Harmonizing single-cell 3D genome data with STARK and scNucleome
Single-cell three-dimensional genome sequencing (sc3DG-seq) reveals genome regulation and heterogeneity in various biological processes, but a universal analysis tool is lacking. Here we present STARK, a versatile toolkit for processing, quality control, and analysis of diverse sc3DG-seq data. Utilizing STARK, we benchmark 15 technologies, quantitatively comparing their strengths and limitations. We also develop EmptyCells to filter empty barcodes and introduce Spatial Structure Capture Efficiency (SSCE) to assess chromatin structure capture quality. Additionally, we establish scNucleome, a uniformly processed repository of sc3DG-seq datasets, to serve as a foundational resource for future 3D genome research.
Authors
- Ruixiang Gao (ORCID: https://orcid.org/0000-0003-3817-1473)
- Xiaoqi Zheng (ORCID: https://orcid.org/0000-0002-1832-4404)
- H P Zhu
- F. P. Ten
- Yujuan Wang (ORCID: https://orcid.org/0000-0002-0404-3599)
- Sun Yuanchen
- Ming Xu
- Nana Wei
- Chunge Zhong
- KangWen Cai
- Futing Lai
- Wen-Jie Jiang
- An Liu
Institutions
- Shanghai Jiao Tong University (CN)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Peking University (CN)
- Peking University Cancer Hospital (CN)
- Ministry of Education (ET)
- Center for Life Sciences (CN)
- Northeastern University (CN)
Publication Details
- Journal
- Genome biology
- Published
- 2026-01-21
- DOI
- https://doi.org/10.1186/s13059-026-03938-x
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00