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...
Saved in:
| Main Authors: | Patrick Danaher, Dan McGuire, Lidan Wu, Michael Patrick, David Kroeppler, Haiyan Zhai, Deniz G. Olgun, Dennis Gong, Jingyi Cao, William L. Hwang, Joachim Schmid, Joseph M. Beechem |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-04-01
|
| Series: | Genome Biology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13059-025-03554-1 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multimodal sequencing of neoadjuvant nivolumab treatment in hepatocellular carcinoma reveals cellular and molecular immune landscape for drug response
by: Fanhong Zeng, et al.
Published: (2025-04-01) -
SC2Spa: a deep learning based approach to map transcriptome to spatial origins at cellular resolution
by: Linbu Liao, et al.
Published: (2025-06-01) -
STModule: identifying tissue modules to uncover spatial components and characteristics of transcriptomic landscapes
by: Ran Wang, et al.
Published: (2025-03-01) -
Using transcripts to refine image based cell segmentation with FastReseg
by: Lidan Wu, et al.
Published: (2025-08-01) -
Exploring the landscape of Parkinson’s disease transcriptomics: a quantitative review of research progress and future directions
by: Yiran Wang, et al.
Published: (2025-05-01)