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CISA: Contig Integrator for Sequence Assembly of Bacterial Genomes

A plethora of algorithmic assemblers have been proposed for the de novo assembly of genomes, however, no individual assembler guarantees the optimal assembly for diverse species. Optimizing various parameters in an assembler is often performed in order to generate the most optimal assembly. However,...

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Detalles Bibliográficos
Autores principales: Lin, Shin-Hung, Liao, Yu-Chieh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3610655/
https://www.ncbi.nlm.nih.gov/pubmed/23556006
http://dx.doi.org/10.1371/journal.pone.0060843
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author Lin, Shin-Hung
Liao, Yu-Chieh
author_facet Lin, Shin-Hung
Liao, Yu-Chieh
author_sort Lin, Shin-Hung
collection PubMed
description A plethora of algorithmic assemblers have been proposed for the de novo assembly of genomes, however, no individual assembler guarantees the optimal assembly for diverse species. Optimizing various parameters in an assembler is often performed in order to generate the most optimal assembly. However, few efforts have been pursued to take advantage of multiple assemblies to yield an assembly of high accuracy. In this study, we employ various state-of-the-art assemblers to generate different sets of contigs for bacterial genomes. A tool, named CISA, has been developed to integrate the assemblies into a hybrid set of contigs, resulting in assemblies of superior contiguity and accuracy, compared with the assemblies generated by the state-of-the-art assemblers and the hybrid assemblies merged by existing tools. This tool is implemented in Python and requires MUMmer and BLAST+ to be installed on the local machine. The source code of CISA and examples of its use are available at http://sb.nhri.org.tw/CISA/.
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spelling pubmed-36106552013-04-03 CISA: Contig Integrator for Sequence Assembly of Bacterial Genomes Lin, Shin-Hung Liao, Yu-Chieh PLoS One Research Article A plethora of algorithmic assemblers have been proposed for the de novo assembly of genomes, however, no individual assembler guarantees the optimal assembly for diverse species. Optimizing various parameters in an assembler is often performed in order to generate the most optimal assembly. However, few efforts have been pursued to take advantage of multiple assemblies to yield an assembly of high accuracy. In this study, we employ various state-of-the-art assemblers to generate different sets of contigs for bacterial genomes. A tool, named CISA, has been developed to integrate the assemblies into a hybrid set of contigs, resulting in assemblies of superior contiguity and accuracy, compared with the assemblies generated by the state-of-the-art assemblers and the hybrid assemblies merged by existing tools. This tool is implemented in Python and requires MUMmer and BLAST+ to be installed on the local machine. The source code of CISA and examples of its use are available at http://sb.nhri.org.tw/CISA/. Public Library of Science 2013-03-28 /pmc/articles/PMC3610655/ /pubmed/23556006 http://dx.doi.org/10.1371/journal.pone.0060843 Text en © 2013 Lin, Liao http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Lin, Shin-Hung
Liao, Yu-Chieh
CISA: Contig Integrator for Sequence Assembly of Bacterial Genomes
title CISA: Contig Integrator for Sequence Assembly of Bacterial Genomes
title_full CISA: Contig Integrator for Sequence Assembly of Bacterial Genomes
title_fullStr CISA: Contig Integrator for Sequence Assembly of Bacterial Genomes
title_full_unstemmed CISA: Contig Integrator for Sequence Assembly of Bacterial Genomes
title_short CISA: Contig Integrator for Sequence Assembly of Bacterial Genomes
title_sort cisa: contig integrator for sequence assembly of bacterial genomes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3610655/
https://www.ncbi.nlm.nih.gov/pubmed/23556006
http://dx.doi.org/10.1371/journal.pone.0060843
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