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Robust analysis of allele-specific copy number alterations from scRNA-seq data with XClone

Author

Listed:
  • Rongting Huang

    (The University of Hong Kong)

  • Xianjie Huang

    (The University of Hong Kong
    Hong Kong Science and Technology Park)

  • Yin Tong

    (The University of Hong Kong, Queen Mary Hospital
    Centre for Oncology and Immunology, Hong Kong Science Park)

  • Helen Y. N. Yan

    (The University of Hong Kong, Queen Mary Hospital
    Centre for Oncology and Immunology, Hong Kong Science Park)

  • Suet Yi Leung

    (The University of Hong Kong, Queen Mary Hospital
    Centre for Oncology and Immunology, Hong Kong Science Park
    The University of Hong Kong
    The University of Hong Kong)

  • Oliver Stegle

    (German Cancer Research Center (DKFZ)
    European Molecular Biology Laboratory)

  • Yuanhua Huang

    (The University of Hong Kong
    Hong Kong Science and Technology Park
    The University of Hong Kong)

Abstract

Somatic copy number alterations (CNAs) are major mutations that contribute to the development and progression of various cancers. Despite a few computational methods proposed to detect CNAs from single-cell transcriptomic data, the technical sparsity of such data makes it challenging to identify allele-specific CNAs, particularly in complex clonal structures. In this study, we present a statistical method, XClone, that strengthens the signals of read depth and allelic imbalance by effective smoothing on cell neighborhood and gene coordinate graphs to detect haplotype-aware CNAs from scRNA-seq data. By applying XClone to multiple datasets with challenging compositions, we demonstrated its ability to robustly detect different types of allele-specific CNAs and potentially indicate whole genome duplication, therefore enabling the discovery of corresponding subclones and the dissection of their phenotypic impacts.

Suggested Citation

  • Rongting Huang & Xianjie Huang & Yin Tong & Helen Y. N. Yan & Suet Yi Leung & Oliver Stegle & Yuanhua Huang, 2024. "Robust analysis of allele-specific copy number alterations from scRNA-seq data with XClone," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-51026-0
    DOI: 10.1038/s41467-024-51026-0
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    References listed on IDEAS

    as
    1. Akdes Serin Harmanci & Arif O. Harmanci & Xiaobo Zhou, 2020. "CaSpER identifies and visualizes CNV events by integrative analysis of single-cell or bulk RNA-sequencing data," Nature Communications, Nature, vol. 11(1), pages 1-16, December.
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    3. Darlan C. Minussi & Michael D. Nicholson & Hanghui Ye & Alexander Davis & Kaile Wang & Toby Baker & Maxime Tarabichi & Emi Sei & Haowei Du & Mashiat Rabbani & Cheng Peng & Min Hu & Shanshan Bai & Yu-w, 2021. "Breast tumours maintain a reservoir of subclonal diversity during expansion," Nature, Nature, vol. 592(7853), pages 302-308, April.
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