{"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/a-spectral-algorithm-for-fast-de-novo-layout","title":"A spectral algorithm for fast de novo layout of uncorrected long nanopore reads","arxiv_id":"1609.07293","date":"2017-07-17","proceeding":null,"authors":[],"abstract":"Motivation: New long read sequencers promise to transform sequencing and\ngenome assembly by producing reads tens of kilobases long. However their high\nerror rate significantly complicates assembly and requires expensive correction\nsteps to layout the reads using standard assembly engines.\n  Results: We present an original and efficient spectral algorithm to layout\nthe uncorrected nanopore reads, and its seamless integration into a\nstraightforward overlap/layout/consensus (OLC) assembly scheme. The method is\nshown to assemble Oxford Nanopore reads from several bacterial genomes into\ngood quality (~99% identity to the reference) genome-sized contigs, while\nyielding more fragmented assemblies from a Sacharomyces cerevisiae reference\nstrain.\n  Availability and implementation: http://github.com/antrec/spectrassembler\n  Contact: antoine.recanati@inria.fr","url_abs":"http://arxiv.org/abs/1609.07293v3","url_pdf":"http://arxiv.org/pdf/1609.07293v3.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":"a-spectral-algorithm-for-fast-de-novo-layout","repo_url":"https://github.com/antrec/spectrassembler","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}