scientific-spatial-multiomics

Integrating spatial transcriptomics and proteomics data for co-localization requires aligning RNA and protein modalities, computing space-aware co-detection, and constructing neighborhood graphs to identify spatial niches.

Aligning MERFISH and CODEX datasets for spatial niche discovery involves modality alignment, neighborhood graph construction, and Leiden-based clustering to derive spatially co-localized cellular communities.

Yes, Leiden clustering constructs neighborhood graphs from spatial multiomics data to detect community structures and derive spatial niches, requiring optional dependencies on igraph and leidenalg.

The spatial multiomics pipeline supports Visium data for end-to-end analysis, orchestrating data loading, modality alignment, co-detection, and spatial community detection.

Yes, performing Leiden-based spatial community detection requires installing the optional dependencies igraph and leidenalg to construct and cluster neighborhood graphs.

Spatial multiomics alignment fails without matching RNA and protein modalities because co-detection analysis and neighborhood graph construction depend on both datasets being present and correctly loaded.