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


ABSTRACT: BACKGROUND:It is not a trivial step to move from single-cell RNA-sequencing (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 the later analysis. RESULTS:We have developed a range of practical scripts, together with their corresponding Galaxy wrappers, that make scRNA-seq training and quality control accessible to researchers previously daunted by the prospect of scRNA-seq analysis. We implement a "visualize-filter-visualize" paradigm through simple command line tools that use the Loom format to exchange data between the tools. The point-and-click nature of Galaxy makes it easy to assess, visualize, and filter scRNA-seq data from short-read sequencing data. CONCLUSION:We have developed a suite of scRNA-seq tools that can be used for both training and more in-depth analyses.

SUBMITTER: Etherington GJ 

PROVIDER: S-EPMC6905351 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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

Etherington Graham J GJ   Soranzo Nicola N   Mohammed Suhaib S   Haerty Wilfried W   Davey Robert P RP   Palma Federica Di FD  

GigaScience 20191201 12


<h4>Background</h4>It is not a trivial step to move from single-cell RNA-sequencing (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 the later analysis.<h4>Results</h4>We have developed a range of practical scripts, together with their corresponding Galaxy wrappers, that make scRNA-seq training and quality control accessible to r  ...[more]

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