Yang-Turner, Fan, Volk, Denis, Fowler, Philip, Swann, Jeremy, Bull, Matthew, Hoosdally, Sarah, Connor, Thomas, Peto, Tim and Crook, Derrick 2019. Scalable pathogen pipeline platform (SP^3): enabling unified genomic data analysis with elastic cloud computing. Presented at: IEEE 12th International Conference on Cloud Computing (CLOUD), Milan, Italy, 8-13 Jul 2019. Proceedings of IEEE 12th International Conference on Cloud Computing (CLOUD). IEEE, pp. 478-480. 10.1109/CLOUD.2019.00083 |
Abstract
Pathogen genomic data analysis can be extremely bespoke and diverse. This paper presents our plan and progress towards creating a Scalable Pathogen Pipeline Platform (SP 3 ) providing an efficient and unified process of collecting, analysing and comparing genomic data analysis with the benefit of elastic cloud computing. SP 3 enables container-centric bioinformatic workflows run on personal computers, High-performance computing (HPC) clusters and cloud platforms. We have deployed and tested SP 3 on local HPC, Google Cloud Platform (GCP), Microsoft Azure and OpenStack Platforms. SP 3 allows users to fetch genomic sequencing data from European Nucleotide Archive (ENA) and conduct analysis with open-source bioinformatic pipelines. We believe SP 3 will promote common standards around pathogen genomic data quality, data processing and data analysis, helping answer the challenges of tools divergence and leveraging a pool of public genomic data repository and cloud resources.
Item Type: | Conference or Workshop Item (Paper) |
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Date Type: | Published Online |
Status: | Published |
Schools: | Biosciences |
Publisher: | IEEE |
Last Modified: | 31 Jan 2020 03:36 |
URI: | https://orca.cardiff.ac.uk/id/eprint/125841 |
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