bioRxivBioinformaticsPreprint
InSituCor: a toolkit for discovering non-trivial spatial correlations in spatial transcriptomics
Patrick J. DanaheriD, Dan McGuire, Michael J. Patrick, David Kroeppler, Haiyan Zhai, Joachim SchmidiD, Joseph BeechemiD
Abstract
Spatial 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.
- assay: spatial transcriptomics
- research focus: cell-cell communication
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 5
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