{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T19:42:22Z","timestamp":1760298142228,"version":"3.37.0"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"21","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: Canonical correlation analysis (CCA) can be used to capture the underlying genetic background of a complex disease, by associating two datasets containing information about a patient's phenotypical and genetic details. Often the genetic information is measured on a qualitative scale, consequently ordinary CCA cannot be applied to such data. Moreover, the size of the data in genetic studies can be enormous, thereby making the results difficult to interpret.<\/jats:p><jats:p>Results: We developed a penalized non-linear CCA approach that can deal with qualitative data by transforming each qualitative variable into a continuous variable through optimal scaling. Additionally, sparse results were obtained by adapting soft-thresholding to this non-linear version of the CCA. By means of simulation studies, we show that our method is capable of extracting relevant variables out of high-dimensional sets. We applied our method to a genetic dataset containing 144 patients with glial cancer.<\/jats:p><jats:p>Contact: \u00a0s.waaijenborg@amc.uva.nl<\/jats:p>","DOI":"10.1093\/bioinformatics\/btp491","type":"journal-article","created":{"date-parts":[[2009,8,19]],"date-time":"2009-08-19T03:03:10Z","timestamp":1250650990000},"page":"2764-2771","source":"Crossref","is-referenced-by-count":13,"title":["Correlating multiple SNPs and multiple disease phenotypes: penalized non-linear canonical correlation analysis"],"prefix":"10.1093","volume":"25","author":[{"given":"Sandra","family":"Waaijenborg","sequence":"first","affiliation":[{"name":"Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Meibergdreef 9, 1100 DD Amsterdam, The Netherlands"}]},{"given":"Aeilko H.","family":"Zwinderman","sequence":"additional","affiliation":[{"name":"Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Meibergdreef 9, 1100 DD Amsterdam, The Netherlands"}]}],"member":"286","published-online":{"date-parts":[[2009,8,17]]},"reference":[{"key":"2023013112200299900_B1","first-page":"453","article-title":"Linear smoothers and additive models","volume":"17","author":"Buja","year":"1989","journal-title":"Ann. 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