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NxRepair: error correction in de novo sequence assembly using Nextera mate pairs

Scaffolding errors and incorrect repeat disambiguation during de novo assembly can result in large scale misassemblies in draft genomes. Nextera mate pair sequencing data provide additional information to resolve assembly ambiguities during scaffolding. Here, we introduce NxRepair, an open source to...

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Detalles Bibliográficos
Autores principales: Murphy, Rebecca R., O’Connell, Jared, Cox, Anthony J., Schulz-Trieglaff, Ole
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4458127/
https://www.ncbi.nlm.nih.gov/pubmed/26056623
http://dx.doi.org/10.7717/peerj.996
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author Murphy, Rebecca R.
O’Connell, Jared
Cox, Anthony J.
Schulz-Trieglaff, Ole
author_facet Murphy, Rebecca R.
O’Connell, Jared
Cox, Anthony J.
Schulz-Trieglaff, Ole
author_sort Murphy, Rebecca R.
collection PubMed
description Scaffolding errors and incorrect repeat disambiguation during de novo assembly can result in large scale misassemblies in draft genomes. Nextera mate pair sequencing data provide additional information to resolve assembly ambiguities during scaffolding. Here, we introduce NxRepair, an open source toolkit for error correction in de novo assemblies that uses Nextera mate pair libraries to identify and correct large-scale errors. We show that NxRepair can identify and correct large scaffolding errors, without use of a reference sequence, resulting in quantitative improvements in the assembly quality. NxRepair can be downloaded from GitHub or PyPI, the Python Package Index; a tutorial and user documentation are also available.
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spelling pubmed-44581272015-06-08 NxRepair: error correction in de novo sequence assembly using Nextera mate pairs Murphy, Rebecca R. O’Connell, Jared Cox, Anthony J. Schulz-Trieglaff, Ole PeerJ Bioinformatics Scaffolding errors and incorrect repeat disambiguation during de novo assembly can result in large scale misassemblies in draft genomes. Nextera mate pair sequencing data provide additional information to resolve assembly ambiguities during scaffolding. Here, we introduce NxRepair, an open source toolkit for error correction in de novo assemblies that uses Nextera mate pair libraries to identify and correct large-scale errors. We show that NxRepair can identify and correct large scaffolding errors, without use of a reference sequence, resulting in quantitative improvements in the assembly quality. NxRepair can be downloaded from GitHub or PyPI, the Python Package Index; a tutorial and user documentation are also available. PeerJ Inc. 2015-06-02 /pmc/articles/PMC4458127/ /pubmed/26056623 http://dx.doi.org/10.7717/peerj.996 Text en © 2015 Murphy et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Murphy, Rebecca R.
O’Connell, Jared
Cox, Anthony J.
Schulz-Trieglaff, Ole
NxRepair: error correction in de novo sequence assembly using Nextera mate pairs
title NxRepair: error correction in de novo sequence assembly using Nextera mate pairs
title_full NxRepair: error correction in de novo sequence assembly using Nextera mate pairs
title_fullStr NxRepair: error correction in de novo sequence assembly using Nextera mate pairs
title_full_unstemmed NxRepair: error correction in de novo sequence assembly using Nextera mate pairs
title_short NxRepair: error correction in de novo sequence assembly using Nextera mate pairs
title_sort nxrepair: error correction in de novo sequence assembly using nextera mate pairs
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4458127/
https://www.ncbi.nlm.nih.gov/pubmed/26056623
http://dx.doi.org/10.7717/peerj.996
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