ArticleBMC genomics2019
Large-scale 3D chromatin reconstruction from chromosomal contacts.
Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
- Reconstructing the three-dimensional architecture of extrachromosomal DNA with ec3D.Nature communications · 2025Article
- Tensor-FLAMINGO unravels the complexity of single-cell spatial architectures of genomes at high-resolution.Nature communications · 2025Article
- Visualization of chromosomal reorganization induced by heterologous fusions in the mammalian nucleus.Nature communications · 2025Article
- geomeTriD: a Bioconductor package for interactive and integrative visualization of 3D structural model with multi-omics data.Bioinformatics advances · 2025Article
- ARGV: 3D genome structure exploration using augmented reality.BMC bioinformatics · 2024Article
- Inference of 3D genome architecture by modeling overdispersion of Hi-C data.Bioinformatics (Oxford, England) · 2023Article
- Unraveling the genomic basis of congenital heart disease.The Journal of clinical investigation · 2021Article
- Application of Hi-C and other omics data analysis in human cancer and cell differentiation research.Computational and structural biotechnology journal · 2021Review
- Computational methods for predicting 3D genomic organization from high-resolution chromosome conformation capture data.Briefings in functional genomics · 2020Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRecent advances in genome analysis have established that chromatin has preferred 3D conformations, which bring distant loci into contact. Identifying these contacts is important for us to understand possible interactions between these loci. This has motivated the creation of the Hi-C technology, which detects long-range chromosomal interactions. Distance geometry-based algorithms, such as ChromSDE and ShRec3D, have been able to utilize Hi-C data to infer 3D chromosomal structures. However, these algorithms, being matrix-based, are space- and time-consuming on very large datasets. A human genome of 100 kilobase resolution would involve ∼30,000 loci, requiring gigabytes just in storing the matrices.
resultsWe propose a succinct representation of the distance matrices which tremendously reduces the space requirement. We give a complete solution, called SuperRec, for the inference of chromosomal structures from Hi-C data, through iterative solving the large-scale weighted multidimensional scaling problem.
conclusionsSuperRec runs faster than earlier systems without compromising on result accuracy. The SuperRec package can be obtained from http://www.cs.cityu.edu.hk/~shuaicli/SuperRec .
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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.