InSituCor: exploring spatially correlated genes conditional on the cell type landscape
Abstract In spatial transcriptomics data, spatially correlated genes promise to reveal high-interest phenomena like cell–cell interactions and latent variables. But in practice, most spatial correlations arise from the spatial arrangement of cell types, obscuring the more interesting relationships w...
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| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-04-01
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| Series: | Genome Biology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13059-025-03554-1 |
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| Summary: | Abstract In spatial transcriptomics data, spatially correlated genes promise to reveal high-interest phenomena like cell–cell interactions and latent variables. But in practice, most spatial correlations arise from the spatial arrangement of cell types, obscuring the more interesting relationships we hope to discover. We introduce InSituCor, a toolkit for discovering modules of spatially correlated genes. InSituCor returns only correlations not explainable by already-known factors like the cell type landscape; this spares precious analyst effort. 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. |
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| ISSN: | 1474-760X |