{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,26]],"date-time":"2025-10-26T21:20:14Z","timestamp":1761513614700},"reference-count":15,"publisher":"Oxford University Press (OUP)","issue":"16","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,8,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: The role of personalized medicine and target treatment in the clinical management of cancer patients has become increasingly important in recent years. This has made the task of precise histological substratification of cancers crucial. Increasingly, genomic data are being seen as a valuable classifier. Specifically, copy number alteration (CNA) profiles generated by next-generation sequencing (NGS) can become a determinant for tumours subtyping. The principle purpose of this study is to devise a model with good prediction capability for the tumours histological subtypes as a function of both the patients covariates and their genome-wide CNA profiles from NGS data.<\/jats:p><jats:p>Results: We investigate a logistic regression for modelling tumour histological subtypes as a function of the patients\u2019 covariates and their CNA profiles, in a mixed model framework. The covariates, such as age and gender, are considered as fixed predictors and the genome-wide CNA profiles are considered as random predictors. We illustrate the application of this model in lung and oral cancer datasets, and the results indicate that the tumour histological subtypes can be modelled with a good fit. Our cross-validation indicates that the logistic regression exhibits the best prediction relative to other classification methods we considered in this study. The model also exhibits the best agreement in the prediction between smooth-segmented and circular binary-segmented CNA profiles.<\/jats:p><jats:p>Availability and implementation: An R package to run a logistic regression is available in http:\/\/www1.maths.leeds.ac.uk\/~arief\/R\/CNALR\/.<\/jats:p><jats:p>Contact: \u00a0a.gusnanto@leeds.ac.uk<\/jats:p><jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btv191","type":"journal-article","created":{"date-parts":[[2015,4,7]],"date-time":"2015-04-07T00:02:55Z","timestamp":1428364975000},"page":"2713-2720","source":"Crossref","is-referenced-by-count":9,"title":["Stratifying tumour subtypes based on copy number alteration profiles using next-generation sequence data"],"prefix":"10.1093","volume":"31","author":[{"given":"Arief","family":"Gusnanto","sequence":"first","affiliation":[{"name":"1 Department of Statistics, University of Leeds, Leeds, LS2 9JT, UK,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter","family":"Tcherveniakov","sequence":"additional","affiliation":[{"name":"2 Department of Thoracic Surgery, St. James Hospital, Leeds, LS9 7TF, UK,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Farag","family":"Shuweihdi","sequence":"additional","affiliation":[{"name":"1 Department of Statistics, University of Leeds, Leeds, LS2 9JT, UK,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manar","family":"Samman","sequence":"additional","affiliation":[{"name":"3 Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, LS9 7TF, UK and"},{"name":"4 King Fahad Medical City, Riyadh, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pamela","family":"Rabbitts","sequence":"additional","affiliation":[{"name":"3 Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, LS9 7TF, UK and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Henry M.","family":"Wood","sequence":"additional","affiliation":[{"name":"3 Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, LS9 7TF, UK and"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2015,4,5]]},"reference":[{"key":"2023020202205240400_btv191-B1","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1002\/cem.785","article-title":"Partial least squares for discrimination","volume":"17","author":"Barker","year":"2003","journal-title":"J. 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