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PGAP: pan-genomes analysis pipeline

Summary: With the rapid development of DNA sequencing technology, increasing bacteria genome data enable the biologists to dig the evolutionary and genetic information of prokaryotic species from pan-genome sight. Therefore, the high-efficiency pipelines for pan-genome analysis are mostly needed. We...

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Detalles Bibliográficos
Autores principales: Zhao, Yongbing, Wu, Jiayan, Yang, Junhui, Sun, Shixiang, Xiao, Jingfa, Yu, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3268234/
https://www.ncbi.nlm.nih.gov/pubmed/22130594
http://dx.doi.org/10.1093/bioinformatics/btr655
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author Zhao, Yongbing
Wu, Jiayan
Yang, Junhui
Sun, Shixiang
Xiao, Jingfa
Yu, Jun
author_facet Zhao, Yongbing
Wu, Jiayan
Yang, Junhui
Sun, Shixiang
Xiao, Jingfa
Yu, Jun
author_sort Zhao, Yongbing
collection PubMed
description Summary: With the rapid development of DNA sequencing technology, increasing bacteria genome data enable the biologists to dig the evolutionary and genetic information of prokaryotic species from pan-genome sight. Therefore, the high-efficiency pipelines for pan-genome analysis are mostly needed. We have developed a new pan-genome analysis pipeline (PGAP), which can perform five analytic functions with only one command, including cluster analysis of functional genes, pan-genome profile analysis, genetic variation analysis of functional genes, species evolution analysis and function enrichment analysis of gene clusters. PGAP's performance has been evaluated on 11 Streptococcus pyogenes strains. Availability:PGAP is developed with Perl script on the Linux Platform and the package is freely available from http://pgap.sf.net. Contact: junyu@big.ac.cn; xiaojingfa@big.ac.cn Supplementary information: Supplementary data are available at Bioinformatics online.
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spelling pubmed-32682342012-01-30 PGAP: pan-genomes analysis pipeline Zhao, Yongbing Wu, Jiayan Yang, Junhui Sun, Shixiang Xiao, Jingfa Yu, Jun Bioinformatics Applications Note Summary: With the rapid development of DNA sequencing technology, increasing bacteria genome data enable the biologists to dig the evolutionary and genetic information of prokaryotic species from pan-genome sight. Therefore, the high-efficiency pipelines for pan-genome analysis are mostly needed. We have developed a new pan-genome analysis pipeline (PGAP), which can perform five analytic functions with only one command, including cluster analysis of functional genes, pan-genome profile analysis, genetic variation analysis of functional genes, species evolution analysis and function enrichment analysis of gene clusters. PGAP's performance has been evaluated on 11 Streptococcus pyogenes strains. Availability:PGAP is developed with Perl script on the Linux Platform and the package is freely available from http://pgap.sf.net. Contact: junyu@big.ac.cn; xiaojingfa@big.ac.cn Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2012-02-01 2011-11-29 /pmc/articles/PMC3268234/ /pubmed/22130594 http://dx.doi.org/10.1093/bioinformatics/btr655 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Zhao, Yongbing
Wu, Jiayan
Yang, Junhui
Sun, Shixiang
Xiao, Jingfa
Yu, Jun
PGAP: pan-genomes analysis pipeline
title PGAP: pan-genomes analysis pipeline
title_full PGAP: pan-genomes analysis pipeline
title_fullStr PGAP: pan-genomes analysis pipeline
title_full_unstemmed PGAP: pan-genomes analysis pipeline
title_short PGAP: pan-genomes analysis pipeline
title_sort pgap: pan-genomes analysis pipeline
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3268234/
https://www.ncbi.nlm.nih.gov/pubmed/22130594
http://dx.doi.org/10.1093/bioinformatics/btr655
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