webSCST：一个用于单细胞 RNA 测序数据和空间转录组学数据整合的交互式网络应用程序。
webSCST: an interactive web application for single-cell RNA-sequencing data and spatial transcriptomic data integration.
机构信息
School of Computer Science and Technology, Hainan University, Haikou 570228, China.
Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China.
出版信息
Bioinformatics. 2022 Jun 27;38(13):3488-3489. doi: 10.1093/bioinformatics/btac350.
SUMMARY
Integrative analysis of single-cell RNA-sequencing (scRNA-seq) data with spatial data for the same species and organ would provide each cell sample with a predictive spatial location, which would facilitate biological study. However, publicly available spatial sequencing datasets for specific species and organs are rare and are often displayed in different formats. In this study, we introduce a new web-based scRNA-seq analysis tool, webSCST, that integrates well-organized spatial transcriptome sequencing datasets categorized by species and organs, provides a user-friendly interface for raw single-cell processing with popular integration methods and allows users to submit their raw scRNA-seq data once to obtain predicted spatial locations for each cell type.
AVAILABILITY AND IMPLEMENTATION
webSCST implemented in shiny with all major browsers supported is available at http://www.webscst.com. webSCST is also freely available as an R package at https://github.com/swsoyee/webSCST.
摘要
将单细胞 RNA 测序（scRNA-seq）数据与同一物种和器官的空间数据进行综合分析，可为每个细胞样本提供预测的空间位置，从而促进生物学研究。然而，特定物种和器官的公开可用的空间测序数据集很少，并且通常以不同的格式显示。在这项研究中，我们介绍了一个新的基于网络的 scRNA-seq 分析工具 webSCST，它整合了按物种和器官分类的组织良好的空间转录组测序数据集，为使用流行的整合方法进行原始单细胞处理提供了用户友好的界面，并允许用户提交他们的原始 scRNA-seq 数据，一次即可获得每个细胞类型的预测空间位置。
可用性和实现
在所有主流浏览器中都支持 shiny 实现的 webSCST 可在 http://www.webscst.com 上获得。webSCST 也可作为 R 包在 https://github.com/swsoyee/webSCST 上免费获得。
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