{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T11:44:19Z","timestamp":1753875859333,"version":"3.41.2"},"reference-count":7,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2023,12,7]],"date-time":"2023-12-07T00:00:00Z","timestamp":1701907200000},"content-version":"vor","delay-in-days":6,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100009376","name":"National Bureau of Statistics of China","doi-asserted-by":"publisher","award":["2022LZ34","National Natural Science Foundation of China","11971404","72071169"],"award-info":[{"award-number":["2022LZ34","National Natural Science Foundation of China","11971404","72071169"]}],"id":[{"id":"10.13039\/100009376","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["CA241699","CA196530","CA204120"],"award-info":[{"award-number":["CA241699","CA196530","CA204120"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Summary<\/jats:title>\n                  <jats:p>Densely measured SNP data are routinely analyzed but face challenges due to its high dimensionality, especially when gene\u2013environment interactions are incorporated. In recent literature, a functional analysis strategy has been developed, which treats dense SNP measurements as a realization of a genetic function and can \u2018bypass\u2019 the dimensionality challenge. However, there is a lack of portable and friendly software, which hinders practical utilization of these functional methods. We fill this knowledge gap and develop the R package FunctanSNP. This comprehensive package encompasses estimation, identification, and visualization tools and has undergone extensive testing using both simulated and real data, confirming its reliability. FunctanSNP can serve as a convenient and reliable tool for analyzing SNP and other densely measured data.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The package is available at https:\/\/CRAN.R-project.org\/package=FunctanSNP.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btad741","type":"journal-article","created":{"date-parts":[[2023,12,7]],"date-time":"2023-12-07T22:35:19Z","timestamp":1701988519000},"source":"Crossref","is-referenced-by-count":0,"title":["FunctanSNP: an R package for functional analysis of dense SNP data (with interactions)"],"prefix":"10.1093","volume":"39","author":[{"given":"Rui","family":"Ren","sequence":"first","affiliation":[{"name":"Department of Biostatistics, Yale School of Public Health , New Haven, CT 06520, United 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