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SNIT: SNP identification for strain typing

With ever-increasing numbers of microbial genomes being sequenced, efficient tools are needed to perform strain-level identification of any newly sequenced genome. Here, we present the SNP identification for strain typing (SNIT) pipeline, a fast and accurate software system that compares a newly seq...

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Detalles Bibliográficos
Autores principales: Vijaya Satya, Ravi, Zavaljevski, Nela, Reifman, Jaques
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3182885/
https://www.ncbi.nlm.nih.gov/pubmed/21902825
http://dx.doi.org/10.1186/1751-0473-6-14
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author Vijaya Satya, Ravi
Zavaljevski, Nela
Reifman, Jaques
author_facet Vijaya Satya, Ravi
Zavaljevski, Nela
Reifman, Jaques
author_sort Vijaya Satya, Ravi
collection PubMed
description With ever-increasing numbers of microbial genomes being sequenced, efficient tools are needed to perform strain-level identification of any newly sequenced genome. Here, we present the SNP identification for strain typing (SNIT) pipeline, a fast and accurate software system that compares a newly sequenced bacterial genome with other genomes of the same species to identify single nucleotide polymorphisms (SNPs) and small insertions/deletions (indels). Based on this information, the pipeline analyzes the polymorphic loci present in all input genomes to identify the genome that has the fewest differences with the newly sequenced genome. Similarly, for each of the other genomes, SNIT identifies the input genome with the fewest differences. Results from five bacterial species show that the SNIT pipeline identifies the correct closest neighbor with 75% to 100% accuracy. The SNIT pipeline is available for download at http://www.bhsai.org/snit.html
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spelling pubmed-31828852011-09-30 SNIT: SNP identification for strain typing Vijaya Satya, Ravi Zavaljevski, Nela Reifman, Jaques Source Code Biol Med Software Review With ever-increasing numbers of microbial genomes being sequenced, efficient tools are needed to perform strain-level identification of any newly sequenced genome. Here, we present the SNP identification for strain typing (SNIT) pipeline, a fast and accurate software system that compares a newly sequenced bacterial genome with other genomes of the same species to identify single nucleotide polymorphisms (SNPs) and small insertions/deletions (indels). Based on this information, the pipeline analyzes the polymorphic loci present in all input genomes to identify the genome that has the fewest differences with the newly sequenced genome. Similarly, for each of the other genomes, SNIT identifies the input genome with the fewest differences. Results from five bacterial species show that the SNIT pipeline identifies the correct closest neighbor with 75% to 100% accuracy. The SNIT pipeline is available for download at http://www.bhsai.org/snit.html BioMed Central 2011-09-08 /pmc/articles/PMC3182885/ /pubmed/21902825 http://dx.doi.org/10.1186/1751-0473-6-14 Text en Copyright ©2011 Satya et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software Review
Vijaya Satya, Ravi
Zavaljevski, Nela
Reifman, Jaques
SNIT: SNP identification for strain typing
title SNIT: SNP identification for strain typing
title_full SNIT: SNP identification for strain typing
title_fullStr SNIT: SNP identification for strain typing
title_full_unstemmed SNIT: SNP identification for strain typing
title_short SNIT: SNP identification for strain typing
title_sort snit: snp identification for strain typing
topic Software Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3182885/
https://www.ncbi.nlm.nih.gov/pubmed/21902825
http://dx.doi.org/10.1186/1751-0473-6-14
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