Interactive analysis of single-cell data using flexible workflows with SCTK2

Yichen Wang, Irzam Sarfraz, Nida Pervaiz, Rui Hong, Yusuke Koga, Vidya Akavoor, Xinyun Cao, Salam Alabdullatif, Syed Ali Zaib, Zhe Wang, Frederick Jansen, Masanao Yajima, W. Evan Johnson, Joshua D. Campbell

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Analysis of single-cell RNA sequencing (scRNA-seq) data can reveal novel insights into the heterogeneity of complex biological systems. Many tools and workflows have been developed to perform different types of analyses. However, these tools are spread across different packages or programming environments, rely on different underlying data structures, and can only be utilized by people with knowledge of programming languages. In the Single-Cell Toolkit 2 (SCTK2), we have integrated a variety of popular tools and workflows to perform various aspects of scRNA-seq analysis. All tools and workflows can be run in the R console or using an intuitive graphical user interface built with R/Shiny. HTML reports generated with Rmarkdown can be used to document and recapitulate individual steps or entire analysis workflows. We show that the toolkit offers more features when compared with existing tools and allows for a seamless analysis of scRNA-seq data for non-computational users.

Original languageEnglish (US)
Article number100814
Issue number8
StatePublished - Aug 11 2023
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General Decision Sciences


  • DSML 4: Production: Data science output is validated, understood, and regularly used for multiple domains/platforms
  • analysis
  • bioinformatics
  • genomic
  • graphical user interface
  • interactive
  • interoperability
  • single cell
  • software
  • toolkit
  • transcriptomic


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