SMASH: Scalable Method for Analyzing Spatial Heterogeneity of genes in spatial transcriptomics data

by Souvik Seal, Benjamin G. Bitler, Debashis Ghosh

In high-throughput spatial transcriptomics (ST) studies, it is of great interest to identify the genes whose level of expression in a tissue covaries with the spatial location of cells/spots. Such genes, also known as spatially variable genes (SVGs), can be crucial to the biological understanding of both structural and functional characteristics of complex tissues. Existing methods for detecting SVGs either suffer from huge computational demand or significantly lack statistical power. We propose a non-parametric method termed SMASH that achieves a balance between the above two problems. We compare SMASH with other existing methods in varying simulation scenarios demonstrating its superior statistical power and robustness. We apply the method to four ST datasets from different platforms uncovering interesting biological insights.

Source: PLoS Genetics - October 20, 2023 Category: Genetics & Stem Cells Authors: Souvik Seal Source Type: research