Showers William M, Desai Jairav, Gipson Stephanie R, Engel Krysta L, Smith Clayton, Jordan Craig T, Gillen Austin E
Division of Hematology, University of Colorado School of Medicine, Aurora, CO, USA.
RefinedScience, Aurora, Colorado, USA.
bioRxiv. 2025 Jun 1:2025.05.28.656649. doi: 10.1101/2025.05.28.656649.
Single-cell sequencing has revolutionized biomedical research by uncovering cellular heterogeneity in disease mechanisms, with significant potential for advancing personalized medicine. However, participation in single-cell data analysis is limited by the programming experience required to access data. Several existing browsers allow the interrogation of single-cell data through a point-and-click interface accessible to non-programmers, but many of these browsers are limited in the depth of analysis that can be performed, or the flexibility of input data formats accepted. Thus, programming experience is still required for comprehensive data analysis. We developed scExploreR to address these limitations and extend the range of analysis tasks that can be performed by non-programmers. scExploreR is implemented as a packaged R Shiny app that can be run locally or easily deployed for multiple users on a server. scExploreR offers extensive customization options for plots, allowing users to generate publication quality figures. Leveraging our SCUBA package, scExploreR seamlessly handles multimodal data, providing identical plotting capabilities regardless of input format. By empowering researchers to directly explore and analyze single-cell data, scExploreR bridges communication gaps between biological and computational scientists, streamlining insight generation.
单细胞测序通过揭示疾病机制中的细胞异质性,彻底改变了生物医学研究,在推进个性化医疗方面具有巨大潜力。然而,参与单细胞数据分析受到访问数据所需编程经验的限制。现有的几种浏览器允许通过非程序员可访问的点击界面查询单细胞数据,但其中许多浏览器在可执行的分析深度或接受的输入数据格式灵活性方面存在限制。因此,全面的数据分析仍需要编程经验。我们开发了scExploreR来解决这些限制,并扩展非程序员可以执行的分析任务范围。scExploreR被实现为一个打包的R Shiny应用程序,可以在本地运行,也可以轻松地在服务器上为多个用户部署。scExploreR为绘图提供了广泛的定制选项,允许用户生成具有发表质量的图表。利用我们的SCUBA软件包,scExploreR无缝处理多模态数据,无论输入格式如何,都提供相同的绘图功能。通过使研究人员能够直接探索和分析单细胞数据,scExploreR弥合了生物科学家和计算科学家之间的沟通差距,简化了见解的生成。