{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T17:52:19Z","timestamp":1775325139378,"version":"3.50.1"},"reference-count":37,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2019,9,10]],"date-time":"2019-09-10T00:00:00Z","timestamp":1568073600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000265","name":"UK Medical Research Council","doi-asserted-by":"crossref","award":["G0800648"],"award-info":[{"award-number":["G0800648"]}],"id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,2,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Clustering patient omic data is integral to developing precision medicine because it allows the identification of disease subtypes. A current major challenge is the integration multi-omic data to identify a shared structure and reduce noise. Cluster analysis is also increasingly applied on single-omic data, for example, in single cell RNA-seq analysis for clustering the transcriptomes of individual cells. This technology has clinical implications. Our motivation was therefore to develop a flexible and effective spectral clustering tool for both single and multi-omic data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We present Spectrum, a new spectral clustering method for complex omic data. Spectrum uses a self-tuning density-aware kernel we developed that enhances the similarity between points that share common nearest neighbours. It uses a tensor product graph data integration and diffusion procedure to reduce noise and reveal underlying structures. Spectrum contains a new method for finding the optimal number of clusters (K) involving eigenvector distribution analysis. Spectrum can automatically find K for both Gaussian and non-Gaussian structures. We demonstrate across 21 real expression datasets that Spectrum gives improved runtimes and better clustering results relative to other methods.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>Spectrum is available as an R software package from CRAN https:\/\/cran.r-project.org\/web\/packages\/Spectrum\/index.html.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btz704","type":"journal-article","created":{"date-parts":[[2019,9,6]],"date-time":"2019-09-06T07:40:54Z","timestamp":1567755654000},"page":"1159-1166","source":"Crossref","is-referenced-by-count":97,"title":["Spectrum: fast density-aware spectral clustering for single and multi-omic data"],"prefix":"10.1093","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4453-9484","authenticated-orcid":false,"given":"Christopher R","family":"John","sequence":"first","affiliation":[{"name":"Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Bart\u2019s and The London School of Medicine and Dentistry, Queen Mary University of London , London EC1M 6BQ, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9632-2159","authenticated-orcid":false,"given":"David","family":"Watson","sequence":"additional","affiliation":[{"name":"Oxford Internet Institute, University of Oxford , Oxford OX1 3JS, UK"},{"name":"The Alan Turing Institute , London NW1 2DB, UK"}]},{"given":"Michael R","family":"Barnes","sequence":"additional","affiliation":[{"name":"Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Bart\u2019s and The London School of Medicine and Dentistry, Queen Mary University of London , London EC1M 6BQ, UK"},{"name":"The Alan Turing Institute , London NW1 2DB, UK"}]},{"given":"Costantino","family":"Pitzalis","sequence":"additional","affiliation":[{"name":"Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Bart\u2019s and The London School of Medicine and Dentistry, Queen Mary University of London , London EC1M 6BQ, UK"}]},{"given":"Myles J","family":"Lewis","sequence":"additional","affiliation":[{"name":"Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Bart\u2019s and The London School of Medicine and Dentistry, Queen Mary University of London , London EC1M 6BQ, UK"}]}],"member":"286","published-online":{"date-parts":[[2019,9,10]]},"reference":[{"key":"2023013110134125500_btz704-B1","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1016\/j.cell.2014.09.050","article-title":"Integrated genomic characterization of papillary thyroid carcinoma","volume":"159","author":"Agrawal","year":"2014","journal-title":"Cell"},{"key":"2023013110134125500_btz704-B2","doi-asserted-by":"crossref","first-page":"1681","DOI":"10.1016\/j.cell.2015.05.044","article-title":"Genomic classification of cutaneous melanoma","volume":"161","author":"Akbani","year":"2015","journal-title":"Cell"},{"key":"2023013110134125500_btz704-B3","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.cels.2016.08.011","article-title":"A single-cell transcriptomic map of the human and mouse pancreas reveals inter-and intra-cell population structure","volume":"3","author":"Baron","year":"2016","journal-title":"Cell Syst"},{"key":"2023013110134125500_btz704-B4","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1038\/nbt.4096","article-title":"Integrating single-cell transcriptomic data across different conditions, technologies, and species","volume":"36","author":"Butler","year":"2018","journal-title":"Nat. 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