Journal article
NanoSPC: a scalable, portable, cloud compatible viral nanopore metagenomic data processing pipeline
- Abstract:
- Metagenomic sequencing combined with Oxford Nanopore Technology has the potential to become a point-of-care test for infectious disease in public health and clinical settings, providing rapid diagnosis of infection, guiding individual patient management and treatment strategies, and informing infection prevention and control practices. However, publicly available, streamlined, and reproducible pipelines for analyzing Nanopore metagenomic sequencing data are still lacking. Here we introduce NanoSPC, a scalable, portable and cloud compatible pipeline for analyzing Nanopore sequencing data. NanoSPC can identify potentially pathogenic viruses and bacteria simultaneously to provide comprehensive characterization of individual samples. The pipeline can also detect single nucleotide variants and assemble high quality complete consensus genome sequences, permitting high-resolution inference of transmission. We implement NanoSPC using Nextflow manager within Docker images to allow reproducibility and portability of the analysis. Moreover, we deploy NanoSPC to our scalable pathogen pipeline platform, enabling elastic computing for high throughput Nanopore data on HPC cluster as well as multiple cloud platforms, such as Google Cloud, Amazon Elastic Computing Cloud, Microsoft Azure and OpenStack. Users could either access our web interface (https://nanospc.mmmoxford.uk) to run cloud-based analysis, monitor process, and visualize results, as well as download Docker images and run command line to analyse data locally.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, 982.2KB, Terms of use)
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- Publisher copy:
- 10.1093/nar/gkaa413
Authors
- Publisher:
- Oxford University Press
- Journal:
- Nucleic Acids Research More from this journal
- Volume:
- 48
- Issue:
- W1
- Pages:
- W366–W371
- Publication date:
- 2020-05-22
- Acceptance date:
- 2020-05-11
- DOI:
- EISSN:
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1362-4962
- ISSN:
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0305-1048
- Pmid:
-
32442274
- Language:
-
English
- Keywords:
- Pubs id:
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1106295
- Local pid:
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pubs:1106295
- Deposit date:
-
2020-06-15
Terms of use
- Copyright holder:
- Yifei Xu et al.
- Copyright date:
- 2020
- Rights statement:
- © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
- Licence:
- CC Attribution (CC BY)
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