16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets.

The diversity of microbial species in a metagenomic study is commonly assessed using 16S rRNA gene sequencing. With the rapid developments in genome sequencing technologies, the focus has shifted towards the sequencing of hypervariable regions of 16S rRNA gene instead of full length gene sequencing....

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Main Authors: Nikhil Chaudhary, Ashok K Sharma, Piyush Agarwal, Ankit Gupta, Vineet K Sharma
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4315456?pdf=render
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author Nikhil Chaudhary
Ashok K Sharma
Piyush Agarwal
Ankit Gupta
Vineet K Sharma
author_facet Nikhil Chaudhary
Ashok K Sharma
Piyush Agarwal
Ankit Gupta
Vineet K Sharma
author_sort Nikhil Chaudhary
collection DOAJ
description The diversity of microbial species in a metagenomic study is commonly assessed using 16S rRNA gene sequencing. With the rapid developments in genome sequencing technologies, the focus has shifted towards the sequencing of hypervariable regions of 16S rRNA gene instead of full length gene sequencing. Therefore, 16S Classifier is developed using a machine learning method, Random Forest, for faster and accurate taxonomic classification of short hypervariable regions of 16S rRNA sequence. It displayed precision values of up to 0.91 on training datasets and the precision values of up to 0.98 on the test dataset. On real metagenomic datasets, it showed up to 99.7% accuracy at the phylum level and up to 99.0% accuracy at the genus level. 16S Classifier is available freely at http://metagenomics.iiserb.ac.in/16Sclassifier and http://metabiosys.iiserb.ac.in/16Sclassifier.
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spelling doaj.art-ca5080ac8bac43b9b640657f3d7914392022-12-22T03:04:03ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01102e011610610.1371/journal.pone.011610616S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets.Nikhil ChaudharyAshok K SharmaPiyush AgarwalAnkit GuptaVineet K SharmaThe diversity of microbial species in a metagenomic study is commonly assessed using 16S rRNA gene sequencing. With the rapid developments in genome sequencing technologies, the focus has shifted towards the sequencing of hypervariable regions of 16S rRNA gene instead of full length gene sequencing. Therefore, 16S Classifier is developed using a machine learning method, Random Forest, for faster and accurate taxonomic classification of short hypervariable regions of 16S rRNA sequence. It displayed precision values of up to 0.91 on training datasets and the precision values of up to 0.98 on the test dataset. On real metagenomic datasets, it showed up to 99.7% accuracy at the phylum level and up to 99.0% accuracy at the genus level. 16S Classifier is available freely at http://metagenomics.iiserb.ac.in/16Sclassifier and http://metabiosys.iiserb.ac.in/16Sclassifier.http://europepmc.org/articles/PMC4315456?pdf=render
spellingShingle Nikhil Chaudhary
Ashok K Sharma
Piyush Agarwal
Ankit Gupta
Vineet K Sharma
16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets.
PLoS ONE
title 16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets.
title_full 16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets.
title_fullStr 16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets.
title_full_unstemmed 16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets.
title_short 16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets.
title_sort 16s classifier a tool for fast and accurate taxonomic classification of 16s rrna hypervariable regions in metagenomic datasets
url http://europepmc.org/articles/PMC4315456?pdf=render
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