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A Galaxy-based training resource for single-cell RNA-sequencing quality control and analyses
Graham J Etherington1, Nicola Soranzo1, Suhaib Mohammed2
1Earlham Institute, Norwich Research Park, Norwich NR4 7UZ, UK.
Gigascience
|December 12, 2019
Summary
Researchers can now easily perform single-cell RNA sequencing (scRNA-seq) analysis and quality control. New practical scripts and Galaxy wrappers simplify complex scRNA-seq data handling for all skill levels.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Single-cell RNA sequencing (scRNA-seq) data analysis presents significant challenges for researchers.
- A lack of intuitive training materials and user-friendly tools hinders mastery of scRNA-seq quality control and downstream analysis.
Purpose of the Study:
- To develop accessible tools for scRNA-seq training and data analysis.
- To simplify the quality control and visualization processes for scRNA-seq data.
Main Methods:
- Developed practical scripts with Galaxy wrappers for scRNA-seq analysis.
- Implemented a "visualize-filter-visualize" workflow using command-line tools.
- Utilized the Loom format for seamless data exchange between tools.
Main Results:
- Created accessible scRNA-seq training and quality control resources.
- Enabled easy assessment, visualization, and filtering of scRNA-seq data via Galaxy's interface.
- Facilitated scRNA-seq data analysis for researchers with limited prior experience.
Conclusions:
- A suite of scRNA-seq tools has been developed for both educational and analytical purposes.
- These tools lower the barrier to entry for scRNA-seq data analysis and quality control.
