Loading…

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...

Full description

Saved in:
Bibliographic Details
Published in:Bioinformatics 2016-02, Vol.32 (4), p.605-607
Main Authors: Wu, Yu-Wei, Simmons, Blake A, Singer, Steven W
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c567t-7d08a9bd93a20e156bacec7a8048aa4b3e93be342620aafbc73e31670bc92cc73
cites cdi_FETCH-LOGICAL-c567t-7d08a9bd93a20e156bacec7a8048aa4b3e93be342620aafbc73e31670bc92cc73
container_end_page 607
container_issue 4
container_start_page 605
container_title Bioinformatics
container_volume 32
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
fullrecord <record><control><sourceid>proquest_osti_</sourceid><recordid>TN_cdi_osti_scitechconnect_1407392</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1793264301</sourcerecordid><originalsourceid>FETCH-LOGICAL-c567t-7d08a9bd93a20e156bacec7a8048aa4b3e93be342620aafbc73e31670bc92cc73</originalsourceid><addsrcrecordid>eNqNkU9PFjEQhxujEUQ_gqbxxOWF_tm2u96UIJJgvOi5TruzLzXb9rXtEvn2Lr5A4o3TzGSe-c3hIeQtZyecDfLUhRzSlEuEFnw9de1Gy_4ZOeRSm03Xc_78sWfygLyq9RdjTDGlX5IDoRVXvWCH5OdX-PMpJCpO2AcKicLS8hqJI3UhpZC2FOZtLqFdR9oyLejzDRa6xZQjVjqVHGlc5hZ2M9KIDf5tgqcjNKjY6mvyYoK54pv7ekR-fD7_fvZlc_Xt4vLs49XGK23axoysh8GNgwTBkCvtwKM30LOuB-icxEE6lJ3QggFMzhuJkmvDnB-EX6cj8n6fm2sLtvrQ0F_7nBL6ZnnHjBzECh3voV3JvxeszcZQPc4zJMxLtdwMUuhOMv4EVPfKCLG6eAIqBq16dZeq9qgvudaCk92VEKHcWs7snVf7v1e797revbt_sbiI4-PVg0j5F6m7pAw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1762965851</pqid></control><display><type>article</type><title>MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets</title><source>Open Access: Oxford University Press Open Journals</source><source>PubMed Central</source><creator>Wu, Yu-Wei ; Simmons, Blake A ; Singer, Steven W</creator><creatorcontrib>Wu, Yu-Wei ; Simmons, Blake A ; Singer, Steven W ; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)</creatorcontrib><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><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. (LBNL), Berkeley, CA (United States)</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Biotechnology Research Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>OSTI.GOV</collection><jtitle>Bioinformatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wu, Yu-Wei</au><au>Simmons, Blake A</au><au>Singer, Steven W</au><aucorp>Lawrence Berkeley National Lab. (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>
fulltext fulltext
identifier ISSN: 1367-4803
ispartof Bioinformatics, 2016-02, Vol.32 (4), p.605-607
issn 1367-4803
1367-4811
1460-2059
language eng
recordid cdi_osti_scitechconnect_1407392
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
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T23%3A15%3A59IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_osti_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=MaxBin%202.0:%20an%20automated%20binning%20algorithm%20to%20recover%20genomes%20from%20multiple%20metagenomic%20datasets&rft.jtitle=Bioinformatics&rft.au=Wu,%20Yu-Wei&rft.aucorp=Lawrence%20Berkeley%20National%20Lab.%20(LBNL),%20Berkeley,%20CA%20(United%20States)&rft.date=2016-02-15&rft.volume=32&rft.issue=4&rft.spage=605&rft.epage=607&rft.pages=605-607&rft.issn=1367-4803&rft.eissn=1367-4811&rft_id=info:doi/10.1093/bioinformatics/btv638&rft_dat=%3Cproquest_osti_%3E1793264301%3C/proquest_osti_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c567t-7d08a9bd93a20e156bacec7a8048aa4b3e93be342620aafbc73e31670bc92cc73%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1762965851&rft_id=info:pmid/26515820&rfr_iscdi=true