Gone is the pre-annotated, high quality tutorial data - now you have real, messy data to deal with. You have decisions to make and parameters to decide. This learning pathway challenges you to replicate a published analysis as if this were your own dataset. You will be introduced to a few more tools available for scRNA-seq in Galaxy. Finally, if our tool offerings are not enough for you, you will be directed towards how to use coding notebooks within Galaxy, setting you up to analyse scRNA-seq in R or python notebooks.

The data is messy. The decisions are tough. The interpretation is meaningful. Come here to advance your single cell skills! Note that you get two options for inferring trajectories.

For support throughout these tutorials, join our Galaxy single cell chat group on Matrix to ask questions!

New to Galaxy and/or the field of scRNA-seq? Follow this learning path to get familiar with the basics!