{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,18]],"date-time":"2026-02-18T22:48:23Z","timestamp":1771454903481,"version":"3.50.1"},"reference-count":27,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2019,7,13]],"date-time":"2019-07-13T00:00:00Z","timestamp":1562976000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100005266","name":"Women\u2019s Health Initiative","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100005266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000050","name":"National Heart, Lung and Blood Institute","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,9,1]]},"abstract":"<jats:title>Summary<\/jats:title>\n               <jats:p>Genetic pathway analysis has become an important tool for investigating the association between a group of genetic variants and traits. With dense genotyping and extensive imputation, the number of genetic variants in biological pathways has increased considerably and sometimes exceeds the sample size $n$. Conducting genetic pathway analysis and statistical inference in such settings is challenging. We introduce an approach that can handle pathways whose dimension $p$ could be greater than $n$. Our method can be used to detect pathways that have nonsparse weak signals, as well as pathways that have sparse but stronger signals. We establish the asymptotic distribution for the proposed statistic and conduct theoretical analysis on its power. Simulation studies show that our test has correct Type I error control and is more powerful than existing approaches. An application to a genome-wide association study of high-density lipoproteins demonstrates the proposed approach.<\/jats:p>","DOI":"10.1093\/biomet\/asz033","type":"journal-article","created":{"date-parts":[[2019,6,7]],"date-time":"2019-06-07T07:09:22Z","timestamp":1559891362000},"page":"651-651","source":"Crossref","is-referenced-by-count":4,"title":["Statistical inference of genetic pathway analysis in high dimensions"],"prefix":"10.1093","volume":"106","author":[{"given":"Yang","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Mathematics and Statistics, Wright State University, 3640 Colonel Glenn Highway, Dayton, Ohio, U.S.A"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Sun","sequence":"additional","affiliation":[{"name":"Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, Washington, U.S.A"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexander P","family":"Reiner","sequence":"additional","affiliation":[{"name":"Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, Washington, U.S.A"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Charles","family":"Kooperberg","sequence":"additional","affiliation":[{"name":"Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, Washington, U.S.A"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qianchuan","family":"He","sequence":"additional","affiliation":[{"name":"Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, Washington, U.S.A"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2019,7,13]]},"reference":[{"key":"2019081209351974800_B1","doi-asserted-by":"crossref","first-page":"823","DOI":"10.1016\/j.ajhg.2012.08.032","article-title":"Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci","volume":"91","author":"Asselbergs,","year":"2012","journal-title":"Am. 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