Grisha Weintraub
ABSTRACT
In recent years there is huge influx of genomic data and a growing need for its analysis, yet existing genomic databases do not allow easy accessibility. We developed a pipeline that continuously pre-processes raw human genetic data. The data is then stored in a cloud data lake and can be accessed via a simple and intuitive web service and API.
- Adam Ameur, Ignas Bunikis, Stefan Enroth, and Ulf Gyllensten. 2014. CanvasDB: a local database infrastructure for analysis of targeted-and whole genome re-sequencing projects. Database 2014 (2014).Google Scholar
- Noam Hadar, Grisha Weintraub, Ehud Gudes, Shlomi Dolev, and Ohad Birk. in press. GeniePool: Genomic Database With Corresponding Annotated Samples Based On a Cloud Data Lake Architecture. Database (in press).Google Scholar
- Rasko Leinonen, Hideaki Sugawara, Martin Shumway, and International Nucleotide Sequence Database Collaboration. 2010. The sequence read archive. Nucleic acids research 39, suppl_1 (2010), D19--D21.Google Scholar
- Grisha Weintraub, Ehud Gudes, and Shlomi Dolev. 2021. Needle in a haystack queries in cloud data lakes. In EDBT/ICDT Workshops.Google Scholar
Index Terms
- Analyzing large-scale genomic data with cloud data lakes
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