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Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing

High-throughput sequencing has revolutionized microbial ecology, but read quality remains a significant barrier to accurate taxonomy assignment and alpha diversity assessment for microbial communities. We demonstrate that high-quality read length and abundance are the primary factors differentiating...

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Detalles Bibliográficos
Autores principales: Bokulich, Nicholas A., Subramanian, Sathish, Faith, Jeremiah J., Gevers, Dirk, Gordon, Jeffrey I., Knight, Rob, Mills, David A., Caporaso, J. Gregory
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531572/
https://www.ncbi.nlm.nih.gov/pubmed/23202435
http://dx.doi.org/10.1038/nmeth.2276
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author Bokulich, Nicholas A.
Subramanian, Sathish
Faith, Jeremiah J.
Gevers, Dirk
Gordon, Jeffrey I.
Knight, Rob
Mills, David A.
Caporaso, J. Gregory
author_facet Bokulich, Nicholas A.
Subramanian, Sathish
Faith, Jeremiah J.
Gevers, Dirk
Gordon, Jeffrey I.
Knight, Rob
Mills, David A.
Caporaso, J. Gregory
author_sort Bokulich, Nicholas A.
collection PubMed
description High-throughput sequencing has revolutionized microbial ecology, but read quality remains a significant barrier to accurate taxonomy assignment and alpha diversity assessment for microbial communities. We demonstrate that high-quality read length and abundance are the primary factors differentiating correct from erroneous reads produced by Illumina GAIIx, HiSeq, and MiSeq instruments. We present guidelines for user-defined quality-filtering strategies, enabling efficient extraction of high-quality data from, and facilitating interpretation of Illumina sequencing results.
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spelling pubmed-35315722013-07-01 Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing Bokulich, Nicholas A. Subramanian, Sathish Faith, Jeremiah J. Gevers, Dirk Gordon, Jeffrey I. Knight, Rob Mills, David A. Caporaso, J. Gregory Nat Methods Article High-throughput sequencing has revolutionized microbial ecology, but read quality remains a significant barrier to accurate taxonomy assignment and alpha diversity assessment for microbial communities. We demonstrate that high-quality read length and abundance are the primary factors differentiating correct from erroneous reads produced by Illumina GAIIx, HiSeq, and MiSeq instruments. We present guidelines for user-defined quality-filtering strategies, enabling efficient extraction of high-quality data from, and facilitating interpretation of Illumina sequencing results. 2012-12-02 2013-01 /pmc/articles/PMC3531572/ /pubmed/23202435 http://dx.doi.org/10.1038/nmeth.2276 Text en Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Bokulich, Nicholas A.
Subramanian, Sathish
Faith, Jeremiah J.
Gevers, Dirk
Gordon, Jeffrey I.
Knight, Rob
Mills, David A.
Caporaso, J. Gregory
Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing
title Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing
title_full Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing
title_fullStr Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing
title_full_unstemmed Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing
title_short Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing
title_sort quality-filtering vastly improves diversity estimates from illumina amplicon sequencing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531572/
https://www.ncbi.nlm.nih.gov/pubmed/23202435
http://dx.doi.org/10.1038/nmeth.2276
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