ArticlePeerJ2017
BinSanity: unsupervised clustering of environmental microbial assemblies using coverage and affinity propagation.
Article in PeerJ, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 109 papers.
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Who cites it
109 citing papers in PubMed.
- Eukaryotic metagenome-assembled genomes recovered from deep metagenomic sequencing of the seagrass,Microbial genomics · 2026Article
- Phoronids and their tubes harbor distinct microbiomes compared to surrounding sediment.bioRxiv : the preprint server for biology · 2026Article
- Robust ammonia oxidation by "mBio · 2026Article
- Antarctic soil prokaryotic diversity: a dataset of 319 metagenome-assembled genomes from Deception and Livingston Islands.Microbiology resource announcements · 2026Article
- 2Pipe starts with a question: matching you with the correct pipeline for MAG reconstruction.mSystems · 2026Review
- Two worlds beneath: Distinct microbial strategies of the rock-attached and planktonic subsurface biosphere.Microbiome · 2026Article
- Diversity and ecological roles of hidden viral players in groundwater microbiomes.Nature communications · 2026Article
- Host species-specific gene expression by a widespread and flexible chemosynthetic symbiont.The ISME journal · 2026Article
- From Low-Loaded Mesophilic to High-Loaded Thermophilic Anaerobic Digestion: Changes in Reactor Performance and Microbiome.Microbial biotechnology · 2025Article
- A ubiquitous and diverse methanogenic community drives microbial methane cycling in eutrophic coastal sediments.FEMS microbiology ecology · 2025Article
- Chemoautotrophy in subzero environments and the potential for cold-adapted Rubisco.Applied and environmental microbiology · 2025Article
- Seasonal transcriptomic shifts reveal metabolic flexibility of chemosynthetic symbionts in an upwelling region.mSystems · 2025Article
- Genome-resolved metagenomics from short-read sequencing data in the era of artificial intelligence.Functional & integrative genomics · 2025Review
- Diversification, niche adaptation, and evolution of a candidate phylum thriving in the deep Critical Zone.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Disentangling the microbial genomic traits associated with aromatic hydrocarbon degradation in a jet fuel-contaminated aquifer.Biodegradation · 2024Article
- MAGqual: a stand-alone pipeline to assess the quality of metagenome-assembled genomes.Microbiome · 2024Article
- Microbial acidification by N, S, Fe and Mn oxidation as a key mechanism for deterioration of subsea tunnel sprayed concrete.Scientific reports · 2024Article
- Characterization ofmSphere · 2024Article
- Solving genomic puzzles: computational methods for metagenomic binning.Briefings in bioinformatics · 2024Review
- Living in mangroves: a syntrophic scenario unveiling a resourceful microbiome.BMC microbiology · 2024Article
49 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metagenomics has become an integral part of defining microbial diversity in various environments. Many ecosystems have characteristically low biomass and few cultured representatives. Linking potential metabolisms to phylogeny in environmental microorganisms is important for interpreting microbial community functions and the impacts these communities have on geochemical cycles. However, with metagenomic studies there is the computational hurdle of 'binning' contigs into phylogenetically related units or putative genomes. Binning methods have been implemented with varying approaches such as k-means clustering, Gaussian mixture models, hierarchical clustering, neural networks, and two-way clustering; however, many of these suffer from biases against low coverage/abundance organisms and closely related taxa/strains. We are introducing a new binning method, BinSanity, that utilizes the clustering algorithm affinity propagation (AP), to cluster assemblies using coverage with compositional based refinement (tetranucleotide frequency and percent GC content) to optimize bins containing multiple source organisms. This separation of composition and coverage based clustering reduces bias for closely related taxa. BinSanity was developed and tested on artificial metagenomes varying in size and complexity. Results indicate that BinSanity has a higher precision, recall, and Adjusted Rand Index compared to five commonly implemented methods. When tested on a previously published environmental metagenome, BinSanity generated high completion and low redundancy bins corresponding with the published metagenome-assembled genomes.
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Registered trials
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