{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T09:09:56Z","timestamp":1784538596373,"version":"3.55.0"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,7,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>We propose one-at-a-time knockoffs (OATK), a new methodology for detecting important explanatory variables in linear regression problems (including ridge and lasso) while controlling the false discovery rate (FDR). For each explanatory variable, OATK generates a knockoff design matrix that preserves the Gram matrix by replacing one-at-a-time only the single corresponding column of the original design matrix. OATK is a substantial relaxation and simplification of the knockoff filter, which simultaneously generates all columns of the knockoff design matrix to satisfy a much larger set of constraints. To test each variable\u2019s importance, statistics are then constructed by comparing the original versus knockoff coefficients. Under a mild correlation assumption on the original design matrix, we prove that OATK asymptotically controls the FDR at any desired level. Moreover, numerical results across a variety of simulation examples and a real genetics data set demonstrate that OATK provides good FDR control and regularly achieves (often substantially) higher power than existing approaches. In particular, in a genome-wide association study, OATK yielded more uniquely discovered genetic mutations associated with virological response to HIV therapeutics that were corroborated in clinical studies. Generating knockoffs one-at-a-time also has substantial computational advantages and facilitates additional enhancements, such as conditional calibration or derandomization, to further improve power and consistency of FDR control.<\/jats:p>","DOI":"10.1093\/biomtc\/ujag119","type":"journal-article","created":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T08:59:38Z","timestamp":1784537978000},"source":"Crossref","is-referenced-by-count":0,"title":["One-at-a-time knockoffs"],"prefix":"10.1093","volume":"82","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-2775-8188","authenticated-orcid":false,"given":"Charlie K","family":"Guan","sequence":"first","affiliation":[{"name":"Department of Industrial Engineering and Management Sciences, Northwestern University , Evanston, IL 60208 ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2872-5842","authenticated-orcid":false,"given":"Zhimei","family":"Ren","sequence":"additional","affiliation":[{"name":"Department of Statistics and Data Science, The Wharton School, The University of Pennsylvania , Philadelphia, PA 19104 ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel W","family":"Apley","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering and Management Sciences, Northwestern University , Evanston, IL 60208 ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,7,20]]},"reference":[{"key":"2026072004593190900_bib1","doi-asserted-by":"crossref","first-page":"2055","DOI":"10.1214\/15-AOS1337","article-title":"Controlling the false discovery rate via 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