Exposing the cancer genome atlas as a SPARQL endpoint

Abstract

The Cancer Genome Atlas (TCGA) is a multidisciplinary, multi-institutional effort to characterize several types of cancer. Datasets from biomedical domains such as TCGA present a particularly challenging task for those interested in dynamically aggregating its results because the data sources are typically both heterogeneous and distributed. The Linked Data best practices offer a solution to integrate and discover data with those characteristics, namely through exposure of data as Web services supporting SPARQL, the Resource Description Framework query language. Most SPARQL endpoints, however, cannot easily be queried by data experts. Furthermore, exposing experimental data as SPARQL endpoints remains a challenging task because, in most cases, data must first be converted to Resource Description Framework triples. In line with those requirements, we have developed an infrastructure to expose clinical, demographic and molecular data elements generated by TCGA as a SPARQL endpoint by assigning elements to entities of the Simple Sloppy Semantic Database (S3DB) management model. All components of the infrastructure are available as independent Representational State Transfer (REST) Web services to encourage reusability, and a simple interface was developed to automatically assemble SPARQL queries by navigating a representation of the TCGA domain. A key feature of the proposed solution that greatly facilitates assembly of SPARQL queries is the distinction between the TCGA domain descriptors and data elements. Furthermore, the use of the S3DB management model as a mediator enables queries to both public and protected data without the need for prior submission to a single data source.

PIERO ontology for analysis of biochemical transformations: Effective implementation of reaction information in the IUBMB enzyme list

“…13 Recent years, RDF is gathering more attention in the bioinformatics community to describe various types of data, and some RDF-related tools (including SPARQL endpoints) are becoming available. [14][15][16] To date, these are still developing technologies, and many studies attempt to improve the calculation e±ciency and the usability. [17][18][19] Our SPARQL endpoint also leaves room to improve, although the continuing development of the ontology data and the related technologies would enable more complex queries with better usability in the foreseeable future.…”

Comparing Relational and Ontological Triple Stores in Healthcare Domain

“…It is used by various open source, academic research and commercial projects [43][44][45]. AllegroGraph supports Java, Python, Ruby, Perl, C#, Lisp, and Prolog interfaces, and also SPARQL, RDFS++, and Prolog reasoning.…”

QMachine: commodity supercomputing in web browsers

“…The current extent of its use is dramatically illustrated by the adoption of the RDF framework across all data services of the European Bioinformatics Institute [28]. As also illustrated by some of our work [29-31] developing SPARQL endpoints for TCGA, the volume of the server-side hosted data is not a significant obstacle to developing web applications (“web apps”) that consume those data. On the other hand, mechanisms to assemble workflows for data analysis have not yet matured as user-friendly commodities, despite the availability of excellent frameworks like Taverna [32] and SHARE [33].…”