Heintz-Buschart, A.

Hickl, O.

May, P.

Queirós, P.

Wilmes, P.

English

The reconstruction of genomes is a critical step in genome-resolved metagenomics and for multi-omic data integration from microbial communities. Here, we present binny, a binning tool that produces high-quality metagenome-assembled genomes (MAG) from both contiguous and highly fragmented genomes. Based on established metrics, binny outperforms or is highly competitive with commonly used and state-of-the-art binning methods and finds unique genomes that could not be detected by other methods. binny uses k-mer-composition and coverage by metagenomic reads for iterative, nonlinear dimension reduction of genomic signatures as well as subsequent automated contig clustering with cluster assessment using lineage-specific marker gene sets. When compared with seven widely used binning algorithms, binny provides substantial amounts of uniquely identified MAGs and almost always recovers the most near-complete (⁠&gt;95% pure, &gt;90% complete) and high-quality (⁠&gt;90% pure, &gt;70% complete) genomes from simulated datasets from the Critical Assessment of Metagenome Interpretation initiative, as well as substantially more high-quality draft genomes, as defined by the Minimum Information about a Metagenome-Assembled Genome standard, from a real-world benchmark comprised of metagenomes from various environments than any other tested method

International Migration, Integration and Social Cohesion online publications

binny:an automated binning algorithm to recover high-quality genomes from complex metagenomic datasets

https://pure.uva.nl/ws/files/101500814/binny.pdf

binny:an automated binning algorithm to recover high-quality genomes from complex metagenomic datasets

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International Migration, Integration and Social Cohesion online publications