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A Platform-Independent Method for Detecting Errors in Metagenomic Sequencing Data: DRISEE
We provide a novel method, DRISEE (duplicate read inferred sequencing error estimation), to assess sequencing quality (alternatively referred to as “noise” or “error”) within and/or between sequencing samples. DRISEE provides positional error estimates that can be used to inform read trimming within...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3369934/ https://www.ncbi.nlm.nih.gov/pubmed/22685393 http://dx.doi.org/10.1371/journal.pcbi.1002541 |
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author | Keegan, Kevin P. Trimble, William L. Wilkening, Jared Wilke, Andreas Harrison, Travis D'Souza, Mark Meyer, Folker |
author_facet | Keegan, Kevin P. Trimble, William L. Wilkening, Jared Wilke, Andreas Harrison, Travis D'Souza, Mark Meyer, Folker |
author_sort | Keegan, Kevin P. |
collection | PubMed |
description | We provide a novel method, DRISEE (duplicate read inferred sequencing error estimation), to assess sequencing quality (alternatively referred to as “noise” or “error”) within and/or between sequencing samples. DRISEE provides positional error estimates that can be used to inform read trimming within a sample. It also provides global (whole sample) error estimates that can be used to identify samples with high or varying levels of sequencing error that may confound downstream analyses, particularly in the case of studies that utilize data from multiple sequencing samples. For shotgun metagenomic data, we believe that DRISEE provides estimates of sequencing error that are more accurate and less constrained by technical limitations than existing methods that rely on reference genomes or the use of scores (e.g. Phred). Here, DRISEE is applied to (non amplicon) data sets from both the 454 and Illumina platforms. The DRISEE error estimate is obtained by analyzing sets of artifactual duplicate reads (ADRs), a known by-product of both sequencing platforms. We present DRISEE as an open-source, platform-independent method to assess sequencing error in shotgun metagenomic data, and utilize it to discover previously uncharacterized error in de novo sequence data from the 454 and Illumina sequencing platforms. |
format | Online Article Text |
id | pubmed-3369934 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-33699342012-06-08 A Platform-Independent Method for Detecting Errors in Metagenomic Sequencing Data: DRISEE Keegan, Kevin P. Trimble, William L. Wilkening, Jared Wilke, Andreas Harrison, Travis D'Souza, Mark Meyer, Folker PLoS Comput Biol Research Article We provide a novel method, DRISEE (duplicate read inferred sequencing error estimation), to assess sequencing quality (alternatively referred to as “noise” or “error”) within and/or between sequencing samples. DRISEE provides positional error estimates that can be used to inform read trimming within a sample. It also provides global (whole sample) error estimates that can be used to identify samples with high or varying levels of sequencing error that may confound downstream analyses, particularly in the case of studies that utilize data from multiple sequencing samples. For shotgun metagenomic data, we believe that DRISEE provides estimates of sequencing error that are more accurate and less constrained by technical limitations than existing methods that rely on reference genomes or the use of scores (e.g. Phred). Here, DRISEE is applied to (non amplicon) data sets from both the 454 and Illumina platforms. The DRISEE error estimate is obtained by analyzing sets of artifactual duplicate reads (ADRs), a known by-product of both sequencing platforms. We present DRISEE as an open-source, platform-independent method to assess sequencing error in shotgun metagenomic data, and utilize it to discover previously uncharacterized error in de novo sequence data from the 454 and Illumina sequencing platforms. Public Library of Science 2012-06-07 /pmc/articles/PMC3369934/ /pubmed/22685393 http://dx.doi.org/10.1371/journal.pcbi.1002541 Text en Keegan 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Keegan, Kevin P. Trimble, William L. Wilkening, Jared Wilke, Andreas Harrison, Travis D'Souza, Mark Meyer, Folker A Platform-Independent Method for Detecting Errors in Metagenomic Sequencing Data: DRISEE |
title | A Platform-Independent Method for Detecting Errors in Metagenomic Sequencing Data: DRISEE |
title_full | A Platform-Independent Method for Detecting Errors in Metagenomic Sequencing Data: DRISEE |
title_fullStr | A Platform-Independent Method for Detecting Errors in Metagenomic Sequencing Data: DRISEE |
title_full_unstemmed | A Platform-Independent Method for Detecting Errors in Metagenomic Sequencing Data: DRISEE |
title_short | A Platform-Independent Method for Detecting Errors in Metagenomic Sequencing Data: DRISEE |
title_sort | platform-independent method for detecting errors in metagenomic sequencing data: drisee |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3369934/ https://www.ncbi.nlm.nih.gov/pubmed/22685393 http://dx.doi.org/10.1371/journal.pcbi.1002541 |
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