Sarwar, Ameer, Rue, Mara, French, Leon, Cross, Helen, Chen, Xiaoyin, Gillis, Jesse (September 2024) Cross-expression analysis reveals patterns of coordinated gene expression in spatial transcriptomics. bioRxiv. ISSN 2692-8205 (Submitted)
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10.1101.2024.09.17.613579.pdf - Submitted Version Available under License Creative Commons Attribution. Download (3MB) | Preview |
Abstract
Spatial transcriptomics promises to transform our understanding of tissue biology by molecularly profiling individual cells in situ. A fundamental question they allow us to ask is how nearby cells orchestrate their gene expression. To investigate this, we introduce cross-expression, a novel framework for discovering gene pairs that coordinate their expression across neighboring cells. Just as co-expression quantifies synchronized gene expression within the same cells, cross-expression measures coordinated gene expression between spatially adjacent cells, allowing us to understand tissue gene expression programs with single cell resolution. Using this framework, we recover ligand-receptor partners and discover gene combinations marking anatomical regions. More generally, we create cross-expression networks to find gene modules with orchestrated expression patterns. Finally, we provide an efficient R package to facilitate cross-expression analysis, quantify effect sizes, and generate novel visualizations to better understand spatial gene expression programs.
| Item Type: | Paper |
|---|---|
| Subjects: | bioinformatics > genomics and proteomics > analysis and processing bioinformatics bioinformatics > genomics and proteomics |
| CSHL Authors: | |
| Communities: | CSHL labs > Gillis Lab |
| SWORD Depositor: | CSHL Elements |
| Depositing User: | CSHL Elements |
| Date: | 21 September 2024 |
| Date Deposited: | 09 Oct 2024 13:07 |
| Last Modified: | 09 Oct 2024 13:07 |
| PMCID: | PMC11429685 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/41702 |
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