Abstract
Next Generation Sequencing (NGS) allows sequencing of a human genome within hours, enabling large scale applications such as sequencing the genome of each patient in a clinical study. Each individual human genome has about 3.5 Million genetic differences to the so called reference genome, the consensus genome of a healthy human. These differences, called variants, determine individual phenotypes, and certain variants are known to indicate disease predispositions. Finding associations from variant patterns and affected genes to these diseases requires combined analysis of variants from multiple individuals and hence, efficient solutions for accessing and filtering the variant data. We present Variant-DB, our in-house database solution that allows such efficient access to millions of variants from hundreds to thousands of individuals. Variant-DB stores individual variant genotypes and annotations. It features a REST-API and a web-based front-end for filtering variants based on annotations, individuals, families and studies. We explain Variant-DB and its front-end and demonstrate how the Variant-DB API can be included in data integration workflows.
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Acknowledgments
We would like to thank Dheeraj R. Bobbili for the help with the PPMI data, Marek Ostaszewski and Piotr Gawron for their support with the Minerva API, Venkata Satagopam, Wei Gu, Sascha Herzinger for their help with tranSMART. JK and PM were supported by the FNR NCER-PD grant. PM was supported by the JPND Courage-PD project. Data used in the preparation of this article were obtained from the Parkinson’s Progression Markers Initiative (PPMI) database (www.ppmi-info.org/data) For up-to-date information on the study, visit www.ppmi-info.org. PPMI - a public-private partnership - is funded by the Michael J. Fox Foundation for Parkinson’s Research and funding partners, including Abbvie, Avid, Biogen, Bristol-Myers Squibb, Covance, GE Healthcare, Genentech, GlaxoSmithKline, Lilly, Lundbeek, Merck, Meso Scale Discovery, Pfizer, Piramal, Roche, Servier, Teva, UCB, and Golub Capital.
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Kutzera, J., May, P. (2017). Variant-DB: A Tool for Efficiently Exploring Millions of Human Genetic Variants and Their Annotations. In: Da Silveira, M., Pruski, C., Schneider, R. (eds) Data Integration in the Life Sciences. DILS 2017. Lecture Notes in Computer Science(), vol 10649. Springer, Cham. https://doi.org/10.1007/978-3-319-69751-2_3
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DOI: https://doi.org/10.1007/978-3-319-69751-2_3
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