About

This resource is supported by Australian biocommons as part of the workflow commons, QCIF and Griffith university.

Who spatial sampler for?

These HowTos assume that you have already QC-ed, pre-processed and annotated celltype in your dataset, and are ready to ask questions of it. Alternatively, perhaps you are planning a spatial experiment and exploring what questions you might be able to ask.

NB: If you’re looking for how to get your data ready check out some other resources.

Spatial sampler is designed for:

• Newcomers to spatial omics: Check out the worked example, and try it on your own data
• Busy bioinformaticians: Know what test you want but don’t want to write the code again? Grab the code snippet and continue on.
• Training developers: This material is open and can be readily adapted for training - see here and here. Get in touch if you’d like to discuss.

Scope of spatial sampler HowTos

These examples emphasise practicality and the application of spatial omics as a tool for common analysis questions. They will never be a complete guide of what is possible. Each example presents just one way of doing things but there are many, many other approaches! These examples aim to provide a starting point which can be optimised or adapted to your needs.

Most HowTos use transcriptomic CosMx data, though approaches should be valid on other single-cell spatial platforms like Xenium, vizgen and STOmics, and may have applications in other omics.

Initial examples are mostly using Seurat, but more examples using the Bioconductor ecosystem are coming. All current examples are all in R – if you’re in a position to contribute python examples please get in touch!

Data

More information on the source datasets, including citations and preprocessing scripts, may be found on the data tab.

Getting in touch

Found a problem, got a question, a request or something to add? Log a github ticket here