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MicroGMT: A Mutation Tracker for SARS-CoV-2 and Other Microbial Genome Sequences
With the continued spread of SARS-CoV-2 virus around the world, researchers often need to quickly identify novel mutations in newly sequenced SARS-CoV-2 genomes for studying the molecular evolution and epidemiology of the virus. We have developed a Python package, MicroGMT, which takes either raw se...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7330013/ https://www.ncbi.nlm.nih.gov/pubmed/32670259 http://dx.doi.org/10.3389/fmicb.2020.01502 |
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author | Xing, Yue Li, Xiao Gao, Xiang Dong, Qunfeng |
author_facet | Xing, Yue Li, Xiao Gao, Xiang Dong, Qunfeng |
author_sort | Xing, Yue |
collection | PubMed |
description | With the continued spread of SARS-CoV-2 virus around the world, researchers often need to quickly identify novel mutations in newly sequenced SARS-CoV-2 genomes for studying the molecular evolution and epidemiology of the virus. We have developed a Python package, MicroGMT, which takes either raw sequence reads or assembled genome sequences as input and compares against database sequences to identify and characterize indels and point mutations. Although our default setting is optimized for SARS-CoV-2 virus, the package can be also applied to any other microbial genomes. The software is freely available at Github URL https://github.com/qunfengdong/MicroGMT. |
format | Online Article Text |
id | pubmed-7330013 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73300132020-07-14 MicroGMT: A Mutation Tracker for SARS-CoV-2 and Other Microbial Genome Sequences Xing, Yue Li, Xiao Gao, Xiang Dong, Qunfeng Front Microbiol Microbiology With the continued spread of SARS-CoV-2 virus around the world, researchers often need to quickly identify novel mutations in newly sequenced SARS-CoV-2 genomes for studying the molecular evolution and epidemiology of the virus. We have developed a Python package, MicroGMT, which takes either raw sequence reads or assembled genome sequences as input and compares against database sequences to identify and characterize indels and point mutations. Although our default setting is optimized for SARS-CoV-2 virus, the package can be also applied to any other microbial genomes. The software is freely available at Github URL https://github.com/qunfengdong/MicroGMT. Frontiers Media S.A. 2020-06-25 /pmc/articles/PMC7330013/ /pubmed/32670259 http://dx.doi.org/10.3389/fmicb.2020.01502 Text en Copyright © 2020 Xing, Li, Gao and Dong. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Microbiology Xing, Yue Li, Xiao Gao, Xiang Dong, Qunfeng MicroGMT: A Mutation Tracker for SARS-CoV-2 and Other Microbial Genome Sequences |
title | MicroGMT: A Mutation Tracker for SARS-CoV-2 and Other Microbial Genome Sequences |
title_full | MicroGMT: A Mutation Tracker for SARS-CoV-2 and Other Microbial Genome Sequences |
title_fullStr | MicroGMT: A Mutation Tracker for SARS-CoV-2 and Other Microbial Genome Sequences |
title_full_unstemmed | MicroGMT: A Mutation Tracker for SARS-CoV-2 and Other Microbial Genome Sequences |
title_short | MicroGMT: A Mutation Tracker for SARS-CoV-2 and Other Microbial Genome Sequences |
title_sort | microgmt: a mutation tracker for sars-cov-2 and other microbial genome sequences |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7330013/ https://www.ncbi.nlm.nih.gov/pubmed/32670259 http://dx.doi.org/10.3389/fmicb.2020.01502 |
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