{"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/dagger-a-sequential-algorithm-for-fdr-control","title":"DAGGER: A sequential algorithm for FDR control on DAGs","arxiv_id":"1709.10250","date":"2017-09-29","proceeding":null,"authors":["Aaditya Ramdas","Jianbo Chen","Martin J. Wainwright","Michael. I. Jordan"],"abstract":"We propose a linear-time, single-pass, top-down algorithm for multiple\ntesting on directed acyclic graphs (DAGs), where nodes represent hypotheses and\nedges specify a partial ordering in which hypotheses must be tested. The\nprocedure is guaranteed to reject a sub-DAG with bounded false discovery rate\n(FDR) while satisfying the logical constraint that a rejected node's parents\nmust also be rejected. It is designed for sequential testing settings, when the\nDAG structure is known a priori, but the $p$-values are obtained selectively\n(such as in a sequence of experiments), but the algorithm is also applicable in\nnon-sequential settings when all $p$-values can be calculated in advance (such\nas variable/model selection). Our DAGGER algorithm, shorthand for Greedily\nEvolving Rejections on DAGs, provably controls the false discovery rate under\nindependence, positive dependence or arbitrary dependence of the $p$-values.\nThe DAGGER procedure specializes to known algorithms in the special cases of\ntrees and line graphs, and simplifies to the classical Benjamini-Hochberg\nprocedure when the DAG has no edges. We explore the empirical performance of\nDAGGER using simulations, as well as a real dataset corresponding to a gene\nontology, showing favorable performance in terms of time and power.","url_abs":"http://arxiv.org/abs/1709.10250v3","url_pdf":"http://arxiv.org/pdf/1709.10250v3.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":"dagger-a-sequential-algorithm-for-fdr-control","repo_url":"https://github.com/Jianbo-Lab/DAGGER","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"model-selection","task_name":"Model Selection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}