دورية أكاديمية
Cellsnake: a user-friendly tool for single-cell RNA sequencing analysis.
العنوان: | Cellsnake: a user-friendly tool for single-cell RNA sequencing analysis. |
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المؤلفون: | Umu SU; Department of Pathology, Institute of Clinical Medicine, University of Oslo, Oslo 0372, Norway., Rapp Vander-Elst K; Department of Pathology, Oslo University Hospital-Rikshospitalet, Oslo 0372, Norway., Karlsen VT; Department of Pathology, Oslo University Hospital-Rikshospitalet, Oslo 0372, Norway., Chouliara M; Department of Pathology, Oslo University Hospital-Rikshospitalet, Oslo 0372, Norway., Bækkevold ES; Department of Pathology, Oslo University Hospital-Rikshospitalet, Oslo 0372, Norway.; Institute of Oral Biology, University of Oslo, Oslo 0372, Norway., Jahnsen FL; Department of Pathology, Institute of Clinical Medicine, University of Oslo, Oslo 0372, Norway.; Department of Pathology, Oslo University Hospital-Rikshospitalet, Oslo 0372, Norway., Domanska D; Department of Pathology, Oslo University Hospital-Rikshospitalet, Oslo 0372, Norway.; Department of Microbiology, University of Oslo, Rikshospitalet, Oslo 0372, Norway. |
المصدر: | GigaScience [Gigascience] 2022 Dec 28; Vol. 12. Date of Electronic Publication: 2023 Oct 27. |
نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't |
اللغة: | English |
بيانات الدورية: | Publisher: Oxford University Press Country of Publication: United States NLM ID: 101596872 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2047-217X (Electronic) Linking ISSN: 2047217X NLM ISO Abbreviation: Gigascience Subsets: MEDLINE |
أسماء مطبوعة: | Publication: 2017- : New York : Oxford University Press Original Publication: London : BioMed Central |
مواضيع طبية MeSH: | Software* , Transcriptome*, Single-Cell Analysis ; Workflow ; Sequence Analysis, RNA ; Gene Expression Profiling ; RNA |
مستخلص: | Background: Single-cell RNA sequencing (scRNA-seq) provides high-resolution transcriptome data to understand the heterogeneity of cell populations at the single-cell level. The analysis of scRNA-seq data requires the utilization of numerous computational tools. However, nonexpert users usually experience installation issues, a lack of critical functionality or batch analysis modes, and the steep learning curves of existing pipelines. Results: We have developed cellsnake, a comprehensive, reproducible, and accessible single-cell data analysis workflow, to overcome these problems. Cellsnake offers advanced features for standard users and facilitates downstream analyses in both R and Python environments. It is also designed for easy integration into existing workflows, allowing for rapid analyses of multiple samples. Conclusion: As an open-source tool, cellsnake is accessible through Bioconda, PyPi, Docker, and GitHub, making it a cost-effective and user-friendly option for researchers. By using cellsnake, researchers can streamline the analysis of scRNA-seq data and gain insights into the complex biology of single cells. (© The Author(s) 2023. Published by Oxford University Press GigaScience.) |
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فهرسة مساهمة: | Keywords: RNA-seq; Seurat; microbiome; scRNA; single-cell; snakemake; workflow |
المشرفين على المادة: | 63231-63-0 (RNA) |
تواريخ الأحداث: | Date Created: 20231027 Date Completed: 20231030 Latest Revision: 20240722 |
رمز التحديث: | 20240723 |
مُعرف محوري في PubMed: | PMC10603768 |
DOI: | 10.1093/gigascience/giad091 |
PMID: | 37889009 |
قاعدة البيانات: | MEDLINE |
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