ArticleMolecular biology and evolution2020
Computational Framework for High-Quality Production and Large-Scale Evolutionary Analysis of Metagenome Assembled Genomes.
Article in Molecular biology and evolution, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Gut microbiome biomarkers for colorectal cancer detection: a systematic review highlighting age as a key confounder.Frontiers in oncology · 2026Pooled it
- Article
- Improving metagenome binning by integrating intrinsic features and taxonomy.Nature biotechnology · 2026Article
- 2Pipe starts with a question: matching you with the correct pipeline for MAG reconstruction.mSystems · 2026Review
- Bacterial population-level trade-offs between drought tolerance and resource acquisition traits impact decomposition.The ISME journal · 2024Article
- MetaBakery: a Singularity implementation of bioBakery tools as a skeleton application for efficient HPC deconvolution of microbiome metagenomic sequencing data to machine learning ready information.Frontiers in microbiology · 2024Article
- Microdiversity of the vaginal microbiome is associated with preterm birth.Nature communications · 2023Article
- Microdiversity of the Vaginal Microbiome is Associated with Preterm Birth.bioRxiv : the preprint server for biology · 2023Article
- Mining of novel secondary metabolite biosynthetic gene clusters from acid mine drainage.Scientific data · 2022Article
- metaGEM: reconstruction of genome scale metabolic models directly from metagenomes.Nucleic acids research · 2021Article
- Article
- Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions.Frontiers in microbiology · 2021Article
- A review of computational tools for generating metagenome-assembled genomes from metagenomic sequencing data.Computational and structural biotechnology journal · 2021Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 user-tailored 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.
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Registered trials
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