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bioRxiv · 10.1101/2023.05.03.539204

cellsnake: a user-friendly tool for single cell RNA sequencing analysis

Umu, S. U.·Rapp Vander-Elst, K.·Karlsen, V. T.·Chouliara, M.·Baekkevold, E. S.·Jahnsen, F. L.·Domanska, D.
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Abstract

BackgroundSingle-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, non-expert users usually experience installation issues, a lack of critical functionality or batch analysis modes, and the steep learning curves of existing pipelines. ResultsWe 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. ConclusionAs 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.

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Umu, S. U., Rapp Vander-Elst, K., Karlsen, V. T., Chouliara, M., Baekkevold, E. S., Jahnsen, F. L., Domanska, D.. 2023-05-04. cellsnake: a user-friendly tool for single cell RNA sequencing analysis. https://doi.org/10.1101/2023.05.03.539204

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