Computational framework for high-quality production and large-scale evolutionary analysis of metagenome assembled genomes
ID Murovec, Boštjan (Author), ID Deutsch, Leon (Author), ID Stres, Blaž (Author)

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Microbial species play important roles in different environments and the production of high-quality genomes from metagenome data sets represents a major obstacle to understanding their ecological and evolutionary dynamics. Metagenome-Assembled Genomes Orchestra (MAGO) is a computational framework that integrates and simplifies metagenome assembly, binning, bin improvement, bin quality (completeness and contamination), bin annotation, and evolutionary placement of bins via detailed maximum-likelihood phylogeny based on multiple marker genes using different amino acid substitution models, next to average nucleotide identity analysis of genomes for delineation of species boundaries and operational taxonomic units. MAGO offers streamlined execution of the entire metagenomics pipeline, error checking, computational resource distribution and compatibility of data formats, governed by usertailored pipeline processing. MAGO is an open-source-software package released in three different ways, as a singularity image and a Docker container for HPC purposes as well as for running MAGO on a commodity hardware, and a virtual machine for gaining a full access to MAGO underlying structure and source code. MAGO is open to suggestions for extensions and is amenable for use in both research and teaching of genomics and molecular evolution of genomes assembled from small single-cell projects or large-scale and complex environmental metagenomes.

Keywords:metagenomics, evolutionary analyses, microbial draft genomes, species boundaries, FastANI, genome assembly and binning
Work type:Article (dk_c)
Typology:1.03 - Short Scientific Article
Organization:FE - Faculty of Electrical Engineering
BF - Biotechnical Faculty
MF - Faculty of Medicine
FGG - Faculty of Civil and Geodetic Engineering
Publication status in journal:Published
Article version:Publisher's version of article
Number of pages:Str. 593-598
Numbering:Vol. 37, iss. 2
ISSN on article:0737-4038
DOI:10.1093/molbev/msz237 This link opens in a new window
COBISS.SI-ID:4315528 This link opens in a new window
Publication date in RUL:18.01.2021
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Record is a part of a journal

Title:Molecular biology and evolution
Publisher:Society for Molecular Biology and Evolution, Oxford University Press
COBISS.SI-ID:236111 This link opens in a new window


License:CC BY-NC 4.0, Creative Commons Attribution-NonCommercial 4.0 International
Description:A creative commons license that bans commercial use, but the users don’t have to license their derivative works on the same terms.
Licensing start date:01.02.2020

Secondary language

Keywords:mikrobiologija, genetika, bioinformatika, MAGO

Document is financed by a project

Funder:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije (ARRS)

Funder:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije (ARRS)

Funder:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije (ARRS)
Name:Zajem mikrobnih encimov udeleženih v učinkoviti razgradnji kompleksnih rastlinskih polimerov s transkriptomiko in de-novo rekonstrukcijo na nivoju združb

Funder:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije (ARRS)
Name:Preučevanje mikrobioma kraških podzemnih voda z novejšimi pristopi v metagenomiki

Funder:Drugi - Drug financer ali več financerjev
Funding Programme:University of Innsbruck, Institute of Microbiology Innsbruck, Republic of Austria

Funder:Drugi - Drug financer ali več financerjev
Funding Programme:CEEPUS Freemover Grant

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