ArticleMolecular systems biology2024
Identifying Spatial Co-occurrence in Healthy and InflAmed tissues (ISCHIA).
Article in Molecular systems biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Understanding heterogeneity in the pathogenesis and drug responses of ulcerative colitis through single-cell and spatial transcriptomics.Frontiers in immunology · 2026Pooled it
- Spatial transcriptomics reveals microenvironmental heterogeneity in osteoarthritic subchondral bone.Nature communications · 2026Article
- HIF1AJournal for immunotherapy of cancer · 2026Article
- Integrative multi-omics and machine learning reveals the spatial niche distribution and role of CYP27A1Frontiers in immunology · 2026Article
- Cell-cell interactions as predictive and prognostic markers for drug responses in cancer.Genome medicine · 2025Review
- APOA2 mediates immune therapy tolerance in hepatocellular carcinoma by inhibiting the antigen-presenting function of dendritic cells through the PPAR signaling pathway.Translational cancer research · 2025Article
- Disruption of DNA methylation underpins the neuroinflammation induced by targeted CNS radiotherapy.Brain : a journal of neurology · 2025Article
- Integrating single-cell and spatial transcriptomics reveals the cellular heterogeneity of vestibular schwannoma.NPJ precision oncology · 2025Article
- New Insights and Implications of Cell-Cell Interactions in Developmental Biology.International journal of molecular sciences · 2025Review
- Spatial transcriptomic analysis of primary and metastatic pancreatic cancers highlights tumor microenvironmental heterogeneity.Nature genetics · 2024Article
- Article
- Stress-free single-cell transcriptomic profiling and functional genomics of murine eosinophils.Nature protocols · 2024Review
- Identification of ligand and receptor interactions in CKD and MASH through the integration of single cell and spatial transcriptomics.PloS one · 2024Article
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
Sequencing-based spatial transcriptomics (ST) methods allow unbiased capturing of RNA molecules at barcoded spots, charting the distribution and localization of cell types and transcripts across a tissue. While the coarse resolution of these techniques is considered a disadvantage, we argue that the inherent proximity of transcriptomes captured on spots can be leveraged to reconstruct cellular networks. To this end, we developed ISCHIA (Identifying Spatial Co-occurrence in Healthy and InflAmed tissues), a computational framework to analyze the spatial co-occurrence of cell types and transcript species within spots. Co-occurrence analysis is complementary to differential gene expression, as it does not depend on the abundance of a given cell type or on the transcript expression levels, but rather on their spatial association in the tissue. We applied ISCHIA to analyze co-occurrence of cell types, ligands and receptors in a Visium dataset of human ulcerative colitis patients, and validated our findings at single-cell resolution on matched hybridization-based data. We uncover inflammation-induced cellular networks involving M cell and fibroblasts, as well as ligand-receptor interactions enriched in the inflamed human colon, and their associated gene signatures. Our results highlight the hypothesis-generating power and broad applicability of co-occurrence analysis on spatial transcriptomics data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.