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SODB有利于空间组学数据的全面探索
2023-02-21 16:03

腾讯AI实验室姚建华等研究人员合作发现,SODB有利于空间组学数据的全面探索。相关论文于2023年2月16日在线发表在《自然—方法学》杂志上。

研究人员报道了空间组学数据库(SODB),这是一个基于web的平台,其提供丰富的数据资源和一套交互式数据分析模块。SODB目前维护着来自25种空间组学技术的2400个实验,这些实验作为与各种计算包兼容的统一数据格式免费访问。SODB还提供了多个交互式数据分析模块,特别是一个独特的模块,空间组学视图(SOView)。研究人员进行了全面的统计分析,并阐明了以多个空间组学数据集为主题的基本和高级分析模块的效用。研究人员用大脑空间转录组数据证明了SOView的实用性,并恢复了已知的解剖结构。研究人员人员进一步描述了相关标记基因的功能组织域,这些标记基因在之前的方法分析中无法辨别。最后,研究人员展示了SODB如何有效地促进计算方法的开发。SODB网站为https://gene.ai.tencent.com/SpatialOmics/。命令行包可以在https://pysodb.readthedocs.io/en/latest/上获得。

据了解,空间组学技术可以生成丰富但高度复杂的数据集。

附:英文原文

Title: SODB facilitates comprehensive exploration of spatial omics data

Author: Yuan, Zhiyuan, Pan, Wentao, Zhao, Xuan, Zhao, Fangyuan, Xu, Zhimeng, Li, Xiu, Zhao, Yi, Zhang, Michael Q., Yao, Jianhua

Issue&Volume: 2023-02-16

Abstract: Spatial omics technologies generate wealthy but highly complex datasets. Here we present Spatial Omics DataBase (SODB), a web-based platform providing both rich data resources and a suite of interactive data analytical modules. SODB currently maintains >2,400 experiments from >25 spatial omics technologies, which are freely accessible as a unified data format compatible with various computational packages. SODB also provides multiple interactive data analytical modules, especially a unique module, Spatial Omics View (SOView). We conduct comprehensive statistical analyses and illustrate the utility of both basic and advanced analytical modules using multiple spatial omics datasets. We demonstrate SOView utility with brain spatial transcriptomics data and recover known anatomical structures. We further delineate functional tissue domains with associated marker genes that were obscured when analyzed using previous methods. We finally show how SODB may efficiently facilitate computational method development. The SODB website is https://gene.ai.tencent.com/SpatialOmics/. The command-line package is available at https://pysodb.readthedocs.io/en/latest/.

DOI: 10.1038/s41592-023-01773-7

Source: https://www.nature.com/articles/s41592-023-01773-7

Nature Methods:《自然—方法学》,创刊于2004年。隶属于施普林格·自然出版集团,最新IF:47.99
官方网址:https://www.nature.com/nmeth/
投稿链接:https://mts-nmeth.nature.com/cgi-bin/main.plex


本期文章:《自然—方法学》:Online/在线发表

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