Version Compatibility

Reference examples tested with: muon 0.1+, mudata 0.2+, scanpy 1.10+, anndata 0.10+, mofapy2 0.7+, paste-bio 1.4+

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 Multi-omics Integration

"Integrate my spatial RNA with protein / ATAC / a histone mark" -> Decide whether the modalities are co-measured on the SAME pixels or come from DIFFERENT sections, then either build one joint representation or register two distinct cell populations.

• Same pixel (vertical): muon/mudata container -> muon.tl.mofa joint factors, or WNN-style per-modality weighting.
• Different sections (diagonal): paste/paste2 (optimal-transport alignment), STalign (diffeomorphic registration), GPSA (common coordinate).

Governing Principle

Serial-section modalities are DIFFERENT cells -- integration across them is registration, not coupling. A z-step of even 5-10 um lands on a different cell population, so RNA on section N and ATAC on section N+1 share NO cell. Aligning them (PASTE/STalign/GPSA) produces an approximate coordinate correspondence between distinct populations, never a cell-to-cell correspondence. Any cross-modality "coupling" read off a registered pair is a statistical imputation across non-identical cells, not a measurement. The single most-abused move in this subfield is presenting diagonal, registration-based integration with the confident language of same-cell co-measurement (Vandereyken 2023 Nat Rev Genet).