A Galaxy-based training resource for single-cell RNA-seq quality control and analyses
This article has been Reviewed by the following groups
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- Evaluated articles (GigaScience)
Abstract
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.
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A version of this preprint has been published in the Open Access journal GigaScience (see paper https://doi.org/10.1093/gigascience/giz144), where the paper and peer reviews are published openly under a CC-BY 4.0 license.
These peer reviews were as follows:
Reviewer 1: http://dx.doi.org/10.5524/REVIEW.102961
Reviewer 2: http://dx.doi.org/10.5524/REVIEW.102962
Reviewer 3: http://dx.doi.org/10.5524/REVIEW.102963
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