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ShIVA: a user-friendly and interactive interface giving biologists control over their single-cell RNA-seq data

Single-cell technologies have revolutionised biological research and applications. As they continue to evolve with multi-omics and spatial resolution, analysing single-cell datasets is becoming increasingly complex. For biologists lacking expert data analysis resources, the problem is even more cruc...

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Detalles Bibliográficos
Autores principales: Aussel, Rudy, Asif, Muhammad, Chenag, Sabrina, Jaeger, Sébastien, Milpied, Pierre, Spinelli, Lionel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10474127/
https://www.ncbi.nlm.nih.gov/pubmed/37658061
http://dx.doi.org/10.1038/s41598-023-40959-z
Descripción
Sumario:Single-cell technologies have revolutionised biological research and applications. As they continue to evolve with multi-omics and spatial resolution, analysing single-cell datasets is becoming increasingly complex. For biologists lacking expert data analysis resources, the problem is even more crucial, even for the simplest single-cell transcriptomics datasets. We propose ShIVA, an interface for the analysis of single-cell RNA-seq and CITE-seq data specifically dedicated to biologists. Intuitive, iterative and documented by video tutorials, ShIVA allows biologists to follow a robust and reproducible analysis process, mostly based on the Seurat v4 R package, to fully explore and quantify their dataset, to produce useful figures and tables and to export their work to allow more complex analyses performed by experts.