. 2014

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BackgroundReporting and sharing experimental metadata- such as the experimental design, characteristics of the samples, and procedures applied, along with the analysis results, in a standardised manner ensures that datasets are comprehensible and, in principle, reproducible, comparable and reusable. Furthermore, sharing datasets in formats designed for consumption by humans and machines will also maximize their use. The Investigation/Study/Assay (ISA) open source metadata tracking framework facilitates standards-compliant collection, curation, visualization, storage and sharing of datasets, leveraging on other platforms to enable analysis and publication. The ISA software suite includes several components used in increasingly diverse set of life science and biomedical domains; it is underpinned by a general-purpose format, ISA-Tab, and conversions exist into formats required by public repositories. While ISA-Tab works well mainly as a human readable format, we have also implemented a linked data approach to semantically define the ISA-Tab syntax.ResultsWe present a semantic web representation of the ISA-Tab syntax that complements ISA-Tab's syntactic interoperability with semantic interoperability. We introduce the linkedISA conversion tool from ISA-Tab to the Resource Description Framework (RDF), supporting mappings from the ISA syntax to multiple community-defined, open ontologies and capitalising on user-provided ontology annotations in the experimental metadata. We describe insights of the implementation and how annotations can be expanded driven by the metadata. We applied the conversion tool as part of Bio-GraphIIn, a web-based application supporting integration of the semantically-rich experimental descriptions. Designed in a user-friendly manner, the Bio-GraphIIn interface hides most of the complexities to the users, exposing a familiar tabular view of the experimental description to allow seamless interaction with the RDF representation, and visualising descriptors to drive the query over the semantic representation of the experimental design. In addition, we defined queries over the linkedISA RDF representation and demonstrated its use over the linkedISA conversion of datasets from Nature' Scientific Data online publication.ConclusionsOur linked data approach has allowed us to: 1) make the ISA-Tab semantics explicit and machine-processable, 2) exploit the existing ontology-based annotations in the ISA-Tab experimental descriptions, 3) augment the ISA-Tab syntax with new descriptive elements, 4) visualise and query elements related to the experimental design. Reasoning over ISA-Tab metadata and associated data will facilitate data integration and knowledge discovery.

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Section: Discussionmentioning

confidence: 99%

linkedISA: semantic representation of ISA-Tab experimental metadata

et al. 2014

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“…Moreover, since the biomedical experimental workflows are a particular case of more general provenance models ( McCusker and McGuinness, 2010 ), the library has a potential to be useful in other application domains.…”

Section: Use Cases and Discussionmentioning

confidence: 99%

graph2tab, a library to convert experimental workflow graphs into tabular formats

et al. 2012

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Motivations: Spreadsheet-like tabular formats are ever more popular in the biomedical field as a mean for experimental reporting. The problem of converting the graph of an experimental workflow into a table-based representation occurs in many such formats and is not easy to solve.Results: We describe graph2tab, a library that implements methods to realise such a conversion in a size-optimised way. Our solution is generic and can be adapted to specific cases of data exporters or data converters that need to be implemented.Availability and Implementation: The library source code and documentation are available at http://github.com/ISA-tools/graph2tab.Contact: brandizi@ebi.ac.uk.Supplementary Information: A supplementary document describes the theoretical and technical details about the library implementation.

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“…The flexibility of the Corvus object model will allow us to incorporate quantitative Omics data from a variety of modalities. In the future, this could include cancer data from caArray or caIntegrator or data obtained directly from ArrayExpress using MAGETab2RDF [ 39 ]. Essentially, Corvus functions as a contextualized observation repository and we intend to incorporate information from other contexts including clinical data and generic provenance data.…”

Section: Discussionmentioning

confidence: 99%

A semantic web framework to integrate cancer omics data with biological knowledge

et al. 2012

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BackgroundThe RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge.ResultsFor this paper, we merged semantic models containing genomic, transcriptomic and epigenomic data from melanoma samples with two semantic models of functional data - one containing Gene Ontology (GO) data, the other, regulatory networks constructed from transcription factor binding information. These two semantic models were created in an ad hoc manner but support a common interface for integration with the quantitative semantic models. Such combined semantic models allow us to pose significant translational medicine questions. Here, we study the interplay between a cell's molecular state and its response to anti-cancer therapy by exploring the resistance of cancer cells to Decitabine, a demethylating agent.ConclusionsWe were able to generate a testable hypothesis to explain how Decitabine fights cancer - namely, that it targets apoptosis-related gene promoters predominantly in Decitabine-sensitive cell lines, thus conveying its cytotoxic effect by activating the apoptosis pathway. Our research provides a framework whereby similar hypotheses can be developed easily.

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Explorations into the Provenance of High Throughput Biomedical Experiments

Cited by 6 publications

References 20 publications

linkedISA: semantic representation of ISA-Tab experimental metadata

linkedISA: semantic representation of ISA-Tab experimental metadata

graph2tab, a library to convert experimental workflow graphs into tabular formats

A semantic web framework to integrate cancer omics data with biological knowledge

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