Transforming Raw Spatial Data into Standardized, Reproducible, & Interoperable Insights to Expedite Spatial Biology Adoption
- Building confidence in cell segmentation — and understanding how algorithm choice impacts what you see and miss
- Aligning cell definitions and annotations across spatial, single-cell, and multi-omics datasets to speak a common language and improve interoperability
- Reconciling pathology insight with spatial-omics molecular resolution to build robust spatial niches