ArticleComputational and structural biotechnology journal2022
CASPIAN: A method to identify chromatin topological associated domains based on spatial density cluster.
Article in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- TADShop: systematic benchmarking and identification of topologically associating domains.Nature methods · 2026Article
- EmbedTAD Using Graph Embedding and Unsupervised Learning to Identify TADs from High-Resolution Hi-C Data.Communications biology · 2025Article
- deepTAD: an approach for identifying topologically associated domains based on convolutional neural network and transformer model.Briefings in bioinformatics · 2025Article
- A method for chromatin domain partitioning based on hypergraph clustering.Computational and structural biotechnology journal · 2024Article
- Article
- [An identification method of chromatin topological associated domains based on spatial density clustering].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2024Article
- Clinical efficacy of Camrelizumab combined with first-line chemotherapy in extensive-stage small-cell lung cancer.Heliyon · 2024Article
- [Advances in methods and applications of single-cell Hi-C data analysis].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2023Article
- Pharmacogenomics: Driving Personalized Medicine.Pharmacological reviews · 2023Review
- TOAST: A novel method for identifying topologically associated domains based on graph auto-encoders and clustering.Computational and structural biotechnology journal · 2023Article
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6 authors.
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Abstract
With the development of Hi-C technology, the detection of topologically associated domains (TADs) boundaries plays an important role in exploring the relationship between gene structure and expression. However, a method that can identify accurate TAD boundaries from the Hi-C contact matrix with different resolutions is currently lacking. We proposed a method named CASPIAN that can identify chromatin TAD boundaries based on the spatial density clustering algorithm. CASPIAN requires few parameters to call TADs. This method is realized using the hierarchical density-based clustering method HDBSCAN, where the distance of pairwise bins is calculated based on three distance metrics (Euclidean, Manhattan, and Chebyshev distance metric) to adapt to the characteristics of the Hi-C contact matrix generated from simulation experiments or normalized methods. Our results show that, same as standard methods (e.g., Insulation Score, TopDom), CASPIAN can enrich factors related to promoting the gene expression, such as CTCF, H3K4me1, H3K4me3, RAD21, POLR2A, and SMC3. We also calculated the approximate proportion of various factors anchored at the TAD boundaries to observe the distribution of these factors surrounding the TAD boundaries. In conclusion, CASPIAN is an easy method to explore the relationship between transcription factors and TAD boundaries. CASPIAN is available online (https://gitee.com/ghaiyan/caspian).
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