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Metassembler: merging and optimizing de novo genome assemblies

Genome assembly projects typically run multiple algorithms in an attempt to find the single best assembly, although those assemblies often have complementary, if untapped, strengths and weaknesses. We present our metassembler algorithm that merges multiple assemblies of a genome into a single superi...

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Detalles Bibliográficos
Autores principales: Wences, Alejandro Hernandez, Schatz, Michael C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4581417/
https://www.ncbi.nlm.nih.gov/pubmed/26403281
http://dx.doi.org/10.1186/s13059-015-0764-4
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author Wences, Alejandro Hernandez
Schatz, Michael C.
author_facet Wences, Alejandro Hernandez
Schatz, Michael C.
author_sort Wences, Alejandro Hernandez
collection PubMed
description Genome assembly projects typically run multiple algorithms in an attempt to find the single best assembly, although those assemblies often have complementary, if untapped, strengths and weaknesses. We present our metassembler algorithm that merges multiple assemblies of a genome into a single superior sequence. We apply it to the four genomes from the Assemblathon competitions and show it consistently and substantially improves the contiguity and quality of each assembly. We also develop guidelines for meta-assembly by systematically evaluating 120 permutations of merging the top 5 assemblies of the first Assemblathon competition. The software is open-source at http://metassembler.sourceforge.net. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-015-0764-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-45814172015-09-25 Metassembler: merging and optimizing de novo genome assemblies Wences, Alejandro Hernandez Schatz, Michael C. Genome Biol Software Genome assembly projects typically run multiple algorithms in an attempt to find the single best assembly, although those assemblies often have complementary, if untapped, strengths and weaknesses. We present our metassembler algorithm that merges multiple assemblies of a genome into a single superior sequence. We apply it to the four genomes from the Assemblathon competitions and show it consistently and substantially improves the contiguity and quality of each assembly. We also develop guidelines for meta-assembly by systematically evaluating 120 permutations of merging the top 5 assemblies of the first Assemblathon competition. The software is open-source at http://metassembler.sourceforge.net. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-015-0764-4) contains supplementary material, which is available to authorized users. BioMed Central 2015-09-24 2015 /pmc/articles/PMC4581417/ /pubmed/26403281 http://dx.doi.org/10.1186/s13059-015-0764-4 Text en © Wences and Schatz. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Wences, Alejandro Hernandez
Schatz, Michael C.
Metassembler: merging and optimizing de novo genome assemblies
title Metassembler: merging and optimizing de novo genome assemblies
title_full Metassembler: merging and optimizing de novo genome assemblies
title_fullStr Metassembler: merging and optimizing de novo genome assemblies
title_full_unstemmed Metassembler: merging and optimizing de novo genome assemblies
title_short Metassembler: merging and optimizing de novo genome assemblies
title_sort metassembler: merging and optimizing de novo genome assemblies
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4581417/
https://www.ncbi.nlm.nih.gov/pubmed/26403281
http://dx.doi.org/10.1186/s13059-015-0764-4
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