SMOPCA: spatially aware dimension reduction integrating multi-omics improves the efficiency of spatial domain detection
Abstract Technological advances have enabled us to profile multiple omics layers with spatial information, significantly enhancing spatial domain detection and advancing a variety of biomedical research fields. Despite these advancements, there is a notable lack of effective methods for modeling spa...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2025-05-01
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| Series: | Genome Biology |
| Online Access: | https://doi.org/10.1186/s13059-025-03576-9 |
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| _version_ | 1849731001682493440 |
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| author | Mo Chen Ruihua Cheng Jianuo He Jun Chen Jie Zhang |
| author_facet | Mo Chen Ruihua Cheng Jianuo He Jun Chen Jie Zhang |
| author_sort | Mo Chen |
| collection | DOAJ |
| description | Abstract Technological advances have enabled us to profile multiple omics layers with spatial information, significantly enhancing spatial domain detection and advancing a variety of biomedical research fields. Despite these advancements, there is a notable lack of effective methods for modeling spatial multi-omics data. We introduce SMOPCA, a Spatial Multi-Omics Principal Component Analysis method designed to perform joint dimension reduction on multimodal data while preserving spatial dependencies. Extensive experiments reveal that SMOPCA outperforms existing single-modal and multimodal dimension reduction and clustering methods, across both single-cell and spatial multi-omics datasets derived from diverse technologies and tissue structures. |
| format | Article |
| id | doaj-art-ab4db5f27cc54c17bf06a924f57e1d84 |
| institution | DOAJ |
| issn | 1474-760X |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Biology |
| spelling | doaj-art-ab4db5f27cc54c17bf06a924f57e1d842025-08-20T03:08:42ZengBMCGenome Biology1474-760X2025-05-0126113110.1186/s13059-025-03576-9SMOPCA: spatially aware dimension reduction integrating multi-omics improves the efficiency of spatial domain detectionMo Chen0Ruihua Cheng1Jianuo He2Jun Chen3Jie Zhang4National Key Laboratory for Novel Software Technology, Nanjing UniversityBig Data Statistics Research Center, Tianjin University of Finance and EconomicsNational Key Laboratory for Novel Software Technology, Nanjing UniversityDepartment of Quantitative Health Sciences, Mayo ClinicNational Key Laboratory for Novel Software Technology, Nanjing UniversityAbstract Technological advances have enabled us to profile multiple omics layers with spatial information, significantly enhancing spatial domain detection and advancing a variety of biomedical research fields. Despite these advancements, there is a notable lack of effective methods for modeling spatial multi-omics data. We introduce SMOPCA, a Spatial Multi-Omics Principal Component Analysis method designed to perform joint dimension reduction on multimodal data while preserving spatial dependencies. Extensive experiments reveal that SMOPCA outperforms existing single-modal and multimodal dimension reduction and clustering methods, across both single-cell and spatial multi-omics datasets derived from diverse technologies and tissue structures.https://doi.org/10.1186/s13059-025-03576-9 |
| spellingShingle | Mo Chen Ruihua Cheng Jianuo He Jun Chen Jie Zhang SMOPCA: spatially aware dimension reduction integrating multi-omics improves the efficiency of spatial domain detection Genome Biology |
| title | SMOPCA: spatially aware dimension reduction integrating multi-omics improves the efficiency of spatial domain detection |
| title_full | SMOPCA: spatially aware dimension reduction integrating multi-omics improves the efficiency of spatial domain detection |
| title_fullStr | SMOPCA: spatially aware dimension reduction integrating multi-omics improves the efficiency of spatial domain detection |
| title_full_unstemmed | SMOPCA: spatially aware dimension reduction integrating multi-omics improves the efficiency of spatial domain detection |
| title_short | SMOPCA: spatially aware dimension reduction integrating multi-omics improves the efficiency of spatial domain detection |
| title_sort | smopca spatially aware dimension reduction integrating multi omics improves the efficiency of spatial domain detection |
| url | https://doi.org/10.1186/s13059-025-03576-9 |
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