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<p>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.</p>

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Harmonizing single-cell 3D genome data with STARK and scNucleome

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月21日

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  • Wen-Jie Jiang,
  • KangWen Cai,
  • YuanChen Sun,
  • An Liu,
  • HanWen Zhu,
  • RuiXiang Gao,
  • Chunge Zhong,
  • Nana Wei,
  • Futing Lai,
  • Teng Fei,
  • Yu-Juan Wang,
  • Xiaoqi Zheng,
  • Ming Xu,
  • Hua-Jun Wu

摘要

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.