Spatial Registration is an analysis that compares the gene expression of groups in a query RNA-seq data set (typically spatially resolved RNA-seq or single cell RNA-seq) to groups in a reference spatially resolved RNA-seq data set (such annotated anatomical features).
For spatial data, this can be helpful to compare manual annotations, or annotating clusters. For scRNA-seq data it can check if a cell type might be more concentrated in one area or anatomical feature of the tissue.
The spatial annotation process correlates the \(t\)-statistics from the gene enrichment analysis between spatial features from the reference data set, with the \(t\)-statistics from the gene enrichment of features in the query data set. Pairs with high positive correlation show where similar patterns of gene expression are occurring and what anatomical feature the new spatial feature or cell population may map to.
Perform gene set enrichment analysis between spatial features (ex. anatomical features, histological layers) on reference spatial data set. Or access existing statistics.
Perform gene set enrichment analysis between features (ex. new annotations, data-driven clusters) on new query data set.
Correlate the \(t\)-statistics between the reference and query features.
Annotate new spatial features with the most strongly associated reference feature.
Plot correlation heat map to observe patterns between the two data sets.