Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pcbi.1004957
Title: MEGAN Community Edition - Interactive Exploration and Analysis of Large-Scale Microbiome Sequencing Data
Authors: Huson D.H. 
Beier S.
Flade I.
Górska A.
El-Hadidi M.
Mitra S.
Ruscheweyh H.-J.
Tappu R.
Keywords: DNA
protein
Article
Bacteroides
computer program
controlled study
data analysis
gene sequence
genome analysis
high throughput sequencing
human
male
metagenome
microbiome
microbiome sequencing
nonhuman
protein database
reference database
taxonomy
bacterial genome
computer interface
DNA sequence
genetics
microflora
procedures
software
Genome, Bacterial
High-Throughput Nucleotide Sequencing
Metagenome
Microbiota
Sequence Analysis, DNA
Software
User-Computer Interface
Issue Date: 2016
Citation: Huson 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
Rights: Attribution 4.0 International
Abstract: There 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.
Source Title: PLoS Computational Biology
URI: https://scholarbank.nus.edu.sg/handle/10635/161912
ISSN: 1553734X
DOI: 10.1371/journal.pcbi.1004957
Rights: Attribution 4.0 International
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