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SCHNAPPs - Single Cell sHiNy APPlication(s)

View ORCID ProfileBernd Jagla, View ORCID ProfileVincent Rouilly, View ORCID ProfileMichel Puceat, View ORCID ProfileMilena Hasan
doi: https://doi.org/10.1101/2020.06.07.127274
Bernd Jagla
1Cytometry and Biomarkers UTechS, Institut Pasteur, Paris, France
2Hub Bioinformatique et Biostatistique, Département de Biologie Computationnelle – USR 3756 CNRS, Institut Pasteur, Paris, France
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  • For correspondence: bernd.jagla@pasteur.fr
Vincent Rouilly
3Datactix, 11 rue de Lourmel, 75015 Paris
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Michel Puceat
4Aix-Marseille University, INSERM U-1251, MMG, France
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Milena Hasan
1Cytometry and Biomarkers UTechS, Institut Pasteur, Paris, France
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  • ORCID record for Milena Hasan
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ABSTRACT

Motivation Single-cell RNA-sequencing (scRNAseq) experiments are becoming a standard tool for bench-scientists to explore the cellular diversity present in all tissues. On one hand, the data produced by scRNASeq is technically complex, with analytical workflows that are still very much an active field of bioinformatics research, and on the other hand, a wealth of biological background knowledge is often needed to guide the investigation. Therefore, there is an increasing need to develop applications geared towards bench-scientists to help them abstract the technical challenges of the analysis, so that they can focus on the Science at play. It is also expected that such applications should support closer collaboration between bioinformaticians and bench-scientists by providing reproducible science tools.

Results We present SCHNAPPs, a computer program designed to enable bench-scientists to autonomously explore and interpret single cell RNA-seq expression data and associated annotations. The Shiny-based application allows selecting genes and cells of interest, performing quality control, normalization, clustering, and differential expression analyses, applying standard workflows from Seurat (Stuart et al., 2019) or Scran (Lun et al., 2016) packages, and most of the common visualizations. An R-markdown report can be generated that tracks the modifications, and selected visualizations facilitating communication and reproducibility between bench-scientist and bioinformatician. The modular design of the tool allows to easily integrate new visualizations and analyses by bioinformaticians. We still recommend that a data analysis specialist oversees the analysis and interpretation.

Availability The SCHNAPPs application, docker file, and documentation are available on GitHub: https://c3bi-pasteur-fr.github.io/UTechSCB-SCHNAPPs; Example contribution are available at the following GitHub site: https://github.com/baj12/SCHNAPPsContributions.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://c3bi-pasteur-fr.github.io/UTechSCB-SCHNAPPs

  • http://github.com/baj12/SCHNAPPsContributions

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted June 09, 2020.
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SCHNAPPs - Single Cell sHiNy APPlication(s)
Bernd Jagla, Vincent Rouilly, Michel Puceat, Milena Hasan
bioRxiv 2020.06.07.127274; doi: https://doi.org/10.1101/2020.06.07.127274
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SCHNAPPs - Single Cell sHiNy APPlication(s)
Bernd Jagla, Vincent Rouilly, Michel Puceat, Milena Hasan
bioRxiv 2020.06.07.127274; doi: https://doi.org/10.1101/2020.06.07.127274

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