InSituCor: exploring spatially correlated genes conditional on the cell type landscape
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.
Authors
- David Kroeppler
- William L. Hwang (ORCID: https://orcid.org/0000-0003-4514-8837)
- Deniz G. Olgun
- Dan McGuire
- Joseph Beechem (ORCID: https://orcid.org/0000-0001-8372-5899)
- Michael J. Patrick
- Joachim Schmid (ORCID: https://orcid.org/0009-0004-1580-7744)
- Dennis Gong (ORCID: https://orcid.org/0000-0003-4429-8593)
- Patrick Danaher (ORCID: https://orcid.org/0000-0002-2844-5883)
- Jingyi Cao
- Haiyan Zhai
- Lidan Wu
Institutions
- Broad Institute (US)
- Brigham and Women's Hospital (US)
- Harvard University (US)
- Bruker (United States) (US)
- Massachusetts General Hospital (US)
- Harvard–MIT Division of Health Sciences and Technology (US)
- Nanostring Technologies (United States) (US)
- Center for Cancer Research (US)
- Center for Systems Biology (US)
- University of Virginia (US)
Publication Details
- Journal
- Genome biology
- Published
- 2025-04-24
- DOI
- https://doi.org/10.1186/s13059-025-03554-1
- Citations
- 4
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 3.22
Funders
- Burroughs Wellcome Fund
- Pancreatic Cancer Action Network
- National Institutes of Health
- National Cancer Institute