ArticleScience advances2022
EagleC: A deep-learning framework for detecting a full range of structural variations from bulk and single-cell contact maps.
Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers.
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Who cites it
77 citing papers in PubMed.
- Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.Methods in molecular biology (Clifton, N.J.) · 2027Article
- Translocation-induced enhancer rewiring reveals cryptic oncogenic circuits in multiple myeloma.Science advances · 2026Article
- Spatial chromatin architecture and accessibility co-profiling of mammalian tissues.Nature methods · 2026Article
- Identification of differential topologically associating domains from low sequencing depth and pseudobulk chromatin contact maps.Genome research · 2026Article
- Overcoming Artificial Structures in Resolution-Enhanced Hi-C Data by Signal Decomposition and Multi-Scale Attention.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Origins and consequences of oncogenic 3D chromatin remodelling.Nature reviews. Cancer · 2026Review
- Article
- map3C: a computational tool for processing multiomic single-cell Hi-C data.Bioinformatics (Oxford, England) · 2026Article
- Robust and generalizable CNV detection for single-cell sequencing assays.Nucleic acids research · 2026Article
- Hi-C for genome-wide detection of enhancer-hijacking rearrangements in routine lymphoid cancer biopsies.Cell genomics · 2026Article
- Strand-seq and the future of personalized genomics.Nature genetics · 2026Review
- HaploC-tools reveal haplotype-specific chromosome conformation and chromatin states.Nature communications · 2026Article
- Convergent evolution of complex structural variants drives therapy resistance in metastatic prostate cancer.Genome biology · 2026Article
- Leveraging a spectrum of cytogenomics methods for profiling complex karyotypes in chronic lymphocytic leukemia.Human genomics · 2026Article
- Chromatin architecture and physical constriction cooperate in phenotype switching and cancer cell dissemination.bioRxiv : the preprint server for biology · 2026Article
- scCAPReSE: detection of large-scale genomic rearrangements from single-cell Hi-C based on few-shot learning.Genomics & informatics · 2026Article
- A method for structural variant detection using Hi-C contact matrix and neural networks.Scientific reports · 2026Article
- The 3D Genome Browser 2.0: an enhanced online platform for visualizing and analyzing 3D genome architecture.Nucleic acids research · 2026Article
- Recent advances in single-cell bioinformatics for inferring higher-order chromatin contact maps.BMB reports · 2025Review
- Excessive DNA Double-Strand Breaks-Associated 3D Genome Reorganization Contributes to Neural Tube Defects with Folate Deficiency.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
17 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors.
Funding
Abstract
The Hi-C technique has been shown to be a promising method to detect structural variations (SVs) in human genomes. However, algorithms that can use Hi-C data for a full-range SV detection have been severely lacking. Current methods can only identify interchromosomal translocations and long-range intrachromosomal SVs (>1 Mb) at less-than-optimal resolution. Therefore, we develop EagleC, a framework that combines deep-learning and ensemble-learning strategies to predict a full range of SVs at high resolution. We show that EagleC can uniquely capture a set of fusion genes that are missed by whole-genome sequencing or nanopore. Furthermore, EagleC also effectively captures SVs in other chromatin interaction platforms, such as HiChIP, Chromatin interaction analysis with paired-end tag sequencing (ChIA-PET), and capture Hi-C. We apply EagleC in more than 100 cancer cell lines and primary tumors and identify a valuable set of high-quality SVs. Last, we demonstrate that EagleC can be applied to single-cell Hi-C and used to study the SV heterogeneity in primary tumors.
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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.