IntegrateRigor: annotation-free integration optimization for cell identity recovery reveals cancer-immune interface niches

Integrating single-cell and spatial transcriptomics data across batches is essential for recovering comparable cell identities (including cell types, subtypes, and states) as a prerequisite for downstream analyses in multi-condition and large-scale studies. This task remains challenging because between-batch variation removal often conflicts with cell identity preservation, and current methods typically rely on generic highly variable gene selection and lack principled metrics for hyperparameter tuning when cell identity annotations are unavailable. Together, these limitations often lead to over-integration, which merges biologically distinct cell identities, or under-integration, which leav