Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pcbi.1004957
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dc.titleMEGAN Community Edition - Interactive Exploration and Analysis of Large-Scale Microbiome Sequencing Data
dc.contributor.authorHuson D.H.
dc.contributor.authorBeier S.
dc.contributor.authorFlade I.
dc.contributor.authorGórska A.
dc.contributor.authorEl-Hadidi M.
dc.contributor.authorMitra S.
dc.contributor.authorRuscheweyh H.-J.
dc.contributor.authorTappu R.
dc.date.accessioned2019-11-08T06:48:24Z
dc.date.available2019-11-08T06:48:24Z
dc.date.issued2016
dc.identifier.citationHuson D.H., Beier S., Flade I., Górska A., El-Hadidi M., Mitra S., Ruscheweyh H.-J., Tappu R. (2016). MEGAN Community Edition - Interactive Exploration and Analysis of Large-Scale Microbiome Sequencing Data. PLoS Computational Biology 12 (6) : e1004957. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pcbi.1004957
dc.identifier.issn1553734X
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/161912
dc.description.abstractThere is increasing interest in employing shotgun sequencing, rather than amplicon sequencing, to analyze microbiome samples. Typical projects may involve hundreds of samples and billions of sequencing reads. The comparison of such samples against a protein reference database generates billions of alignments and the analysis of such data is computationally challenging. To address this, we have substantially rewritten and extended our widely-used microbiome analysis tool MEGAN so as to facilitate the interactive analysis of the taxonomic and functional content of very large microbiome datasets. Other new features include a functional classifier called InterPro2GO, gene-centric read assembly, principal coordinate analysis of taxonomy and function, and support for metadata. The new program is called MEGAN Community Edition (CE) and is open source. By integrating MEGAN CE with our high-throughput DNA-to-protein alignment tool DIAMOND and by providing a new program MeganServer that allows access to metagenome analysis files hosted on a server, we provide a straightforward, yet powerful and complete pipeline for the analysis of metagenome shotgun sequences. We illustrate how to perform a full-scale computational analysis of a metagenomic sequencing project, involving 12 samples and 800 million reads, in less than three days on a single server. All source code is available here: https://github.com/danielhuson/megan-ce © 2016 Huson et al.
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceUnpaywall 20191101
dc.subjectDNA
dc.subjectprotein
dc.subjectArticle
dc.subjectBacteroides
dc.subjectcomputer program
dc.subjectcontrolled study
dc.subjectdata analysis
dc.subjectgene sequence
dc.subjectgenome analysis
dc.subjecthigh throughput sequencing
dc.subjecthuman
dc.subjectmale
dc.subjectmetagenome
dc.subjectmicrobiome
dc.subjectmicrobiome sequencing
dc.subjectnonhuman
dc.subjectprotein database
dc.subjectreference database
dc.subjecttaxonomy
dc.subjectbacterial genome
dc.subjectcomputer interface
dc.subjectDNA sequence
dc.subjectgenetics
dc.subjectmicroflora
dc.subjectprocedures
dc.subjectsoftware
dc.subjectGenome, Bacterial
dc.subjectHigh-Throughput Nucleotide Sequencing
dc.subjectMetagenome
dc.subjectMicrobiota
dc.subjectSequence Analysis, DNA
dc.subjectSoftware
dc.subjectUser-Computer Interface
dc.typeArticle
dc.contributor.departmentLIFE SCIENCES INSTITUTE
dc.description.doi10.1371/journal.pcbi.1004957
dc.description.sourcetitlePLoS Computational Biology
dc.description.volume12
dc.description.issue6
dc.description.pagee1004957
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