The Spatial Transcriptomics Toolkit: Memory, Clustering, and Deconvolution

In this episode, Alex and Lorena tackle the computational challenges of spatial transcriptomics. Learn how BPCells can help you work with millions of cells without needing terabytes of RAM, discover how Banksy's neighborhood-aware clustering reveals tissue architecture, and explore RCTD's approach to cell type deconvolution in spatially-resolved data. Plus, Lorena reviews Positron, the new R-friendly IDE that's catching attention in the bioinformatics community.

https://github.com/bnprks/BPCells

https://github.com/prabhakarlab/Banksy

https://github.com/dmcable/spacexr

https://github.com/bcbio/spatial-reports

https://github.com/seandavi/awesome-single-cell

https://positron.posit.co/

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