A Galaxy-based training resource for single-cell RNA-seq quality control and analyses

Background

It is not a trivial step to move from single-cell RNA-seq (scRNA-seq) data production to data analysis. There is a lack of intuitive training materials and easy-to-use analysis tools, and researchers can find it difficult to master the basics of scRNA-seq quality control and analysis.

Results

We have developed a range of easy-to-use scripts, together with their corresponding Galaxy wrappers, that make scRNA-seq training and analysis accessible to researchers previously daunted by the prospect of scRNA-seq analysis. The simple command-line tools and the point-and-click nature of Galaxy makes it easy to assess, visualise, and quality control scRNA-seq data.

Conclusion

We have developed a suite of scRNA-seq tools that can be used for both training and more in-depth analyses.

Data and Resources

Additional Info

Field Value
Author Etherington, Graham J
Last Updated November 20, 2019, 16:51 (UTC)
Created August 9, 2019, 11:29 (UTC)
Article Host Type publisher
Article Is Open Access true
Article License Type cc-by-nc-nd
Article Version Type publishedVersion
Citation Report https://scite.ai/reports/10.1101/724047
DOI 10.1101/724047
Date Last Updated 2019-08-05T21:22:47.644337
Evidence open (via page says license)
Funder code(s)
Journal Is Open Access false
Open Access Status hybrid
PDF URL https://www.biorxiv.org/content/biorxiv/early/2019/08/04/724047.full.pdf
Publisher URL https://doi.org/10.1101/724047