Streamlining spatial omics data analysis with Pysodb
文献类型：期刊论文
| 作者 | Lin, Senlin4,5; Zhao, Fangyuan4,5; Wu, Zihan3; Yao, Jianhua3; Zhao, Yi4,5; Yuan, Zhiyuan1,2 |
| 刊名 | NATURE PROTOCOLS
 |
| 出版日期 | 2023-12-22 |
| 页码 | 72 |
| ISSN号 | 1754-2189 |
| DOI | 10.1038/s41596-023-00925-5 |
| 英文摘要 | Advances in spatial omics technologies have improved the understanding of cellular organization in tissues, leading to the generation of complex and heterogeneous data and prompting the development of specialized tools for managing, loading and visualizing spatial omics data. The Spatial Omics Database (SODB) was established to offer a unified format for data storage and interactive visualization modules. Here we detail the use of Pysodb, a Python-based tool designed to enable the efficient exploration and loading of spatial datasets from SODB within a Python environment. We present seven case studies using Pysodb, detailing the interaction with various computational methods, ensuring reproducibility of experimental data and facilitating the integration of new data and alternative applications in SODB. The approach offers a reference for method developers by outlining label and metadata availability in representative spatial data that can be loaded by Pysodb. The tool is supplemented by a website (https://protocols-pysodb.readthedocs.io/) with detailed information for benchmarking analysis, and allows method developers to focus on computational models by facilitating data processing. This protocol is designed for researchers with limited experience in computational biology. Depending on the dataset complexity, the protocol typically requires similar to 12 h to complete. |
| 资助项目 | Chenguang Program of Shanghai Education Development Foundation ; Chenguang Program of Shanghai Education Development Foundation and Shanghai Municipal Education Commission, Shanghai Science and Technology Development Funds[23YF1403000] ; Tencent AI Lab Rhino-Bird Focused Research Program[RBFR2023008] ; Shanghai Municipal Science and Technology Major Project[2018SHZDZX01] |
| WOS研究方向 | Biochemistry & Molecular Biology |
| 语种 | 英语 |
| WOS记录号 | WOS:001130466600001 |
| 出版者 | NATURE PORTFOLIO |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/38425]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Zhao, Yi; Yuan, Zhiyuan |
| 作者单位 | 1.Fudan Univ, Pudong Med Ctr, Shanghai Pudong Hosp, Ctr Med Res & Innovat, Shanghai, Peoples R China 2.Fudan Univ, Inst Sci & Technol Brain Inspired Intelligence, MOE Frontiers Ctr Brain Sci, MOE Key Lab Computat Neurosci & Brain Inspired Int, Shanghai, Peoples R China 3.Tencent AI Lab, Shenzhen, Peoples R China 4.Univ Chinese Acad Sci, Beijing, Peoples R China 5.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lin, Senlin,Zhao, Fangyuan,Wu, Zihan,et al. Streamlining spatial omics data analysis with Pysodb[J]. NATURE PROTOCOLS,2023:72. |
| APA | Lin, Senlin,Zhao, Fangyuan,Wu, Zihan,Yao, Jianhua,Zhao, Yi,&Yuan, Zhiyuan.(2023).Streamlining spatial omics data analysis with Pysodb.NATURE PROTOCOLS,72. |
| MLA | Lin, Senlin,et al."Streamlining spatial omics data analysis with Pysodb".NATURE PROTOCOLS (2023):72. |
入库方式： OAI收割
来源：计算技术研究所
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