{"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/indexing-variation-graphs","title":"Indexing Variation Graphs","arxiv_id":"1604.06605","date":"2016-04-22","proceeding":null,"authors":["Jouni Sirén"],"abstract":"Variation graphs, which represent genetic variation within a population, are replacing sequences as reference genomes. Path indexes are one of the most important tools for working with variation graphs. They generalize text indexes to graphs, allowing one to find the paths matching the query string. We propose using de Bruijn graphs as path indexes, compressing them by merging redundant subgraphs, and encoding them with the Burrows-Wheeler transform. The resulting fast, space-efficient, and versatile index is used in the variation graph toolkit vg.","url_abs":"http://arxiv.org/abs/1604.06605v4","url_pdf":"http://arxiv.org/pdf/1604.06605v4.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":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"indexing-variation-graphs","repo_url":"https://github.com/jltsiren/gcsa2","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"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}