Thin plate models to detect spatially variable genes
The goal of tpSVG is to detect and visualize spatial variation in the gene expression for spatially resolved transcriptomics data analysis. Specifically, tpSVG introduces a family of count-based models, with generalizable parametric assumptions such as Poisson distribution or negative binomial distribution. In addition, comparing to currently available count-based model for spatially resolved data analysis, the tpSVG models improves computational time, and hence greatly improves the applicability of count-based models in SRT data analysis.
