CREST--classification resources for environmental sequence tags.

Sequencing of taxonomic or phylogenetic markers is becoming a fast and efficient method for studying environmental microbial communities. This has resulted in a steadily growing collection of marker sequences, most notably of the small-subunit (SSU) ribosomal RNA gene, and an increased understanding...

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Autores principales:	Anders Lanzén, Steffen L Jørgensen, Daniel H Huson, Markus Gorfer, Svenn Helge Grindhaug, Inge Jonassen, Lise Øvreås, Tim Urich
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/23565c021fc04c53ab4a652ba94b4253
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spelling	oai:doaj.org-article:23565c021fc04c53ab4a652ba94b42532021-11-18T08:09:19ZCREST--classification resources for environmental sequence tags.1932-620310.1371/journal.pone.0049334https://doaj.org/article/23565c021fc04c53ab4a652ba94b42532012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23145153/?tool=EBIhttps://doaj.org/toc/1932-6203Sequencing of taxonomic or phylogenetic markers is becoming a fast and efficient method for studying environmental microbial communities. This has resulted in a steadily growing collection of marker sequences, most notably of the small-subunit (SSU) ribosomal RNA gene, and an increased understanding of microbial phylogeny, diversity and community composition patterns. However, to utilize these large datasets together with new sequencing technologies, a reliable and flexible system for taxonomic classification is critical. We developed CREST (Classification Resources for Environmental Sequence Tags), a set of resources and tools for generating and utilizing custom taxonomies and reference datasets for classification of environmental sequences. CREST uses an alignment-based classification method with the lowest common ancestor algorithm. It also uses explicit rank similarity criteria to reduce false positives and identify novel taxa. We implemented this method in a web server, a command line tool and the graphical user interfaced program MEGAN. Further, we provide the SSU rRNA reference database and taxonomy SilvaMod, derived from the publicly available SILVA SSURef, for classification of sequences from bacteria, archaea and eukaryotes. Using cross-validation and environmental datasets, we compared the performance of CREST and SilvaMod to the RDP Classifier. We also utilized Greengenes as a reference database, both with CREST and the RDP Classifier. These analyses indicate that CREST performs better than alignment-free methods with higher recall rate (sensitivity) as well as precision, and with the ability to accurately identify most sequences from novel taxa. Classification using SilvaMod performed better than with Greengenes, particularly when applied to environmental sequences. CREST is freely available under a GNU General Public License (v3) from http://apps.cbu.uib.no/crest and http://lcaclassifier.googlecode.com.Anders LanzénSteffen L JørgensenDaniel H HusonMarkus GorferSvenn Helge GrindhaugInge JonassenLise ØvreåsTim UrichPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 11, p e49334 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Anders Lanzén Steffen L Jørgensen Daniel H Huson Markus Gorfer Svenn Helge Grindhaug Inge Jonassen Lise Øvreås Tim Urich CREST--classification resources for environmental sequence tags.
description	Sequencing of taxonomic or phylogenetic markers is becoming a fast and efficient method for studying environmental microbial communities. This has resulted in a steadily growing collection of marker sequences, most notably of the small-subunit (SSU) ribosomal RNA gene, and an increased understanding of microbial phylogeny, diversity and community composition patterns. However, to utilize these large datasets together with new sequencing technologies, a reliable and flexible system for taxonomic classification is critical. We developed CREST (Classification Resources for Environmental Sequence Tags), a set of resources and tools for generating and utilizing custom taxonomies and reference datasets for classification of environmental sequences. CREST uses an alignment-based classification method with the lowest common ancestor algorithm. It also uses explicit rank similarity criteria to reduce false positives and identify novel taxa. We implemented this method in a web server, a command line tool and the graphical user interfaced program MEGAN. Further, we provide the SSU rRNA reference database and taxonomy SilvaMod, derived from the publicly available SILVA SSURef, for classification of sequences from bacteria, archaea and eukaryotes. Using cross-validation and environmental datasets, we compared the performance of CREST and SilvaMod to the RDP Classifier. We also utilized Greengenes as a reference database, both with CREST and the RDP Classifier. These analyses indicate that CREST performs better than alignment-free methods with higher recall rate (sensitivity) as well as precision, and with the ability to accurately identify most sequences from novel taxa. Classification using SilvaMod performed better than with Greengenes, particularly when applied to environmental sequences. CREST is freely available under a GNU General Public License (v3) from http://apps.cbu.uib.no/crest and http://lcaclassifier.googlecode.com.
format	article
author	Anders Lanzén Steffen L Jørgensen Daniel H Huson Markus Gorfer Svenn Helge Grindhaug Inge Jonassen Lise Øvreås Tim Urich
author_facet	Anders Lanzén Steffen L Jørgensen Daniel H Huson Markus Gorfer Svenn Helge Grindhaug Inge Jonassen Lise Øvreås Tim Urich
author_sort	Anders Lanzén
title	CREST--classification resources for environmental sequence tags.
title_short	CREST--classification resources for environmental sequence tags.
title_full	CREST--classification resources for environmental sequence tags.
title_fullStr	CREST--classification resources for environmental sequence tags.
title_full_unstemmed	CREST--classification resources for environmental sequence tags.
title_sort	crest--classification resources for environmental sequence tags.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/23565c021fc04c53ab4a652ba94b4253
work_keys_str_mv	AT anderslanzen crestclassificationresourcesforenvironmentalsequencetags AT steffenljørgensen crestclassificationresourcesforenvironmentalsequencetags AT danielhhuson crestclassificationresourcesforenvironmentalsequencetags AT markusgorfer crestclassificationresourcesforenvironmentalsequencetags AT svennhelgegrindhaug crestclassificationresourcesforenvironmentalsequencetags AT ingejonassen crestclassificationresourcesforenvironmentalsequencetags AT liseøvreas crestclassificationresourcesforenvironmentalsequencetags AT timurich crestclassificationresourcesforenvironmentalsequencetags
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CREST--classification resources for environmental sequence tags.

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