A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics
文献类型：期刊论文
| 作者 | Li, Haoyang2,5; Zhou, Juexiao2,5; Li, Zhongxiao2,5; Chen, Siyuan2,5; Liao, Xingyu2,5; Zhang, Bin2,5; Zhang, Ruochi1; Wang, Yu1; Sun, Shiwei3,4; Gao, Xin2,5 |
| 刊名 | NATURE COMMUNICATIONS
 |
| 出版日期 | 2023-03-21 |
| 卷号 | 14期号:1页码:10 |
| DOI | 10.1038/s41467-023-37168-7 |
| 英文摘要 | Spatial transcriptomics technologies are used to profile transcriptomes while preserving spatial information, which enables high-resolution characterization of transcriptional patterns and reconstruction of tissue architecture. Due to the existence of low-resolution spots in recent spatial transcriptomics technologies, uncovering cellular heterogeneity is crucial for disentangling the spatial patterns of cell types, and many related methods have been proposed. Here, we benchmark 18 existing methods resolving a cellular deconvolution task with 50 real-world and simulated datasets by evaluating the accuracy, robustness, and usability of the methods. We compare these methods comprehensively using different metrics, resolutions, spatial transcriptomics technologies, spot numbers, and gene numbers. In terms of performance, CARD, Cell2location, and Tangram are the best methods for conducting the cellular deconvolution task. To refine our comparative results, we provide decision-tree-style guidelines and recommendations for method selection and their additional features, which will help users easily choose the best method for fulfilling their concerns. This study comprehensively benchmarks 18 state-of-the-art methods for cellular deconvolution of spatial transcriptomics and provide decision-tree-style guidelines and recommendations for method selection. |
| 资助项目 | King Abdullah University of Science and Technology (KAUST) Office of Research Administration (ORA)[FCC/1/1976-44-01] ; King Abdullah University of Science and Technology (KAUST) Office of Research Administration (ORA)[FCC/1/1976-45-01] ; King Abdullah University of Science and Technology (KAUST) Office of Research Administration (ORA)[URF/1/4663-01-01] ; King Abdullah University of Science and Technology (KAUST) Office of Research Administration (ORA)[REI/1/5202-01-01] ; King Abdullah University of Science and Technology (KAUST) Office of Research Administration (ORA)[REI/1/5234-01-01] ; King Abdullah University of Science and Technology (KAUST) Office of Research Administration (ORA)[REI/1/4940-01-01] ; King Abdullah University of Science and Technology (KAUST) Office of Research Administration (ORA)[RGC/3/4816-01-01] |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| 出版者 | NATURE PORTFOLIO |
| WOS记录号 | WOS:001001758000003 |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/21203]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Gao, Xin |
| 作者单位 | 1.Syneron Technol, Guangzhou 510000, Peoples R China 2.King Abdullah Univ Sci & Technol KAUST, Comp Elect & Math Sci & Engn Div, Thuwal, Saudi Arabia 3.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.King Abdullah Univ Sci & Technol KAUST, Computat Biosci Res Ctr, Thuwal, Saudi Arabia |
| 推荐引用方式 GB/T 7714 | Li, Haoyang,Zhou, Juexiao,Li, Zhongxiao,et al. A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics[J]. NATURE COMMUNICATIONS,2023,14(1):10. |
| APA | Li, Haoyang.,Zhou, Juexiao.,Li, Zhongxiao.,Chen, Siyuan.,Liao, Xingyu.,...&Gao, Xin.(2023).A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics.NATURE COMMUNICATIONS,14(1),10. |
| MLA | Li, Haoyang,et al."A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics".NATURE COMMUNICATIONS 14.1(2023):10. |
入库方式： OAI收割
来源：计算技术研究所
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