{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/metagenome-assembly-of-high-fidelity-long","title":"Metagenome assembly of high-fidelity long reads with hifiasm-meta","arxiv_id":"2110.08457","date":"2021-10-16","proceeding":null,"authors":["Xiaowen Feng","Haoyu Cheng","Daniel Portik","Heng Li"],"abstract":"Current metagenome assemblers developed for short sequence reads or noisy long readswere not optimized for accurate long reads. Here we describe hifiasm-meta, a new metagenome assembler that exploits the high accuracy of recent data. Evaluated on seven empirical datasets, hifiasm-meta reconstructed tens to hundreds of complete circular bacterial genomes per dataset, consistently outperforming other metagenome assemblers.","url_abs":"https://arxiv.org/abs/2110.08457v1","url_pdf":"https://arxiv.org/pdf/2110.08457v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"metagenome-assembly-of-high-fidelity-long","repo_url":"https://github.com/xfengnefx/hifiasm-meta","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"high","task_name":"Vocal Bursts Intensity Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}