Demonstration of GenoMetric Query Language
Authors: 
Stefano Ceri, 
Arif Canakoglu, Andrea Gulino, Abdulrahman Kaitoua, Marco Masseroli, Luca Nanni, Pietro PinoliAuthors Info & Claims
Pages 1887 - 1890
Abstract
In the last ten years, genomic computing has made gigantic steps due to Next Generation Sequencing (NGS), a high-throughput, massively parallel technology; the cost of producing a complete human sequence dropped to 1000 US$ in 2015 and is expected to drop below 100 US$ by 2020. Several new methods have recently become available for extracting heterogeneous datasets from the genome, revealing data signals such as variations from a reference sequence, levels of expression of coding regions, or protein binding enrichments ('peaks') with their statistical or geometric properties. Huge collections of such datasets are made available by large international consortia.
In this new context, we developed GenoMetric Query Language (GMQL), a new data extraction and integration language. GMQL supports queries over thousands of heterogeneous datasets; as such, it is key to genomic data analysis. GMQL queries are executed on the cloud, after being translated and optimized; our best deployment uses Spark over Hadoop. Datasets are described by the Genomic Data Model (GDM), which provides interoperability between many data formats; GDM combines abstractions for genomic region data with the associated experimental, biological and clinical metadata.
GMQL is targeted to the bio-informatics community for facilitating data exploration and for integrating data extraction and data analysis; this demonstration highlights its usability and expressive power. We show GMQL at work from a Web-based user interface and from a language embedding (Python).
References
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W. J. Kent et al. The Human Genome Browser at UCSC, Genome Res, 12(6):996--1006 (2002).
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A. Kaitoua et al. Framework for supporting genomic operations IEEE-TC, 66(3):443--457 (2017).
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M. Masseroli et al. GenoMetric Query Language: A novel approach to large-scale genomic data management. Bioinformatics, 31(12):1881--1888 (2015).
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M. Masseroli, et al. Modeling and interoperability of heterogeneous genomic big data for integrative processing and querying. Methods, 1;111:3--11 (2016).
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Index Terms
- Demonstration of GenoMetric Query Language
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Information
Published In
October 2018
2362 pages
ISBN:9781450360142
DOI:10.1145/3269206
- General Chair:
- Alfredo Cuzzocrea,
- Program Chairs:
- James Allan,
- Norman Paton,
- Divesh Srivastava,
- Rakesh Agrawal,
- Andrei Broder,
- Mohammed Zaki,
- Selcuk Candan,
- Alexandros Labrinidis,
- Assaf Schuster,
- Haixun Wang
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Published: 17 October 2018
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CIKM '18: The 27th ACM International Conference on Information and Knowledge Management
October 22 - 26, 2018
Torino, Italy
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