ArticleMicrobiome2022
MetaDecoder: a novel method for clustering metagenomic contigs.
Article in Microbiome, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed.
- MetaCAT enables reconstruction of high-quality microbial genomes and their association with host traits from metagenomic data.Nature microbiology · 2026Article
- Genomic insights into the taxonomy, safety and biotechnological potential ofMicrobial genomics · 2026Article
- Protocol for the assessment of the impact of mycotoxins and glyphosate residues on the gut microbiome and resistome of European fallow deer.STAR protocols · 2026Article
- Shared biosynthetic architectures generate diverse β-amino polyketide residues in cyanobacterial peptides.bioRxiv : the preprint server for biology · 2026Article
- Viral Assemblages of a Hypersaline Estuary Show Divergent Responses to Freshwater and Temperature Disturbances.Environmental microbiology reports · 2026Article
- A review of computational approaches for metagenomics by long-read sequencing.Science China. Life sciences · 2026Review
- DCVBin: a novel binning method for single-sample metagenomes based on DNA language model and variational autoencoder.Briefings in bioinformatics · 2026Article
- Improving metagenome binning by integrating intrinsic features and taxonomy.Nature biotechnology · 2026Article
- Comprehensive benchmarking of metagenomic binning tools reveals key factors for improved genome recovery.Nature communications · 2026Article
- Spiroplasma Display an Intricate Continuum of Infection Heterogeneity and Persistence in Myrmica Ants.Molecular ecology · 2026Article
- Metagenome Sequencing and Recovery of 52 Microbial Genomes from Plastic-Polluted Coastal Sediment.Scientific data · 2026Article
- 2Pipe starts with a question: matching you with the correct pipeline for MAG reconstruction.mSystems · 2026Review
- Calibrating tetranucleotide-frequency distances for metagenomic binning with right-skewed distribution models.Bioinformatics advances · 2026Article
- VIRGO2: an enhanced gene catalog of the vaginal microbiome provides insights into its functional and ecology complexity.Nature communications · 2025Article
- Reconstruction of 1,979 prokaryotic metagenome-assembled genomes from 37 global cave environments.Scientific data · 2025Article
- Multi-Habitat Landscape Promotes Microbial Diversity: Insights from the Traditional Agricultural Heritage and the Global Trend.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Characterization of the Tychonamide Biosynthetic Pathway in the Recently Described Cyanobacterial SpeciesACS chemical biology · 2025Article
- Lactiplantibacillus plantarum Attenuates Diet-Induced Obesity and Insulin Resistance Through Gut Microbiota-Driven PPAR/PI3K-Axis Modulation.Microbial biotechnology · 2025Article
- Machine Learning Enables Alignment-Free Distance Calculation and Phylogenetic Placement Using k-Mer Frequencies.Molecular ecology resources · 2025Article
- LorBin: efficient binning of long-read metagenomes by multiscale adaptive clustering and evaluation.Nature communications · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundClustering the metagenomic contigs into potential genomes is a key step to investigate the functional roles of microbial populations. Existing algorithms have achieved considerable success with simulated or real sequencing datasets. However, accurately classifying contigs from complex metagenomes is still a challenge.
resultsWe introduced a novel clustering algorithm, MetaDecoder, which can classify metagenomic contigs based on the frequencies of k-mers and coverages. MetaDecoder was built as a two-layer model with the first layer being a GPU-based modified Dirichlet process Gaussian mixture model (DPGMM), which controls the weight of each DPGMM cluster to avoid over-segmentation by dynamically dissolving contigs in small clusters and reassigning them to the remaining clusters. The second layer comprises a semi-supervised k-mer frequency probabilistic model and a modified Gaussian mixture model for modeling the coverage based on single copy marker genes. Benchmarks on simulated and real-world datasets demonstrated that MetaDecoder can be served as a promising approach for effectively clustering metagenomic contigs.
conclusionsIn conclusion, we developed the GPU-based MetaDecoder for effectively clustering metagenomic contigs and reconstructing microbial communities from microbial data. Applying MetaDecoder on both simulated and real-world datasets demonstrated that it could generate more complete clusters with lower contamination. Using MetaDecoder, we identified novel high-quality genomes and expanded the existing catalog of bacterial genomes. Video Abstract.
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