eXframe: reusable framework for storage, analysis and visualization of genomics experiments

<p>Abstract</p> <p>Background</p> <p>Genome-wide experiments are routinely conducted to measure gene expression, DNA-protein interactions and epigenetic status. Structured metadata for these experiments is imperative for a complete understanding of experimental conditions, to enable consistent data processing and to allow retrieval, comparison, and integration of experimental results. Even though several repositories have been developed for genomics data, only a few provide annotation of samples and assays using controlled vocabularies. Moreover, many of them are tailored for a single type of technology or measurement and do not support the integration of multiple data types.</p> <p>Results</p> <p>We have developed eXframe - a reusable web-based framework for genomics experiments that provides 1) the ability to publish structured data compliant with accepted standards 2) support for multiple data types including microarrays and next generation sequencing 3) query, analysis and visualization integration tools (enabled by consistent processing of the raw data and annotation of samples) and is available as open-source software. We present two case studies where this software is currently being used to build repositories of genomics experiments - one contains data from hematopoietic stem cells and another from Parkinson's disease patients.</p> <p>Conclusion</p> <p>The web-based framework eXframe offers structured annotation of experiments as well as uniform processing and storage of molecular data from microarray and next generation sequencing platforms. The framework allows users to query and integrate information across species, technologies, measurement types and experimental conditions. Our framework is reusable and freely modifiable - other groups or institutions can deploy their own custom web-based repositories based on this software. It is interoperable with the most important data formats in this domain. We hope that other groups will not only use eXframe, but also contribute their own useful modifications.</p

Selected papers from the 16th Annual Bio-Ontologies Special Interest Group Meeting

Copyright @ 2014 Soldatova et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Over the 16 years, the Bio-Ontologies SIG at ISMB has provided a forum for vibrant discussions of the latest and most innovative advances in the research area of bio-ontologies, its applications to biomedicine and more generally in the organisation, sharing and re-use of knowledge in biomedicine and the life sciences. The six papers selected for this supplement span a wide range of topics including: ontology-based data integration, ontology-based annotation of scientific literature, ontology and data model development, representation of scientific results and gene candidate prediction