stJoincount

stJoincount facilitates the application of join count analysis to spatial transcriptomic data generated from the 10x Genomics Visium platform.

Key Features:

• Raster conversion: Converts a labeled spatial tissue map into a raster object in which each spatial feature is represented by a pixel coded by label assignment.
• Automatic parameter calculation: Automatically calculates optimal raster resolution and extent for the sample.
• Neighbor identification: Creates a neighbors list from the rasterized sample in which adjacent and diagonal neighbors for each pixel are identified.
• Binary spatial weights: Adds binary spatial weights to the neighbors list.
• Multi-categorical join count analysis: Tabulates "joins" between all possible combinations of label pairs.
• Statistical output: Returns observed join counts, expected count under conditions of spatial randomness, and variance calculated under non-free sampling.
• Z-score calculation: Calculates the z-score as the difference between observed and expected counts, divided by the square root of the variance.

Scientific Applications:

• Spatial transcriptomics analysis: Quantifies spatial correlation between clusters in spatial transcriptomic data from the 10x Genomics Visium platform.

Methodology:

The tool converts a labeled spatial tissue map into a raster object with automatic calculation of optimal raster resolution and extent, creates a neighbors list identifying adjacent and diagonal neighbors, adds binary spatial weights, and performs multi-categorical join count analysis to tabulate joins between all label pairs.