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Peer-reviewedCC BYAdvanced science (Weinheim, Baden-Wurttemberg, Germany)

STRIDE: A Sequencing Depth Robust Metric for Sparse Chromosome Conformation Capture Data Comparison.

  • Bingxiang Xu1,2
  • Xiaomeng Gao3
  • Weichu Tao2
  • Zhihua Zhang4,5,6
  • Feifei Li7
7 affiliations
  1. 1Key Laboratory of Hebei Province for Molecular Biophysics, Institute of Biophysics, School of Health Science & Biomedical Engineering, Hebei University of Technology, Tianjin, China.
  2. 2School of Exercise and Health, Shanghai University of Sport, Shanghai, China.
  3. 3Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, California, USA.
  4. 4China National Center for Bioinformation, Beijing, China.
  5. 5Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.
  6. 6School of Life Science, University of Chinese Academy of Sciences, Beijing, China.
  7. 7Division of Cell, Developmental and Integrative Biology, School of Medicine, South China University of Technology, Guangzhou, China.
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Abstract

High-throughput chromatin conformation capture technologies, such as Hi-C and its derivatives, have revolutionized the study of 3D genome organization. However, the robustness of contact-frequency-based analyses to sequencing depth remains a major challenge, particularly for sparse datasets such as single-cell Hi-C. To overcome this challenge, we present a novel computational framework that employs the mean first passage time (MFPT) from Markov chain theory to convert chromatin contact matrices into a graph-based effective distance representation. We demonstrate that the MFPT representation is empirically more robust to sequencing-depth reduction and supports reliable downstream 3D genomic analyses, including TAD and chromatin loop detection, differential chromatin contact analysis, as well as the imputation and representation of sparse single-cell Hi-C data. Building on this representation, we developed STRIDE (spatial topological representation of interaction distance evaluation), a library similarity metric that does not require dataset-specific parameter optimization. STRIDE is robust to sparse and noisy data and shows improved resilience to technical variation, thereby facilitating accurate identification of cellular states and developmental trajectories in the datasets analyzed. Together, the MFPT representation and STRIDE provide a robust computational framework for sequencing-depth-resilient analysis of 3D genome organization.

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Cite

BibTeXRIS
BibTeX
@article{xu2026stride,
  title = {{STRIDE: A Sequencing Depth Robust Metric for Sparse Chromosome Conformation Capture Data Comparison.}},
  author = {Bingxiang Xu and Xiaomeng Gao and Weichu Tao and Zhihua Zhang and Feifei Li},
  journal = {Advanced science (Weinheim, Baden-Wurttemberg, Germany)},
  year = {2026},
  month = oct,
  doi = {10.1002/advs.78529},
  url = {https://europepmc.org/article/MED/42949804},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - STRIDE: A Sequencing Depth Robust Metric for Sparse Chromosome Conformation Capture Data Comparison.
AU  - Bingxiang Xu
AU  - Xiaomeng Gao
AU  - Weichu Tao
AU  - Zhihua Zhang
AU  - Feifei Li
PY  - 2026
DA  - 2026/10/28
JO  - Advanced science (Weinheim, Baden-Wurttemberg, Germany)
DO  - 10.1002/advs.78529
UR  - https://europepmc.org/article/MED/42949804
AB  - High-throughput chromatin conformation capture technologies, such as Hi-C and its derivatives, have revolutionized the study of 3D genome organization. However, the robustness of contact-frequency-based analyses to sequencing depth remains a major challenge, particularly for sparse datasets such as single-cell Hi-C. To overcome this challenge, we present a novel computational framework that employs the mean first passage time (MFPT) from Markov chain theory to convert chromatin contact matrices into a graph-based effective distance representation. We demonstrate that the MFPT representation is empirically more robust to sequencing-depth reduction and supports reliable downstream 3D genomic analyses, including TAD and chromatin loop detection, differential chromatin contact analysis, as well as the imputation and representation of sparse single-cell Hi-C data. Building on this representation, we developed STRIDE (spatial topological representation of interaction distance evaluation), a library similarity metric that does not require dataset-specific parameter optimization. STRIDE is robust to sparse and noisy data and shows improved resilience to technical variation, thereby facilitating accurate identification of cellular states and developmental trajectories in the datasets analyzed. Together, the MFPT representation and STRIDE provide a robust computational framework for sequencing-depth-resilient analysis of 3D genome organization.
SN  - 2198-3844
ER  -