{"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/snowball-strain-aware-gene-assembly-of","title":"Snowball: Strain aware gene assembly of Metagenomes","arxiv_id":"1510.03923","date":"2015-10-13","proceeding":null,"authors":[],"abstract":"Gene assembly is an important step in functional analysis of shotgun\nmetagenomic data. Nonetheless, strain aware assembly remains a challenging\ntask, as current assembly tools often fail to distinguish among strain variants\nor require closely related reference genomes of the studied species to be\navailable. We have developed Snowball, a novel strain aware and reference-free\ngene assembler for shotgun metagenomic data. It uses profile hidden Markov\nmodels (HMMs) of gene domains of interest to guide the assembly. Our assembler\nperforms gene assembly of individual gene domains based on read overlaps and\nerror correction using read quality scores at the same time, which result in\nvery low per-base error rates. The software runs on a user-defined number of\nprocessor cores in parallel, runs on a standard laptop and is freely available\nfor installation under Linux or OS X on:\nhttps://github.com/algbioi/snowball/wiki","url_abs":"http://arxiv.org/abs/1510.03923v1","url_pdf":"http://arxiv.org/pdf/1510.03923v1.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":"snowball-strain-aware-gene-assembly-of","repo_url":"https://github.com/algbioi/snowball","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"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}