Working with Galaxy
If it is desirable to perform all processing in Galaxy1 , it should not be a problem for smaller experiments with a 1:1 comparisons between samples. For experiments with a large number of samples, and also for complex comparisons (e.g. 2x2 factorial design), Galaxy may not work as well; we instead recommend learning and using the command line tools and R/Bioconductor. However, Galaxy can be used to test parameter settings on a subset of the data, prior to switching over to command line for the whole analysis. Another issue of note, though Galaxy is quite good with data provenance,the latest versions of tools may not be available in Galaxy’s Tool Shed (in particular those available in R/Bioconductor); In most cases Galaxy’s excellent data provenance tracking will keep track of the versions used, so please make a note of the version numbers.
The Galaxy Tool Shed lists all tools currently available through Galaxy. Tools available in Galaxy mentioned above include:
- FASTQC
- STAR
- featureCounts
- Trimmomatic, Trim_galore
- Picard
- edgeR, DESeq2
- Kallisto
- Salmon
Bibliography
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Afgan, E., Baker, D., Batut, B., Van Den Beek, M., Bouvier, D., Čech, M., … & Guerler, A. (2018). The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update. Nucleic acids research, 46(W1), W537-W544. ↩
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