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Swarm: A federated cloud framework for large-scale variant analysis.

Authors :
Bahmani A
Ferriter K
Krishnan V
Alavi A
Alavi A
Tsao PS
Snyder MP
Pan C
Source :
PLoS computational biology [PLoS Comput Biol] 2021 May 12; Vol. 17 (5), pp. e1008977. Date of Electronic Publication: 2021 May 12 (Print Publication: 2021).
Publication Year :
2021

Abstract

Genomic data analysis across multiple cloud platforms is an ongoing challenge, especially when large amounts of data are involved. Here, we present Swarm, a framework for federated computation that promotes minimal data motion and facilitates crosstalk between genomic datasets stored on various cloud platforms. We demonstrate its utility via common inquiries of genomic variants across BigQuery in the Google Cloud Platform (GCP), Athena in the Amazon Web Services (AWS), Apache Presto and MySQL. Compared to single-cloud platforms, the Swarm framework significantly reduced computational costs, run-time delays and risks of security breach and privacy violation.<br />Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: MPS is the Cofounder and SAB member of Personalis, Mirvie, SensOmics, Qbio, January, Oralome, Filtricine, Protos; SAB of Genapsys, Jupiter.

Details

Language :
English
ISSN :
1553-7358
Volume :
17
Issue :
5
Database :
MEDLINE
Journal :
PLoS computational biology
Publication Type :
Academic Journal
Accession number :
33979321
Full Text :
https://doi.org/10.1371/journal.pcbi.1008977