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MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets
The recovery of genomes from metagenomic datasets is a critical step to defining the functional roles of the underlying uncultivated populations. We previously developed MaxBin, an automated binning approach for high-throughput recovery of microbial genomes from metagenomes. Here we present an expan...
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Published in: | Bioinformatics 2016-02, Vol.32 (4), p.605-607 |
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container_title | Bioinformatics |
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creator | Wu, Yu-Wei Simmons, Blake A Singer, Steven W |
description | The recovery of genomes from metagenomic datasets is a critical step to defining the functional roles of the underlying uncultivated populations. We previously developed MaxBin, an automated binning approach for high-throughput recovery of microbial genomes from metagenomes. Here we present an expanded binning algorithm, MaxBin 2.0, which recovers genomes from co-assembly of a collection of metagenomic datasets. Tests on simulated datasets revealed that MaxBin 2.0 is highly accurate in recovering individual genomes, and the application of MaxBin 2.0 to several metagenomes from environmental samples demonstrated that it could achieve two complementary goals: recovering more bacterial genomes compared to binning a single sample as well as comparing the microbial community composition between different sampling environments.
MaxBin 2.0 is freely available at http://sourceforge.net/projects/maxbin/ under BSD license. |
doi_str_mv | 10.1093/bioinformatics/btv638 |
format | article |
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MaxBin 2.0 is freely available at http://sourceforge.net/projects/maxbin/ under BSD license.</description><identifier>ISSN: 1367-4803</identifier><identifier>EISSN: 1367-4811</identifier><identifier>EISSN: 1460-2059</identifier><identifier>DOI: 10.1093/bioinformatics/btv638</identifier><identifier>PMID: 26515820</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Algorithms ; Automation ; Bacteria ; BASIC BIOLOGICAL SCIENCES ; Bioinformatics ; Genome, Bacterial ; Genome, Microbial ; Genomes ; MATHEMATICS AND COMPUTING ; Metagenome ; Metagenomics - methods ; Microorganisms ; Recovering ; Recovery ; Software</subject><ispartof>Bioinformatics, 2016-02, Vol.32 (4), p.605-607</ispartof><rights>The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c567t-7d08a9bd93a20e156bacec7a8048aa4b3e93be342620aafbc73e31670bc92cc73</citedby><cites>FETCH-LOGICAL-c567t-7d08a9bd93a20e156bacec7a8048aa4b3e93be342620aafbc73e31670bc92cc73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26515820$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://www.osti.gov/biblio/1407392$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Wu, Yu-Wei</creatorcontrib><creatorcontrib>Simmons, Blake A</creatorcontrib><creatorcontrib>Singer, Steven W</creatorcontrib><creatorcontrib>Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)</creatorcontrib><title>MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets</title><title>Bioinformatics</title><addtitle>Bioinformatics</addtitle><description>The recovery of genomes from metagenomic datasets is a critical step to defining the functional roles of the underlying uncultivated populations. We previously developed MaxBin, an automated binning approach for high-throughput recovery of microbial genomes from metagenomes. Here we present an expanded binning algorithm, MaxBin 2.0, which recovers genomes from co-assembly of a collection of metagenomic datasets. Tests on simulated datasets revealed that MaxBin 2.0 is highly accurate in recovering individual genomes, and the application of MaxBin 2.0 to several metagenomes from environmental samples demonstrated that it could achieve two complementary goals: recovering more bacterial genomes compared to binning a single sample as well as comparing the microbial community composition between different sampling environments.
MaxBin 2.0 is freely available at http://sourceforge.net/projects/maxbin/ under BSD license.</description><subject>Algorithms</subject><subject>Automation</subject><subject>Bacteria</subject><subject>BASIC BIOLOGICAL SCIENCES</subject><subject>Bioinformatics</subject><subject>Genome, Bacterial</subject><subject>Genome, Microbial</subject><subject>Genomes</subject><subject>MATHEMATICS AND COMPUTING</subject><subject>Metagenome</subject><subject>Metagenomics - methods</subject><subject>Microorganisms</subject><subject>Recovering</subject><subject>Recovery</subject><subject>Software</subject><issn>1367-4803</issn><issn>1367-4811</issn><issn>1460-2059</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNqNkU9PFjEQhxujEUQ_gqbxxOWF_tm2u96UIJJgvOi5TruzLzXb9rXtEvn2Lr5A4o3TzGSe-c3hIeQtZyecDfLUhRzSlEuEFnw9de1Gy_4ZOeRSm03Xc_78sWfygLyq9RdjTDGlX5IDoRVXvWCH5OdX-PMpJCpO2AcKicLS8hqJI3UhpZC2FOZtLqFdR9oyLejzDRa6xZQjVjqVHGlc5hZ2M9KIDf5tgqcjNKjY6mvyYoK54pv7ekR-fD7_fvZlc_Xt4vLs49XGK23axoysh8GNgwTBkCvtwKM30LOuB-icxEE6lJ3QggFMzhuJkmvDnB-EX6cj8n6fm2sLtvrQ0F_7nBL6ZnnHjBzECh3voV3JvxeszcZQPc4zJMxLtdwMUuhOMv4EVPfKCLG6eAIqBq16dZeq9qgvudaCk92VEKHcWs7snVf7v1e797revbt_sbiI4-PVg0j5F6m7pAw</recordid><startdate>20160215</startdate><enddate>20160215</enddate><creator>Wu, Yu-Wei</creator><creator>Simmons, Blake A</creator><creator>Singer, Steven W</creator><general>Oxford University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7QO</scope><scope>7TM</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>7SC</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>OTOTI</scope></search><sort><creationdate>20160215</creationdate><title>MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets</title><author>Wu, Yu-Wei ; Simmons, Blake A ; Singer, Steven W</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c567t-7d08a9bd93a20e156bacec7a8048aa4b3e93be342620aafbc73e31670bc92cc73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Algorithms</topic><topic>Automation</topic><topic>Bacteria</topic><topic>BASIC BIOLOGICAL SCIENCES</topic><topic>Bioinformatics</topic><topic>Genome, Bacterial</topic><topic>Genome, Microbial</topic><topic>Genomes</topic><topic>MATHEMATICS AND COMPUTING</topic><topic>Metagenome</topic><topic>Metagenomics - methods</topic><topic>Microorganisms</topic><topic>Recovering</topic><topic>Recovery</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wu, Yu-Wei</creatorcontrib><creatorcontrib>Simmons, Blake A</creatorcontrib><creatorcontrib>Singer, Steven W</creatorcontrib><creatorcontrib>Lawrence Berkeley National Lab. 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(LBNL), Berkeley, CA (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets</atitle><jtitle>Bioinformatics</jtitle><addtitle>Bioinformatics</addtitle><date>2016-02-15</date><risdate>2016</risdate><volume>32</volume><issue>4</issue><spage>605</spage><epage>607</epage><pages>605-607</pages><issn>1367-4803</issn><eissn>1367-4811</eissn><eissn>1460-2059</eissn><abstract>The recovery of genomes from metagenomic datasets is a critical step to defining the functional roles of the underlying uncultivated populations. We previously developed MaxBin, an automated binning approach for high-throughput recovery of microbial genomes from metagenomes. Here we present an expanded binning algorithm, MaxBin 2.0, which recovers genomes from co-assembly of a collection of metagenomic datasets. Tests on simulated datasets revealed that MaxBin 2.0 is highly accurate in recovering individual genomes, and the application of MaxBin 2.0 to several metagenomes from environmental samples demonstrated that it could achieve two complementary goals: recovering more bacterial genomes compared to binning a single sample as well as comparing the microbial community composition between different sampling environments.
MaxBin 2.0 is freely available at http://sourceforge.net/projects/maxbin/ under BSD license.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>26515820</pmid><doi>10.1093/bioinformatics/btv638</doi><tpages>3</tpages><oa>free_for_read</oa></addata></record> |
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source | Open Access: Oxford University Press Open Journals; PubMed Central |
subjects | Algorithms Automation Bacteria BASIC BIOLOGICAL SCIENCES Bioinformatics Genome, Bacterial Genome, Microbial Genomes MATHEMATICS AND COMPUTING Metagenome Metagenomics - methods Microorganisms Recovering Recovery Software |
title | MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets |
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