ArticleCommunications biology2022
InterCellar enables interactive analysis and exploration of cell-cell communication in single-cell transcriptomic data.
Article in Communications biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Accurately Predicting Cell Type Abundance from Spatial Histology Image Through HPCell.Interdisciplinary sciences, computational life sciences · 2026Article
- Single cell analysis of muscle contracture in cerebral palsy reveals profibrotic and antimyogenic stem cell populations with altered cell-cell interactions.American journal of physiology. Cell physiology · 2026Article
- Spatial transcriptomics reveals injury-responsive compartments and coordinated immune-fibrotic signaling in ANCA-associated renal vasculitis.Frontiers in immunology · 2026Article
- Pericytes orchestrate a tumor-restraining microenvironment in glioblastoma.Nature communications · 2025Article
- A spatial map of MAPK-activated immunosuppressive myeloid populations in pediatric low-grade glioma.Nature immunology · 2025Article
- ETMR stem-like state and chemo-resistance are supported by perivascular cells at single-cell resolution.Nature communications · 2025Article
- Differential cellular communication inference framework for large-scale single-cell RNA-sequencing data.NAR genomics and bioinformatics · 2025Article
- New Insights and Implications of Cell-Cell Interactions in Developmental Biology.International journal of molecular sciences · 2025Review
- Lack of SMARCB1 expression characterizes a subset of human and murine peripheral T-cell lymphomas.Nature communications · 2024Article
- The diversification of methods for studying cell-cell interactions and communication.Nature reviews. Genetics · 2024Review
- Loss of LPAR6 and CAB39L dysregulates the basal-to-luminal urothelial differentiation program, contributing to bladder carcinogenesis.Cell reports · 2024Article
- CPPLS-MLP: a method for constructing cell-cell communication networks and identifying related highly variable genes based on single-cell sequencing and spatial transcriptomics data.Briefings in bioinformatics · 2024Article
- Single-cell sequencing reveals alterations in the peripheral blood mononuclear cell landscape and monocyte status during colorectal adenocarcinoma formation.Clinical and translational medicine · 2024Article
- Translational pathology in drug discovery.Frontiers in pharmacology · 2024Article
- Branched-chain keto acids promote an immune-suppressive and neurodegenerative microenvironment in leptomeningeal disease.bioRxiv : the preprint server for biology · 2023Article
- Article
- Use of Single Cell Transcriptomic Techniques to Study the Role of High-Risk Human Papillomavirus Infection in Cervical Cancer.Frontiers in immunology · 2022Article
- Single-cell multiomics revealed the dynamics of antigen presentation, immune response and T cell activation in the COVID-19 positive and recovered individuals.Frontiers in immunology · 2022Article
- Angiogenesis goes computational - The future way forward to discover new angiogenic targets?Computational and structural biotechnology journal · 2022Review
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Authors and funding
3 authors.
Funding
Abstract
Deciphering cell-cell communication is a key step in understanding the physiology and pathology of multicellular systems. Recent advances in single-cell transcriptomics have contributed to unraveling the cellular composition of tissues and enabled the development of computational algorithms to predict cellular communication mediated by ligand-receptor interactions. Despite the existence of various tools capable of inferring cell-cell interactions from single-cell RNA sequencing data, the analysis and interpretation of the biological signals often require deep computational expertize. Here we present InterCellar, an interactive platform empowering lab-scientists to analyze and explore predicted cell-cell communication without requiring programming skills. InterCellar guides the biological interpretation through customized analysis steps, multiple visualization options, and the possibility to link biological pathways to ligand-receptor interactions. Alongside convenient data exploration features, InterCellar implements data-driven analyses including the possibility to compare cell-cell communication from multiple conditions. By analyzing COVID-19 and melanoma cell-cell interactions, we show that InterCellar resolves data-driven patterns of communication and highlights molecular signals through the integration of biological functions and pathways. We believe our user-friendly, interactive platform will help streamline the analysis of cell-cell communication and facilitate hypothesis generation in diverse biological systems.
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