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

• Published in: Scientific reports Vol. 13; no. 1; pp. 14377 - 7
• Main Authors: Aussel, Rudy, Asif, Muhammad, Chenag, Sabrina, Jaeger, Sébastien, Milpied, Pierre, Spinelli, Lionel
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.09.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114/794; 631/61/212; Bioinformatics; Biological research; Biologists; Biology; Collaboration; Data analysis; Datasets; Genes; Genomics; Humanities and Social Sciences; Life Sciences; multidisciplinary; Quality control; Science; Science (multidisciplinary); Spatial analysis; Spatial discrimination; Transcriptomics; Visualization; Genomics; Software
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-023-40959-z

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.