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

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 enviro...

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Detalles Bibliográficos
Autores principales: Wang, Yichen, Sarfraz, Irzam, Pervaiz, Nida, Hong, Rui, Koga, Yusuke, Akavoor, Vidya, Cao, Xinyun, Alabdullatif, Salam, Zaib, Syed Ali, Wang, Zhe, Jansen, Frederick, Yajima, Masanao, Johnson, W. Evan, Campbell, Joshua D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10436054/
https://www.ncbi.nlm.nih.gov/pubmed/37602214
http://dx.doi.org/10.1016/j.patter.2023.100814
Descripción
Sumario: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.