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While a number of computational methods have been developed for SVG identification, their reliance on algorithm-specific assumptions, such as predefined kernel functions or spatial neighborhood graphs, often results in substantial variability in sensitivity and inflated false discovery rates (FDRs) across heterogeneous datasets. To address this challenge, we here develop Castl, an ensemble-based framework for SVG identification that integrates multiple detection methods through statistically designed aggregation modules. Comprehensive evaluations on both simulated and real-world data demonstrate that Castl consistently identifies biologically meaningful spatial expression patterns, mitigates method-specific biases and effectively controls FDRs across various biological contexts, resolutions, and spatial technologies. This flexible, assumption-free framework offers a robust and standardized foundation for spatially informed feature discovery in complex biological systems.<\/jats:p>","DOI":"10.1093\/bib\/bbag074","type":"journal-article","created":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T12:42:19Z","timestamp":1770381739000},"source":"Crossref","is-referenced-by-count":0,"title":["Castl: robust identification of spatially variable genes in spatial transcriptomics via an ensemble-based framework"],"prefix":"10.1093","volume":"27","author":[{"given":"Yiyi","family":"Yu","sequence":"first","affiliation":[{"name":"Department of Mathematics, College of Science, Zhejiang Sci-Tech University , 928 2nd Avenue, Qiantang District, Hangzhou, Zhejiang 310018 ,","place":["China"]}]},{"given":"Jiyuan","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences, Shanghai Jiao Tong University , 800 Dongchuan Rd, Minhang District, Shanghai 200240 ,","place":["China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3749-1483","authenticated-orcid":false,"given":"Ping-an","family":"He","sequence":"additional","affiliation":[{"name":"Department of Mathematics, College of Science, Zhejiang Sci-Tech University , 928 2nd Avenue, Qiantang District, Hangzhou, Zhejiang 310018 ,","place":["China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1832-4404","authenticated-orcid":false,"given":"Xiaoqi","family":"Zheng","sequence":"additional","affiliation":[{"name":"Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine , 227 South Chongqing Rd, Huangpu District, Shanghai 200025 ,","place":["China"]},{"name":"Hainan International Medical Center, Shanghai Jiao Tong University School of Medicine , 41 Kangxiang Rd, Boao Lecheng International Medical Tourism Pilot Zone, Qionghai, Hainan 571400 ,","place":["China"]},{"name":"The Guangxi Key Laboratory of Intelligent Precision Medicine, 22 Shuangyong Rd, 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