AMRomics: a scalable workflow to analyze large microbial genome collections
Whole genome analysis for microbial genomics is critical to studying and monitoring antimicrobial resistance strains. The exponential growth of microbial sequencing data necessitates a fast and scalable computational pipeline to generate the desired outputs in a timely and cost-effective manner. Rec...
| Main Authors: | , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
BioMed Central
2024
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| _version_ | 1826313583620784128 |
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| author | Le, DQ Nguyen, TT Nguyen, CH Ho, TH Vo, NS Nguyen, T Nguyen, HA Vinh, LS Dang, TH Cao, MD Nguyen, SH |
| author_facet | Le, DQ Nguyen, TT Nguyen, CH Ho, TH Vo, NS Nguyen, T Nguyen, HA Vinh, LS Dang, TH Cao, MD Nguyen, SH |
| author_sort | Le, DQ |
| collection | OXFORD |
| description | Whole genome analysis for microbial genomics is critical to studying and monitoring antimicrobial resistance strains. The exponential growth of microbial sequencing data necessitates a fast and scalable computational pipeline to generate the desired outputs in a timely and cost-effective manner. Recent methods have been implemented to integrate individual genomes into large collections of specific bacterial populations and are widely employed for systematic genomic surveillance. However, they do not scale well when the population expands and turnaround time remains the main issue for this type of analysis. Here, we introduce AMRomics, an optimized microbial genomics pipeline that can work efficiently with big datasets. We use different bacterial data collections to compare AMRomics against competitive tools and show that our pipeline can generate similar results of interest but with better performance. The software is open source and is publicly available at https://github.com/amromics/amromics under an MIT license. |
| first_indexed | 2024-09-25T04:17:16Z |
| format | Journal article |
| id | oxford-uuid:7a150ca0-cdf6-4093-bb13-5ebe9efdf616 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-09-25T04:17:16Z |
| publishDate | 2024 |
| publisher | BioMed Central |
| record_format | dspace |
| spelling | oxford-uuid:7a150ca0-cdf6-4093-bb13-5ebe9efdf6162024-07-22T19:38:41ZAMRomics: a scalable workflow to analyze large microbial genome collectionsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:7a150ca0-cdf6-4093-bb13-5ebe9efdf616EnglishJisc Publications RouterBioMed Central2024Le, DQNguyen, TTNguyen, CHHo, THVo, NSNguyen, TNguyen, HAVinh, LSDang, THCao, MDNguyen, SHWhole genome analysis for microbial genomics is critical to studying and monitoring antimicrobial resistance strains. The exponential growth of microbial sequencing data necessitates a fast and scalable computational pipeline to generate the desired outputs in a timely and cost-effective manner. Recent methods have been implemented to integrate individual genomes into large collections of specific bacterial populations and are widely employed for systematic genomic surveillance. However, they do not scale well when the population expands and turnaround time remains the main issue for this type of analysis. Here, we introduce AMRomics, an optimized microbial genomics pipeline that can work efficiently with big datasets. We use different bacterial data collections to compare AMRomics against competitive tools and show that our pipeline can generate similar results of interest but with better performance. The software is open source and is publicly available at https://github.com/amromics/amromics under an MIT license. |
| spellingShingle | Le, DQ Nguyen, TT Nguyen, CH Ho, TH Vo, NS Nguyen, T Nguyen, HA Vinh, LS Dang, TH Cao, MD Nguyen, SH AMRomics: a scalable workflow to analyze large microbial genome collections |
| title | AMRomics: a scalable workflow to analyze large microbial genome collections |
| title_full | AMRomics: a scalable workflow to analyze large microbial genome collections |
| title_fullStr | AMRomics: a scalable workflow to analyze large microbial genome collections |
| title_full_unstemmed | AMRomics: a scalable workflow to analyze large microbial genome collections |
| title_short | AMRomics: a scalable workflow to analyze large microbial genome collections |
| title_sort | amromics a scalable workflow to analyze large microbial genome collections |
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