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However, SRT data often suffer from substantial technical noise introduced by experimental procedures, posing challenges for downstream analyses. To overcome these challenges, we introduce a Multiview Denoising framework for Spatial Transcriptomics (MvDST), which integrates a deep autoencoder and self-supervised learning to jointly reconstruct expression profiles, denoise features, and enforce cross-view consistency, effectively reducing technical noise, and heterogeneity. As a result, MvDST reliably and accurately delineates tissue subgroups across simulated datasets under various perturbations. In real cancer datasets, it distinguishes tumor-associated domains, identifies region-specific marker genes, and reveals intra-tumoral heterogeneity. Furthermore, we validate the robustness of MvDST across multiple spatial transcriptomics platforms, including 10 $\\times $ Visium, STARmap, and osmFISH. Overall, these results demonstrate that MvDST can serve as a crucial initial step for the analysis of spatially resolved transcriptomics data.<\/jats:p>","DOI":"10.1093\/bib\/bbaf528","type":"journal-article","created":{"date-parts":[[2025,10,4]],"date-time":"2025-10-04T17:27:41Z","timestamp":1759598861000},"source":"Crossref","is-referenced-by-count":0,"title":["Denoising spatially resolved transcriptomics with consistency of heterogeneous spatial coordinates, transcription, and morphology"],"prefix":"10.1093","volume":"26","author":[{"given":"Haiyue","family":"Wang","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Xidian University , No. 2 South Taibai Road, 710071 Xi\u2019an, Shaanxi ,","place":["China"]},{"name":"School of Physics and Electronic Science, Shandong Normal University , No. 1 Daxue Road, 250358 Jinan, Shandong ,","place":["China"]}]},{"given":"Peng","family":"Gao","sequence":"additional","affiliation":[{"name":"Department of Hematology, The First Affiliated Hospital of Xi\u2019an jiaotong University , No. 277 Yanta West Road, 710061 Xi\u2019an, Shaanxi ,","place":["China"]},{"name":"Genome Institute, The First Affiliated Hospital of Xi\u2019an jiaotong University , No. 277 Yanta West Road, 710061 Xi\u2019an, Shaanxi ,","place":["China"]}]},{"given":"Shaoqing","family":"Feng","sequence":"additional","affiliation":[{"name":"Department of Plastic and Reconstructive Surgery, Shanghai Ninth People\u2019s Hospital, Shanghai Jiaotong University , No. 639 Zhizaoju Road, 200011 Shanghai ,","place":["China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5604-7137","authenticated-orcid":false,"given":"Xiaoke","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xidian University , No. 2 South Taibai Road, 710071 Xi\u2019an, Shaanxi 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