Application of a Database-Independent Approach To Assess the Quality of Operational Taxonomic Unit Picking Methods

ABSTRACT Assignment of 16S rRNA gene sequences to operational taxonomic units (OTUs) allows microbial ecologists to overcome the inconsistencies and biases within bacterial taxonomy and provides a strategy for clustering similar sequences that do not have representatives in a reference database. I h...

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Autor principal:	Patrick D. Schloss
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2016
Materias:	16S rRNA gene sequences environmental microbiology OTU QIIME bioinformatics metagenomics Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/a3c32104f0794dfba59158b8e8270463
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spelling	oai:doaj.org-article:a3c32104f0794dfba59158b8e82704632021-12-02T18:15:43ZApplication of a Database-Independent Approach To Assess the Quality of Operational Taxonomic Unit Picking Methods10.1128/mSystems.00027-162379-5077https://doaj.org/article/a3c32104f0794dfba59158b8e82704632016-04-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00027-16https://doaj.org/toc/2379-5077ABSTRACT Assignment of 16S rRNA gene sequences to operational taxonomic units (OTUs) allows microbial ecologists to overcome the inconsistencies and biases within bacterial taxonomy and provides a strategy for clustering similar sequences that do not have representatives in a reference database. I have applied the Matthews correlation coefficient to assess the ability of 15 reference-independent and -dependent clustering algorithms to assign sequences to OTUs. This metric quantifies the ability of an algorithm to reflect the relationships between sequences without the use of a reference and can be applied to any data set or method. The most consistently robust method was the average neighbor algorithm; however, for some data sets, other algorithms matched its performance.Patrick D. SchlossAmerican Society for Microbiologyarticle16S rRNA gene sequencesenvironmental microbiologyOTUQIIMEbioinformaticsmetagenomicsMicrobiologyQR1-502ENmSystems, Vol 1, Iss 2 (2016)
institution	DOAJ
collection	DOAJ
language	EN
topic	16S rRNA gene sequences environmental microbiology OTU QIIME bioinformatics metagenomics Microbiology QR1-502
spellingShingle	16S rRNA gene sequences environmental microbiology OTU QIIME bioinformatics metagenomics Microbiology QR1-502 Patrick D. Schloss Application of a Database-Independent Approach To Assess the Quality of Operational Taxonomic Unit Picking Methods
description	ABSTRACT Assignment of 16S rRNA gene sequences to operational taxonomic units (OTUs) allows microbial ecologists to overcome the inconsistencies and biases within bacterial taxonomy and provides a strategy for clustering similar sequences that do not have representatives in a reference database. I have applied the Matthews correlation coefficient to assess the ability of 15 reference-independent and -dependent clustering algorithms to assign sequences to OTUs. This metric quantifies the ability of an algorithm to reflect the relationships between sequences without the use of a reference and can be applied to any data set or method. The most consistently robust method was the average neighbor algorithm; however, for some data sets, other algorithms matched its performance.
format	article
author	Patrick D. Schloss
author_facet	Patrick D. Schloss
author_sort	Patrick D. Schloss
title	Application of a Database-Independent Approach To Assess the Quality of Operational Taxonomic Unit Picking Methods
title_short	Application of a Database-Independent Approach To Assess the Quality of Operational Taxonomic Unit Picking Methods
title_full	Application of a Database-Independent Approach To Assess the Quality of Operational Taxonomic Unit Picking Methods
title_fullStr	Application of a Database-Independent Approach To Assess the Quality of Operational Taxonomic Unit Picking Methods
title_full_unstemmed	Application of a Database-Independent Approach To Assess the Quality of Operational Taxonomic Unit Picking Methods
title_sort	application of a database-independent approach to assess the quality of operational taxonomic unit picking methods
publisher	American Society for Microbiology
publishDate	2016
url	https://doaj.org/article/a3c32104f0794dfba59158b8e8270463
work_keys_str_mv	AT patrickdschloss applicationofadatabaseindependentapproachtoassessthequalityofoperationaltaxonomicunitpickingmethods
_version_	1718378349971111936

Application of a Database-Independent Approach To Assess the Quality of Operational Taxonomic Unit Picking Methods

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