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Novo&Stitch: accurate reconciliation of genome assemblies via optical maps

MOTIVATION: De novo genome assembly is a challenging computational problem due to the high repetitive content of eukaryotic genomes and the imperfections of sequencing technologies (i.e. sequencing errors, uneven sequencing coverage and chimeric reads). Several assembly tools are currently available...

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Autores principales: Pan, Weihua, Wanamaker, Steve I, Ah-Fong, Audrey M V, Judelson, Howard S, Lonardi, Stefano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022655/
https://www.ncbi.nlm.nih.gov/pubmed/29949964
http://dx.doi.org/10.1093/bioinformatics/bty255
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author Pan, Weihua
Wanamaker, Steve I
Ah-Fong, Audrey M V
Judelson, Howard S
Lonardi, Stefano
author_facet Pan, Weihua
Wanamaker, Steve I
Ah-Fong, Audrey M V
Judelson, Howard S
Lonardi, Stefano
author_sort Pan, Weihua
collection PubMed
description MOTIVATION: De novo genome assembly is a challenging computational problem due to the high repetitive content of eukaryotic genomes and the imperfections of sequencing technologies (i.e. sequencing errors, uneven sequencing coverage and chimeric reads). Several assembly tools are currently available, each of which has strengths and weaknesses in dealing with the trade-off between maximizing contiguity and minimizing assembly errors (e.g. mis-joins). To obtain the best possible assembly, it is common practice to generate multiple assemblies from several assemblers and/or parameter settings and try to identify the highest quality assembly. Unfortunately, often there is no assembly that both maximizes contiguity and minimizes assembly errors, so one has to compromise one for the other. RESULTS: The concept of assembly reconciliation has been proposed as a way to obtain a higher quality assembly by merging or reconciling all the available assemblies. While several reconciliation methods have been introduced in the literature, we have shown in one of our recent papers that none of them can consistently produce assemblies that are better than the assemblies provided in input. Here we introduce Novo&Stitch, a novel method that takes advantage of optical maps to accurately carry out assembly reconciliation (assuming that the assembled contigs are sufficiently long to be reliably aligned to the optical maps, e.g. 50 Kbp or longer). Experimental results demonstrate that Novo&Stitch can double the contiguity (N50) of the input assemblies without introducing mis-joins or reducing genome completeness. AVAILABILITY AND IMPLEMENTATION: Novo&Stitch can be obtained from https://github.com/ucrbioinfo/Novo_Stitch.
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spelling pubmed-60226552018-07-10 Novo&Stitch: accurate reconciliation of genome assemblies via optical maps Pan, Weihua Wanamaker, Steve I Ah-Fong, Audrey M V Judelson, Howard S Lonardi, Stefano Bioinformatics Ismb 2018–Intelligent Systems for Molecular Biology Proceedings MOTIVATION: De novo genome assembly is a challenging computational problem due to the high repetitive content of eukaryotic genomes and the imperfections of sequencing technologies (i.e. sequencing errors, uneven sequencing coverage and chimeric reads). Several assembly tools are currently available, each of which has strengths and weaknesses in dealing with the trade-off between maximizing contiguity and minimizing assembly errors (e.g. mis-joins). To obtain the best possible assembly, it is common practice to generate multiple assemblies from several assemblers and/or parameter settings and try to identify the highest quality assembly. Unfortunately, often there is no assembly that both maximizes contiguity and minimizes assembly errors, so one has to compromise one for the other. RESULTS: The concept of assembly reconciliation has been proposed as a way to obtain a higher quality assembly by merging or reconciling all the available assemblies. While several reconciliation methods have been introduced in the literature, we have shown in one of our recent papers that none of them can consistently produce assemblies that are better than the assemblies provided in input. Here we introduce Novo&Stitch, a novel method that takes advantage of optical maps to accurately carry out assembly reconciliation (assuming that the assembled contigs are sufficiently long to be reliably aligned to the optical maps, e.g. 50 Kbp or longer). Experimental results demonstrate that Novo&Stitch can double the contiguity (N50) of the input assemblies without introducing mis-joins or reducing genome completeness. AVAILABILITY AND IMPLEMENTATION: Novo&Stitch can be obtained from https://github.com/ucrbioinfo/Novo_Stitch. Oxford University Press 2018-07-01 2018-06-27 /pmc/articles/PMC6022655/ /pubmed/29949964 http://dx.doi.org/10.1093/bioinformatics/bty255 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Ismb 2018–Intelligent Systems for Molecular Biology Proceedings
Pan, Weihua
Wanamaker, Steve I
Ah-Fong, Audrey M V
Judelson, Howard S
Lonardi, Stefano
Novo&Stitch: accurate reconciliation of genome assemblies via optical maps
title Novo&Stitch: accurate reconciliation of genome assemblies via optical maps
title_full Novo&Stitch: accurate reconciliation of genome assemblies via optical maps
title_fullStr Novo&Stitch: accurate reconciliation of genome assemblies via optical maps
title_full_unstemmed Novo&Stitch: accurate reconciliation of genome assemblies via optical maps
title_short Novo&Stitch: accurate reconciliation of genome assemblies via optical maps
title_sort novo&stitch: accurate reconciliation of genome assemblies via optical maps
topic Ismb 2018–Intelligent Systems for Molecular Biology Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022655/
https://www.ncbi.nlm.nih.gov/pubmed/29949964
http://dx.doi.org/10.1093/bioinformatics/bty255
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