{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T00:46:20Z","timestamp":1767919580480,"version":"3.49.0"},"reference-count":11,"publisher":"Oxford University Press (OUP)","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,4,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: DNA copy number and mRNA expression are commonly used data types in cancer studies. Available software for integrative analysis arbitrarily fixes the parametric form of the association between the two molecular levels and hence offers no opportunities for modelling it. We present a new tool for flexible modelling of this association. PLRS uses a wide class of interpretable models including popular ones and incorporates prior biological knowledge. It is capable to identify the gene-specific type of relationship between gene copy number and mRNA expression. Moreover, it tests the strength of the association and provides confidence intervals. We illustrate PLRS using glioblastoma data from The Cancer Genome Atlas.<\/jats:p>\n               <jats:p>Availability and implementation: PLRS is implemented as an R package and available from Bioconductor (as of version 2.12; http:\/\/bioconductor.org). Additional code for parallel computations is available as Supplementary Material.<\/jats:p>\n               <jats:p>Contact: \u00a0g.g.r.leday@vu.nl<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btt082","type":"journal-article","created":{"date-parts":[[2013,2,19]],"date-time":"2013-02-19T12:32:56Z","timestamp":1361277176000},"page":"1081-1082","source":"Crossref","is-referenced-by-count":8,"title":["PLRS: a flexible tool for the joint analysis of DNA copy number and mRNA expression data"],"prefix":"10.1093","volume":"29","author":[{"given":"Gwena\u00ebl G.R.","family":"Leday","sequence":"first","affiliation":[{"name":"1 Department of Mathematics, VU University, De Boelelaan 1081a, 1081HV Amsterdam and 2Department of Epidemiology and Biostatistics, VU University Medical Center, 1007MB Amsterdam, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mark A.","family":"van de Wiel","sequence":"additional","affiliation":[{"name":"1 Department of Mathematics, VU University, De Boelelaan 1081a, 1081HV Amsterdam and 2Department of Epidemiology and Biostatistics, VU University Medical Center, 1007MB Amsterdam, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2013,2,17]]},"reference":[{"key":"2023012810290728500_btt082-B1","doi-asserted-by":"crossref","first-page":"422","DOI":"10.1186\/1471-2105-9-422","article-title":"SIGMA2: a system for the integrative genomic multi-dimensional analysis of cancer genomes, epigenomes, and transcriptomes","volume":"9","author":"Chari","year":"2008","journal-title":"BMC Bioinformatics"},{"key":"2023012810290728500_btt082-B2","doi-asserted-by":"crossref","first-page":"2855","DOI":"10.1093\/bioinformatics\/btp515","article-title":"integrOmics: an R package to unravel relationships between two omics datasets","volume":"25","author":"L\u00ea Cao","year":"2009","journal-title":"Bioinformatics"},{"key":"2023012810290728500_btt082-B3","doi-asserted-by":"crossref","DOI":"10.1214\/12-AOAS605","article-title":"Modeling association between DNA copy number and gene expression with constrained piecewise linear regression splines","author":"Leday","year":"2013","journal-title":"Ann. 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