1. BigQ: a NoSQL based framework to handle genomic variants in i2b2
- Author
-
Daniele Segagni, Matteo Gabetta, Riccardo Bellazzi, Alberto Riva, Ettore Rizzo, and Ivan Limongelli
- Subjects
i2b2 ,Databases, Factual ,Computer science ,Genomic data ,MEDLINE ,Information Storage and Retrieval ,Genomics ,NoSQL ,computer.software_genre ,Biochemistry ,Structural Biology ,Humans ,Molecular Biology ,Throughput (business) ,Applied Mathematics ,Variants ,High-Throughput Nucleotide Sequencing ,Precision medicine ,Data science ,Computer Science Applications ,Informatics ,NGS ,DNA microarray ,computer ,Software ,CouchDB - Abstract
Background Precision medicine requires the tight integration of clinical and molecular data. To this end, it is mandatory to define proper technological solutions able to manage the overwhelming amount of high throughput genomic data needed to test associations between genomic signatures and human phenotypes. The i2b2 Center (Informatics for Integrating Biology and the Bedside) has developed a widely internationally adopted framework to use existing clinical data for discovery research that can help the definition of precision medicine interventions when coupled with genetic data. i2b2 can be significantly advanced by designing efficient management solutions of Next Generation Sequencing data. Results We developed BigQ, an extension of the i2b2 framework, which integrates patient clinical phenotypes with genomic variant profiles generated by Next Generation Sequencing. A visual programming i2b2 plugin allows retrieving variants belonging to the patients in a cohort by applying filters on genomic variant annotations. We report an evaluation of the query performance of our system on more than 11 million variants, showing that the implemented solution scales linearly in terms of query time and disk space with the number of variants. Conclusions In this paper we describe a new i2b2 web service composed of an efficient and scalable document-based database that manages annotations of genomic variants and of a visual programming plug-in designed to dynamically perform queries on clinical and genetic data. The system therefore allows managing the fast growing volume of genomic variants and can be used to integrate heterogeneous genomic annotations. Electronic supplementary material The online version of this article (doi:10.1186/s12859-015-0861-0) contains supplementary material, which is available to authorized users.
- Published
- 2015