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

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 clou...

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Detalles Bibliográficos
Autores principales: Bahmani, Amir, Ferriter, Kyle, Krishnan, Vandhana, Alavi, Arash, Alavi, Amir, Tsao, Philip S., Snyder, Michael P., Pan, Cuiping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8143397/
https://www.ncbi.nlm.nih.gov/pubmed/33979321
http://dx.doi.org/10.1371/journal.pcbi.1008977
Descripción
Sumario: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.

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