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Gigascience. 2018 Jun 1;7(6). doi: 10.1093/gigascience/giy069.

AMBER: Assessment of Metagenome BinnERs.

Author information

1
Department of Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, Germany.
2
Braunschweig Integrated Centre of Systems Biology, Braunschweig, Germany.
3
Faculty of Technology, Bielefeld University, Bielefeld, Germany.
4
Center for Biotechnology, Bielefeld University, Bielefeld, Germany.
5
Department of Plant Microbe Interactions, Max Planck Institute for Plant Breeding Research, Cologne, Germany.
6
Cluster of Excellence on Plant Sciences.

Abstract

Reconstructing the genomes of microbial community members is key to the interpretation of shotgun metagenome samples. Genome binning programs deconvolute reads or assembled contigs of such samples into individual bins. However, assessing their quality is difficult due to the lack of evaluation software and standardized metrics. Here, we present Assessment of Metagenome BinnERs (AMBER), an evaluation package for the comparative assessment of genome reconstructions from metagenome benchmark datasets. It calculates the performance metrics and comparative visualizations used in the first benchmarking challenge of the initiative for the Critical Assessment of Metagenome Interpretation (CAMI). As an application, we show the outputs of AMBER for 11 binning programs on two CAMI benchmark datasets. AMBER is implemented in Python and available under the Apache 2.0 license on GitHub.

PMID:
29893851
PMCID:
PMC6022608
DOI:
10.1093/gigascience/giy069
[Indexed for MEDLINE]
Free PMC Article

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