ArticleFrontiers in genetics2023
RobustCCC: a robustness evaluation tool for cell-cell communication methods.
Article in Frontiers in genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Advances in sex-specific single-cell transcriptomic profiling in Parkinson's disease.Journal of Parkinson's disease · 2026Review
- Single-cell T-cell landscape in atherosclerosis: implications for targeted therapy and beyond.Journal of translational medicine · 2026Review
- Advances and challenges in cell-cell communication inference: a comprehensive review of tools, resources, and future directions.Briefings in bioinformatics · 2025Review
- New Insights and Implications of Cell-Cell Interactions in Developmental Biology.International journal of molecular sciences · 2025Review
- The diversification of methods for studying cell-cell interactions and communication.Nature reviews. Genetics · 2024Review
- Integrative analysis of single-cell transcriptomic and multilayer signaling networks in glioma reveal tumor progression stage.Frontiers in genetics · 2024Article
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4 authors.
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Abstract
Cell-cell communication (CCC) inference has become a routine task in single-cell data analysis. Many computational tools are developed for this purpose. However, the robustness of existing CCC methods remains underexplored. We develop a user-friendly tool, RobustCCC, to facilitate the robustness evaluation of CCC methods with respect to three perspectives, including replicated data, transcriptomic data noise and prior knowledge noise. RobustCCC currently integrates 14 state-of-the-art CCC methods and 6 simulated single-cell transcriptomics datasets to generate robustness evaluation reports in tabular form for easy interpretation. We find that these methods exhibit substantially different robustness performances using different simulation datasets, implying a strong impact of the input data on resulting CCC patterns. In summary, RobustCCC represents a scalable tool that can easily integrate more CCC methods, more single-cell datasets from different species (e.g., mouse and human) to provide guidance in selecting methods for identification of consistent and stable CCC patterns in tissue microenvironments. RobustCCC is freely available at https://github.com/GaoLabXDU/RobustCCC.
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