InSituCor: exploring spatially correlated genes conditional on the cell type landscape
Name
13059_2025_Article_3554.pdf
Size
2.41 MB
Format
Adobe PDF
Checksum (MD5)
ca73e1bb5d34aba11b6c1f7fde6c09db
Author(s)
Danaher, Patrick
McGuire, Dan
Wu, Lidan
Patrick, Michael
Kroeppler, David
Zhai, Haiyan
Olgun, Deniz G.
Gong, Dennis
Cao, Jingyi
Hwang, William L.
Date Issued
April 24, 2025
Journal
Genome Biology
Publisher
BioMed Central
Citation
Danaher, P., McGuire, D., Wu, L. et al. InSituCor: exploring spatially correlated genes conditional on the cell type landscape. Genome Biol 26, 105 (2025).
Version
Final published version
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.
MIT Department
Broad Institute of MIT and Harvard
Harvard-MIT Program in Health Sciences and Technology
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1186/s13059-025-03554-1
