{"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/competition-based-control-of-the-false","title":"Competition-based control of the false discovery proportion","arxiv_id":"2011.11939","date":"2020-11-24","proceeding":null,"authors":["Dong Luo","Arya Ebadi","Yilun He","Kristen Emery","William Stafford Noble","Uri Keich"],"abstract":"Recently, Barber and Cand\\`es laid the theoretical foundation for a general framework for false discovery rate (FDR) control based on the notion of \"knockoffs.\" A closely related FDR control methodology has long been employed in the analysis of mass spectrometry data, referred to there as \"target-decoy competition\" (TDC). However, any approach that aims to control the FDR, which is defined as the expected value of the false discovery proportion (FDP), suffers from a problem. Specifically, even when successfully controlling the FDR at level $\\alpha$, the FDP in the list of discoveries can significantly exceed $\\alpha$. We offer FDP-SD, a new procedure that rigorously controls the FDP in the competition (knockoff / TDC) setup by guaranteeing that the FDP is bounded by $\\alpha$ at any desired confidence level. Compared with the just-published general framework of Katsevich and Ramdas, FDP-SD generally delivers more power and often substantially so in simulated as well as real data.","url_abs":"https://arxiv.org/abs/2011.11939v3","url_pdf":"https://arxiv.org/pdf/2011.11939v3.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":"competition-based-control-of-the-false","repo_url":"https://github.com/uni-arya/stepdownfdp","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"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}