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STing: accurate and ultrafast genomic profiling with exact sequence matches
Genome-enabled approaches to molecular epidemiology have become essential to public health agencies and the microbial research community. We developed the algorithm STing to provide turn-key solutions for molecular typing and gene detection directly from next generation sequence data of microbial pa...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7430640/ https://www.ncbi.nlm.nih.gov/pubmed/32619234 http://dx.doi.org/10.1093/nar/gkaa566 |
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author | Espitia-Navarro, Hector F Chande, Aroon T Nagar, Shashwat D Smith, Heather Jordan, I King Rishishwar, Lavanya |
author_facet | Espitia-Navarro, Hector F Chande, Aroon T Nagar, Shashwat D Smith, Heather Jordan, I King Rishishwar, Lavanya |
author_sort | Espitia-Navarro, Hector F |
collection | PubMed |
description | Genome-enabled approaches to molecular epidemiology have become essential to public health agencies and the microbial research community. We developed the algorithm STing to provide turn-key solutions for molecular typing and gene detection directly from next generation sequence data of microbial pathogens. Our implementation of STing uses an innovative k-mer search strategy that eliminates the computational overhead associated with the time-consuming steps of quality control, assembly, and alignment, required by more traditional methods. We compared STing to six of the most widely used programs for genome-based molecular typing and demonstrate its ease of use, accuracy, speed and efficiency. STing shows superior accuracy and performance for standard multilocus sequence typing schemes, along with larger genome-scale typing schemes, and it enables rapid automated detection of antimicrobial resistance and virulence factor genes. STing determines the sequence type of traditional 7-gene MLST with 100% accuracy in less than 10 seconds per isolate. We hope that the adoption of STing will help to democratize microbial genomics and thereby maximize its benefit for public health. |
format | Online Article Text |
id | pubmed-7430640 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-74306402020-08-19 STing: accurate and ultrafast genomic profiling with exact sequence matches Espitia-Navarro, Hector F Chande, Aroon T Nagar, Shashwat D Smith, Heather Jordan, I King Rishishwar, Lavanya Nucleic Acids Res Computational Biology Genome-enabled approaches to molecular epidemiology have become essential to public health agencies and the microbial research community. We developed the algorithm STing to provide turn-key solutions for molecular typing and gene detection directly from next generation sequence data of microbial pathogens. Our implementation of STing uses an innovative k-mer search strategy that eliminates the computational overhead associated with the time-consuming steps of quality control, assembly, and alignment, required by more traditional methods. We compared STing to six of the most widely used programs for genome-based molecular typing and demonstrate its ease of use, accuracy, speed and efficiency. STing shows superior accuracy and performance for standard multilocus sequence typing schemes, along with larger genome-scale typing schemes, and it enables rapid automated detection of antimicrobial resistance and virulence factor genes. STing determines the sequence type of traditional 7-gene MLST with 100% accuracy in less than 10 seconds per isolate. We hope that the adoption of STing will help to democratize microbial genomics and thereby maximize its benefit for public health. Oxford University Press 2020-07-03 /pmc/articles/PMC7430640/ /pubmed/32619234 http://dx.doi.org/10.1093/nar/gkaa566 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Computational Biology Espitia-Navarro, Hector F Chande, Aroon T Nagar, Shashwat D Smith, Heather Jordan, I King Rishishwar, Lavanya STing: accurate and ultrafast genomic profiling with exact sequence matches |
title | STing: accurate and ultrafast genomic profiling with exact sequence matches |
title_full | STing: accurate and ultrafast genomic profiling with exact sequence matches |
title_fullStr | STing: accurate and ultrafast genomic profiling with exact sequence matches |
title_full_unstemmed | STing: accurate and ultrafast genomic profiling with exact sequence matches |
title_short | STing: accurate and ultrafast genomic profiling with exact sequence matches |
title_sort | sting: accurate and ultrafast genomic profiling with exact sequence matches |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7430640/ https://www.ncbi.nlm.nih.gov/pubmed/32619234 http://dx.doi.org/10.1093/nar/gkaa566 |
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