ArticleBriefings in bioinformatics2022
binny: an automated binning algorithm to recover high-quality genomes from complex metagenomic datasets.
Article in Briefings in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- MetaCAT enables reconstruction of high-quality microbial genomes and their association with host traits from metagenomic data.Nature microbiology · 2026Article
- Comprehensive benchmarking of metagenomic binning tools reveals key factors for improved genome recovery.Nature communications · 2026Article
- ChloroScan: Recovering Plastid Genome Bins From Metagenomic Data.Molecular ecology resources · 2026Article
- Multi-Habitat Landscape Promotes Microbial Diversity: Insights from the Traditional Agricultural Heritage and the Global Trend.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Article
- A Graph Contrastive Learning Method for Enhancing Genome Recovery in Complex Microbial Communities.Entropy (Basel, Switzerland) · 2025Article
- Benchmarking metagenomic binning tools on real datasets across sequencing platforms and binning modes.Nature communications · 2025Article
- Ketogenic diet suppresses colorectal cancer through the gut microbiome long chain fatty acid stearate.Nature communications · 2025Article
- Article
- Mapping the metagenomic diversity of the multi-kingdom glacier-fed stream microbiome.Nature microbiology · 2025Article
- Evolutionary conservation of dopamine-mediated cellular plasticity in Arctic sponges (Porifera).Frontiers in molecular biosciences · 2025Article
- Solving genomic puzzles: computational methods for metagenomic binning.Briefings in bioinformatics · 2024Review
- Genome-resolved metagenomics: a game changer for microbiome medicine.Experimental & molecular medicine · 2024Review
- Forecasting the dynamics of a complex microbial community using integrated meta-omics.Nature ecology & evolution · 2024Article
- Illuminating the oral microbiome and its host interactions: recent advancements in omics and bioinformatics technologies in the context of oral microbiome research.FEMS microbiology reviews · 2023Review
- A toolbox of machine learning software to support microbiome analysis.Frontiers in microbiology · 2023Review
- Genomic and metabolic adaptations of biofilms to ecological windows of opportunity in glacier-fed streams.Nature communications · 2022Article
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Authors and funding
5 authors.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.