Package: tpSVG 1.3.0

tpSVG: 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.

Authors:Boyi Guo [aut, cre], Lukas M. Weber [ctb], Stephanie C. Hicks [aut]