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ShIVA: a user-friendly and interactive interface giving biologists control over their single-cell RNA-seq data.
Aussel, Rudy; Asif, Muhammad; Chenag, Sabrina; Jaeger, Sébastien; Milpied, Pierre; Spinelli, Lionel.
  • Aussel R; CNRS, INSERM, CIML, Centre d'Immunologie de Marseille-Luminy, Aix Marseille Univ, Marseille, France.
  • Asif M; Turing Centre for Living Systems (CENTURI), Aix Marseille Univ, Marseille, France.
  • Chenag S; Biomedical Data Science Lab, Department of Bioinformatics and Biotechnology, Government College University Faisalabad (GCUF), Faisalabad, 38000, Pakistan.
  • Jaeger S; CNRS, INSERM, CIML, Centre d'Immunologie de Marseille-Luminy, Aix Marseille Univ, Marseille, France.
  • Milpied P; CNRS, INSERM, CIML, Centre d'Immunologie de Marseille-Luminy, Aix Marseille Univ, Marseille, France.
  • Spinelli L; Turing Centre for Living Systems (CENTURI), Aix Marseille Univ, Marseille, France.
Sci Rep ; 13(1): 14377, 2023 09 01.
Article en En | MEDLINE | ID: mdl-37658061
ABSTRACT
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.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Análisis de Datos / Análisis de Expresión Génica de una Sola Célula Límite: Humans Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Análisis de Datos / Análisis de Expresión Génica de una Sola Célula Límite: Humans Idioma: En Año: 2023 Tipo del documento: Article