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DRISEE overestimates errors in metagenomic sequencing data

The extremely high error rates reported by Keegan et al. in ‘A platform-independent method for detecting errors in metagenomic sequencing data: DRISEE’ (PLoS Comput Biol 2012;8:e1002541) for many next-generation sequencing datasets prompted us to re-examine their results. Our analysis reveals that t...

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Detalles Bibliográficos
Autores principales: Eren, A. Murat, Morrison, Hilary G., Huse, Susan M., Sogin, Mitchell L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4171678/
https://www.ncbi.nlm.nih.gov/pubmed/23698723
http://dx.doi.org/10.1093/bib/bbt010
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author Eren, A. Murat
Morrison, Hilary G.
Huse, Susan M.
Sogin, Mitchell L.
author_facet Eren, A. Murat
Morrison, Hilary G.
Huse, Susan M.
Sogin, Mitchell L.
author_sort Eren, A. Murat
collection PubMed
description The extremely high error rates reported by Keegan et al. in ‘A platform-independent method for detecting errors in metagenomic sequencing data: DRISEE’ (PLoS Comput Biol 2012;8:e1002541) for many next-generation sequencing datasets prompted us to re-examine their results. Our analysis reveals that the presence of conserved artificial sequences, e.g. Illumina adapters, and other naturally occurring sequence motifs accounts for most of the reported errors. We conclude that DRISEE reports inflated levels of sequencing error, particularly for Illumina data. Tools offered for evaluating large datasets need scrupulous review before they are implemented.
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spelling pubmed-41716782014-09-23 DRISEE overestimates errors in metagenomic sequencing data Eren, A. Murat Morrison, Hilary G. Huse, Susan M. Sogin, Mitchell L. Brief Bioinform Papers The extremely high error rates reported by Keegan et al. in ‘A platform-independent method for detecting errors in metagenomic sequencing data: DRISEE’ (PLoS Comput Biol 2012;8:e1002541) for many next-generation sequencing datasets prompted us to re-examine their results. Our analysis reveals that the presence of conserved artificial sequences, e.g. Illumina adapters, and other naturally occurring sequence motifs accounts for most of the reported errors. We conclude that DRISEE reports inflated levels of sequencing error, particularly for Illumina data. Tools offered for evaluating large datasets need scrupulous review before they are implemented. Oxford University Press 2014-09 2013-05-22 /pmc/articles/PMC4171678/ /pubmed/23698723 http://dx.doi.org/10.1093/bib/bbt010 Text en © The Author 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), 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 Papers
Eren, A. Murat
Morrison, Hilary G.
Huse, Susan M.
Sogin, Mitchell L.
DRISEE overestimates errors in metagenomic sequencing data
title DRISEE overestimates errors in metagenomic sequencing data
title_full DRISEE overestimates errors in metagenomic sequencing data
title_fullStr DRISEE overestimates errors in metagenomic sequencing data
title_full_unstemmed DRISEE overestimates errors in metagenomic sequencing data
title_short DRISEE overestimates errors in metagenomic sequencing data
title_sort drisee overestimates errors in metagenomic sequencing data
topic Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4171678/
https://www.ncbi.nlm.nih.gov/pubmed/23698723
http://dx.doi.org/10.1093/bib/bbt010
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