InSituCor: a toolkit for discovering non-trivial spatial correlations in spatial transcriptomics

Abstract

AbstractSpatial transcriptomics presents the best kind of problem: how to find the many biological insights hidden within complex datasets. Spatially correlated genes can reveal high-interest phenomena like cell-cell interactions and latent variables. We introduce InSituCor, a toolkit for discovering modules of spatially correlated genes. A major contribution is that InSituCor returns only correlations not explainable by obvious factors like the cell type landscape; this spares precious analyst effort for non-trivial findings. InSituCor supports both unbiased discovery of whole-dataset correlations and knowledge-driven exploration of genes of interest. As a special case, it evaluates ligand-receptor pairs for spatial co-regulation.