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Therefore, the discovery and identification of cancer subtypes are crucial to cancer diagnosis, prognosis and treatment. Recent technological advances have accelerated the increasing availability of multi-omics data for cancer subtyping. To take advantage of the complementary information from multi-omics data, it is necessary to develop computational models that can represent and integrate different layers of data into a single framework. Here, we propose a decoupled contrastive clustering method (Subtype-DCC) based on multi-omics data integration for clustering to identify cancer subtypes. The idea of contrastive learning is introduced into deep clustering based on deep neural networks to learn clustering-friendly representations. Experimental results demonstrate the superior performance of the proposed Subtype-DCC model in identifying cancer subtypes over the currently available state-of-the-art clustering methods. The strength of Subtype-DCC is also supported by the survival and clinical analysis.<\/jats:p>","DOI":"10.1093\/bib\/bbad025","type":"journal-article","created":{"date-parts":[[2023,1,27]],"date-time":"2023-01-27T03:13:27Z","timestamp":1674789207000},"source":"Crossref","is-referenced-by-count":45,"title":["Subtype-DCC: decoupled contrastive clustering method for cancer subtype identification based on multi-omics data"],"prefix":"10.1093","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9944-3244","authenticated-orcid":false,"given":"Jing","family":"Zhao","sequence":"first","affiliation":[{"name":"State Key Laboratory of Microbial Metabolism , Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, , Shanghai, 200240 , China"},{"name":"Shanghai Jiao Tong University , Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, , Shanghai, 200240 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7421-0869","authenticated-orcid":false,"given":"Bowen","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Microbial Metabolism , Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, , Shanghai, 200240 , China"},{"name":"Shanghai Jiao Tong University , Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, , Shanghai, 200240 , China"}]},{"given":"Xiaotong","family":"Song","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences, Shanghai Jiao Tong University , Shanghai, 200240 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2725-6092","authenticated-orcid":false,"given":"Chujun","family":"Lyu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Microbial Metabolism , Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, , Shanghai, 200240 , China"},{"name":"Shanghai Jiao Tong University , Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, , Shanghai, 200240 , China"}]},{"given":"Weizhi","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Microbial Metabolism , Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, , Shanghai, 200240 , China"},{"name":"Shanghai Jiao Tong University , Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, , Shanghai, 200240 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2910-6725","authenticated-orcid":false,"given":"Yi","family":"Xiong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Microbial Metabolism , Joint International 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