ArticleScientific reports2020
Terabase-scale metagenome coassembly with MetaHipMer.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Deployable high-fidelity metagenome binning at scale with QuickBin.Communications biology · 2026Article
- MeioBIOME: A snakemake workflow for the parallel analysis of meiofaunal genomes and host-associated bacteria/archaea.bioRxiv : the preprint server for biology · 2026Article
- Disentangling production and persistence of extracellular virions in grassland soils with SIP-viromics.mSystems · 2026Article
- Cultivation-independent high-quality microbial genome reconstruction from environmental samples with midi-metagenomics.Genome research · 2026Article
- A review of computational approaches for metagenomics by long-read sequencing.Science China. Life sciences · 2026Review
- CAMP: a modular metagenomics analysis system for integrated multistep data exploration.NAR genomics and bioinformatics · 2026Article
- The ornithine-arginine cycle supported a toxic, metalimnic Planktothrix rubescens bloom.Harmful algae · 2026Article
- Bin Chicken: targeted metagenomic coassembly for the efficient recovery of novel genomes.Nature methods · 2025Article
- Comparative metagenomics using pan-metagenomic graphs.bioRxiv : the preprint server for biology · 2025Article
- Host species and geographic location shape microbial diversity and functional potential in the conifer needle microbiome.Microbiome · 2025Article
- Highly-accurate prediction of colorectal cancer through low abundance uncultivated genomes recovered using metagenomic co-assembly and binning approach.BMC cancer · 2025Article
- CAMI Benchmarking Portal: online evaluation and ranking of metagenomic software.Nucleic acids research · 2025Article
- Sequential co-assembly reduces computational resources and errors in metagenome-assembled genomes.Cell reports methods · 2025Article
- GenomeOcean: An Efficient Genome Foundation Model Trained on Large-Scale Metagenomic Assemblies.bioRxiv : the preprint server for biology · 2025Article
- Metagenome-assembled-genomes recovered from the Arctic drift expedition MOSAiC.Scientific data · 2025Article
- A metagenomic perspective on the microbial prokaryotic genome census.Science advances · 2025Article
- A holistic genome dataset of bacteria and archaea of mangrove sediments.GigaScience · 2025Article
- Coassembly and binning of a twenty-year metagenomic time-series from Lake Mendota.Scientific data · 2024Article
- From soil to sequence: filling the critical gap in genome-resolved metagenomics is essential to the future of soil microbial ecology.Environmental microbiome · 2024Article
- Virus diversity and activity is driven by snowmelt and host dynamics in a high-altitude watershed soil ecosystem.Microbiome · 2023Article
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metagenome sequence datasets can contain terabytes of reads, too many to be coassembled together on a single shared-memory computer; consequently, they have only been assembled sample by sample (multiassembly) and combining the results is challenging. We can now perform coassembly of the largest datasets using MetaHipMer, a metagenome assembler designed to run on supercomputers and large clusters of compute nodes. We have reported on the implementation of MetaHipMer previously; in this paper we focus on analyzing the impact of very large coassembly. In particular, we show that coassembly recovers a larger genome fraction than multiassembly and enables the discovery of more complete genomes, with lower error rates, whereas multiassembly recovers more dominant strain variation. Being able to coassemble a large dataset does not preclude one from multiassembly; rather, having a fast, scalable metagenome assembler enables a user to more easily perform coassembly and multiassembly, and assemble both abundant, high strain variation genomes, and low-abundance, rare genomes. We present several assemblies of terabyte datasets that could never be coassembled before, demonstrating MetaHipMer's scaling power. MetaHipMer is available for public use under an open source license and all datasets used in the paper are available for public download.
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