Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding
Comprehensive annotating of cell types in spatially resolved transcriptomics to understand biological processes at the single cell level remains challenging. Here the authors introduce Spatial-ID, a supervision-based cell typing method, that combines the existing knowledge of reference single-cell R...
| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-12-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-022-35288-0 |
| _version_ | 1811204120034410496 |
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| author | Rongbo Shen Lin Liu Zihan Wu Ying Zhang Zhiyuan Yuan Junfu Guo Fan Yang Chao Zhang Bichao Chen Wanwan Feng Chao Liu Jing Guo Guozhen Fan Yong Zhang Yuxiang Li Xun Xu Jianhua Yao |
| author_facet | Rongbo Shen Lin Liu Zihan Wu Ying Zhang Zhiyuan Yuan Junfu Guo Fan Yang Chao Zhang Bichao Chen Wanwan Feng Chao Liu Jing Guo Guozhen Fan Yong Zhang Yuxiang Li Xun Xu Jianhua Yao |
| author_sort | Rongbo Shen |
| collection | DOAJ |
| description | Comprehensive annotating of cell types in spatially resolved transcriptomics to understand biological processes at the single cell level remains challenging. Here the authors introduce Spatial-ID, a supervision-based cell typing method, that combines the existing knowledge of reference single-cell RNA-seq data and the spatial information of spatially resolved transcriptomics data. |
| first_indexed | 2024-04-12T03:06:59Z |
| format | Article |
| id | doaj.art-3ae7c4f41e5046c587fc9996b00ff84a |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-04-12T03:06:59Z |
| publishDate | 2022-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-3ae7c4f41e5046c587fc9996b00ff84a2022-12-22T03:50:28ZengNature PortfolioNature Communications2041-17232022-12-0113111710.1038/s41467-022-35288-0Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embeddingRongbo Shen0Lin Liu1Zihan Wu2Ying Zhang3Zhiyuan Yuan4Junfu Guo5Fan Yang6Chao Zhang7Bichao Chen8Wanwan Feng9Chao Liu10Jing Guo11Guozhen Fan12Yong Zhang13Yuxiang Li14Xun Xu15Jianhua Yao16Tencent AI LabBGI-ShenzhenTencent AI LabBGI-ShenzhenTencent AI LabBGI-ShenzhenTencent AI LabBGI-ShenzhenBGI-ShenzhenTencent AI LabBGI-ShenzhenBGI-ShenzhenBGI-ShenzhenBGI-ShenzhenBGI-ShenzhenBGI-ShenzhenTencent AI LabComprehensive annotating of cell types in spatially resolved transcriptomics to understand biological processes at the single cell level remains challenging. Here the authors introduce Spatial-ID, a supervision-based cell typing method, that combines the existing knowledge of reference single-cell RNA-seq data and the spatial information of spatially resolved transcriptomics data.https://doi.org/10.1038/s41467-022-35288-0 |
| spellingShingle | Rongbo Shen Lin Liu Zihan Wu Ying Zhang Zhiyuan Yuan Junfu Guo Fan Yang Chao Zhang Bichao Chen Wanwan Feng Chao Liu Jing Guo Guozhen Fan Yong Zhang Yuxiang Li Xun Xu Jianhua Yao Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding Nature Communications |
| title | Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding |
| title_full | Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding |
| title_fullStr | Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding |
| title_full_unstemmed | Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding |
| title_short | Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding |
| title_sort | spatial id a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding |
| url | https://doi.org/10.1038/s41467-022-35288-0 |
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