tpSVG

tpSVG detects and visualizes spatial variation in gene expression for spatially resolved transcriptomics data analysis using a family of count-based thin plate models.

Key Features:

• Count-based models: Introduces a family of count-based models with generalizable parametric assumptions including Poisson distribution or negative binomial distribution.
• Computational efficiency: Improves computational time compared to currently available count-based models for spatially resolved transcriptomics data analysis.

Scientific Applications:

• Spatially resolved transcriptomics data analysis: Detects and visualizes spatial variation in gene expression for SRT data analysis.

Methodology:

Thin plate models with count-based parametric assumptions.