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SnapFISH: a computational pipeline to identify chromatin loops from multiplexed DNA FISH data

Author

Listed:
  • Lindsay Lee

    (Cleveland Clinic Foundation)

  • Hongyu Yu

    (University of Wisconsin Madison
    University of Wisconsin Madison)

  • Bojing Blair Jia

    (University of California San Diego
    University of California San Diego)

  • Adam Jussila

    (University of California San Diego)

  • Chenxu Zhu

    (Ludwig Institute for Cancer Research
    New York Genome Center
    Institute for Computational Biomedicine, Weill Cornell Medicine)

  • Jiawen Chen

    (University of North Carolina)

  • Liangqi Xie

    (Lerner Research Institute, Cleveland Clinic Foundation
    Lerner Research Institute, Cleveland Clinic Foundation)

  • Antonina Hafner

    (Stanford University)

  • Shreya Mishra

    (Cleveland Clinic Foundation)

  • Duan Dennis Wang

    (Chapel Hill High School)

  • Caterina Strambio-De-Castillia

    (University of Massachusetts Chan Medical School)

  • Alistair Boettiger

    (Stanford University)

  • Bing Ren

    (Ludwig Institute for Cancer Research
    University of California San Diego)

  • Yun Li

    (University of North Carolina
    University of North Carolina
    University of North Carolina)

  • Ming Hu

    (Cleveland Clinic Foundation)

Abstract

Multiplexed DNA fluorescence in situ hybridization (FISH) imaging technologies have been developed to map the folding of chromatin fibers at tens of nanometers and up to several kilobases in resolution in single cells. However, computational methods to reliably identify chromatin loops from such imaging datasets are still lacking. Here we present a Single-Nucleus Analysis Pipeline for multiplexed DNA FISH (SnapFISH), to process the multiplexed DNA FISH data and identify chromatin loops. SnapFISH can identify known chromatin loops from mouse embryonic stem cells with high sensitivity and accuracy. In addition, SnapFISH obtains comparable results of chromatin loops across datasets generated from diverse imaging technologies. SnapFISH is freely available at https://github.com/HuMingLab/SnapFISH .

Suggested Citation

  • Lindsay Lee & Hongyu Yu & Bojing Blair Jia & Adam Jussila & Chenxu Zhu & Jiawen Chen & Liangqi Xie & Antonina Hafner & Shreya Mishra & Duan Dennis Wang & Caterina Strambio-De-Castillia & Alistair Boet, 2023. "SnapFISH: a computational pipeline to identify chromatin loops from multiplexed DNA FISH data," Nature Communications, Nature, vol. 14(1), pages 1-7, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40658-3
    DOI: 10.1038/s41467-023-40658-3
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    References listed on IDEAS

    as
    1. Leslie J. Mateo & Sedona E. Murphy & Antonina Hafner & Isaac S. Cinquini & Carly A. Walker & Alistair N. Boettiger, 2019. "Visualizing DNA folding and RNA in embryos at single-cell resolution," Nature, Nature, vol. 568(7750), pages 49-54, April.
    2. Jesse R. Dixon & Siddarth Selvaraj & Feng Yue & Audrey Kim & Yan Li & Yin Shen & Ming Hu & Jun S. Liu & Bing Ren, 2012. "Topological domains in mammalian genomes identified by analysis of chromatin interactions," Nature, Nature, vol. 485(7398), pages 376-380, May.
    3. Yodai Takei & Jina Yun & Shiwei Zheng & Noah Ollikainen & Nico Pierson & Jonathan White & Sheel Shah & Julian Thomassie & Shengbao Suo & Chee-Huat Linus Eng & Mitchell Guttman & Guo-Cheng Yuan & Long , 2021. "Integrated spatial genomics reveals global architecture of single nuclei," Nature, Nature, vol. 590(7845), pages 344-350, February.
    4. Miao Liu & Yanfang Lu & Bing Yang & Yanbo Chen & Jonathan S. D. Radda & Mengwei Hu & Samuel G. Katz & Siyuan Wang, 2020. "Multiplexed imaging of nucleome architectures in single cells of mammalian tissue," Nature Communications, Nature, vol. 11(1), pages 1-14, December.
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