Version Compatibility

Reference examples tested with: squidpy 1.5+, scanpy 1.10+, anndata 0.10+, spatialdata 0.2+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Spatial Preprocessing

"QC and normalize my spatial data" -> Flag and remove low-quality spots/cells, then put counts on a scale fit for downstream domain and marker analysis -- but the right QC floors and the right normalization both depend on which side of the platform fork the data sits.

• Sequencing/spot (Visium, Visium HD, Slide-seq, Stereo-seq): a spot/bin is mini-bulk over 1-10 cells; QC on UMI/spot, genes/spot, mito-%, cells/spot; normalization must respect that library size tracks cellularity.
• Imaging/in-situ (Xenium, MERSCOPE/MERFISH, CosMx, seqFISH): a cell is segmentation-derived, carries tens-to-low-hundreds of transcripts over a TARGETED panel; QC on a low transcript floor, cell area, and negative-control FDR; normalization must not be gene-count-based.

The platform-class fork (decide this first)

The first question on any spatial dataset is which assay family produced it, because it changes every QC threshold and the entire normalization decision.