{"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/peaksegjoint-fast-supervised-peak-detection","title":"PeakSegJoint: fast supervised peak detection via joint segmentation of multiple count data samples","arxiv_id":"1506.01286","date":"2015-06-03","proceeding":null,"authors":["Toby Dylan Hocking","Guillaume Bourque"],"abstract":"Joint peak detection is a central problem when comparing samples in genomic\ndata analysis, but current algorithms for this task are unsupervised and\nlimited to at most 2 sample types. We propose PeakSegJoint, a new constrained\nmaximum likelihood segmentation model for any number of sample types. To select\nthe number of peaks in the segmentation, we propose a supervised penalty\nlearning model. To infer the parameters of these two models, we propose to use\na discrete optimization heuristic for the segmentation, and convex optimization\nfor the penalty learning. In comparisons with state-of-the-art peak detection\nalgorithms, PeakSegJoint achieves similar accuracy, faster speeds, and a more\ninterpretable model with overlapping peaks that occur in exactly the same\npositions across all samples.","url_abs":"http://arxiv.org/abs/1506.01286v1","url_pdf":"http://arxiv.org/pdf/1506.01286v1.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":"peaksegjoint-fast-supervised-peak-detection","repo_url":"https://github.com/tdhock/PeakSegJoint","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"segmentation","task_name":"Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}