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FastClone is a probabilistic tool for deconvoluting tumor heterogeneity in bulk-sequencing samples

Author

Listed:
  • Yao Xiao

    (University of Michigan)

  • Xueqing Wang

    (University of Michigan)

  • Hongjiu Zhang

    (University of Michigan
    Microsoft Inc.)

  • Peter J. Ulintz

    (University of Michigan)

  • Hongyang Li

    (University of Michigan)

  • Yuanfang Guan

    (University of Michigan
    University of Michigan)

Abstract

Dissecting tumor heterogeneity is a key to understanding the complex mechanisms underlying drug resistance in cancers. The rich literature of pioneering studies on tumor heterogeneity analysis spurred a recent community-wide benchmark study that compares diverse modeling algorithms. Here we present FastClone, a top-performing algorithm in accuracy in this benchmark. FastClone improves over existing methods by allowing the deconvolution of subclones that have independent copy number variation events within the same chromosome regions. We characterize the behavior of FastClone in identifying subclones using stage III colon cancer primary tumor samples as well as simulated data. It achieves approximately 100-fold acceleration in computation for both simulated and patient data. The efficacy of FastClone will allow its application to large-scale data and clinical data, and facilitate personalized medicine in cancers.

Suggested Citation

  • Yao Xiao & Xueqing Wang & Hongjiu Zhang & Peter J. Ulintz & Hongyang Li & Yuanfang Guan, 2020. "FastClone is a probabilistic tool for deconvoluting tumor heterogeneity in bulk-sequencing samples," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-18169-2
    DOI: 10.1038/s41467-020-18169-2
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    Cited by:

    1. Georgette Tanner & David R. Westhead & Alastair Droop & Lucy F. Stead, 2021. "Benchmarking pipelines for subclonal deconvolution of bulk tumour sequencing data," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    2. Sebastian Wagner & Christoph Baldow & Andrea Calabria & Laura Rudilosso & Pierangela Gallina & Eugenio Montini & Daniela Cesana & Ingmar Glauche, 2022. "Clonal reconstruction from co-occurrence of vector integration sites accurately quantifies expanding clones in vivo," Nature Communications, Nature, vol. 13(1), pages 1-12, December.

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