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MetaCarvel: linking assembly graph motifs to biological variants

Reconstructing genomic segments from metagenomics data is a highly complex task. In addition to general challenges, such as repeats and sequencing errors, metagenomic assembly needs to tolerate the uneven depth of coverage among organisms in a community and differences between nearly identical strai...

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Detalles Bibliográficos
Autores principales: Ghurye, Jay, Treangen, Todd, Fedarko, Marcus, Hervey, W. Judson, Pop, Mihai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6710874/
https://www.ncbi.nlm.nih.gov/pubmed/31451112
http://dx.doi.org/10.1186/s13059-019-1791-3
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author Ghurye, Jay
Treangen, Todd
Fedarko, Marcus
Hervey, W. Judson
Pop, Mihai
author_facet Ghurye, Jay
Treangen, Todd
Fedarko, Marcus
Hervey, W. Judson
Pop, Mihai
author_sort Ghurye, Jay
collection PubMed
description Reconstructing genomic segments from metagenomics data is a highly complex task. In addition to general challenges, such as repeats and sequencing errors, metagenomic assembly needs to tolerate the uneven depth of coverage among organisms in a community and differences between nearly identical strains. Previous methods have addressed these issues by smoothing genomic variants. We present a variant-aware metagenomic scaffolder called MetaCarvel, which combines new strategies for repeat detection with graph analytics for the discovery of variants. We show that MetaCarvel can accurately reconstruct genomic segments from complex microbial mixtures and correctly identify and characterize several classes of common genomic variants. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-019-1791-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-67108742019-08-28 MetaCarvel: linking assembly graph motifs to biological variants Ghurye, Jay Treangen, Todd Fedarko, Marcus Hervey, W. Judson Pop, Mihai Genome Biol Method Reconstructing genomic segments from metagenomics data is a highly complex task. In addition to general challenges, such as repeats and sequencing errors, metagenomic assembly needs to tolerate the uneven depth of coverage among organisms in a community and differences between nearly identical strains. Previous methods have addressed these issues by smoothing genomic variants. We present a variant-aware metagenomic scaffolder called MetaCarvel, which combines new strategies for repeat detection with graph analytics for the discovery of variants. We show that MetaCarvel can accurately reconstruct genomic segments from complex microbial mixtures and correctly identify and characterize several classes of common genomic variants. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-019-1791-3) contains supplementary material, which is available to authorized users. BioMed Central 2019-08-26 /pmc/articles/PMC6710874/ /pubmed/31451112 http://dx.doi.org/10.1186/s13059-019-1791-3 Text en © The Author(s). 2019 Open Access This 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 Method
Ghurye, Jay
Treangen, Todd
Fedarko, Marcus
Hervey, W. Judson
Pop, Mihai
MetaCarvel: linking assembly graph motifs to biological variants
title MetaCarvel: linking assembly graph motifs to biological variants
title_full MetaCarvel: linking assembly graph motifs to biological variants
title_fullStr MetaCarvel: linking assembly graph motifs to biological variants
title_full_unstemmed MetaCarvel: linking assembly graph motifs to biological variants
title_short MetaCarvel: linking assembly graph motifs to biological variants
title_sort metacarvel: linking assembly graph motifs to biological variants
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6710874/
https://www.ncbi.nlm.nih.gov/pubmed/31451112
http://dx.doi.org/10.1186/s13059-019-1791-3
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