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Mutation Clusters from Cancer Exome

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  • Zura Kakushadze
  • Willie Yu

Abstract

We apply our statistically deterministic machine learning/clustering algorithm *K-means (recently developed in https://ssrn.com/abstract=2908286) to 10,656 published exome samples for 32 cancer types. A majority of cancer types exhibit mutation clustering structure. Our results are in-sample stable. They are also out-of-sample stable when applied to 1,389 published genome samples across 14 cancer types. In contrast, we find in- and out-of-sample instabilities in cancer signatures extracted from exome samples via nonnegative matrix factorization (NMF), a computationally costly and non-deterministic method. Extracting stable mutation structures from exome data could have important implications for speed and cost, which are critical for early-stage cancer diagnostics such as novel blood-test methods currently in development.

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  • Zura Kakushadze & Willie Yu, 2017. "Mutation Clusters from Cancer Exome," Papers 1707.08504, arXiv.org.
    • Handle: RePEc:arx:papers:1707.08504
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    References listed on IDEAS

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    1. Daniel D. Lee & H. Sebastian Seung, 1999. "Learning the parts of objects by non-negative matrix factorization," Nature, Nature, vol. 401(6755), pages 788-791, October.
    2. Zura Kakushadze & Willie Yu, 2016. "Statistical Industry Classification," Journal of Risk & Control, Risk Market Journals, vol. 3(1), pages 17-65.
    3. Sarah B. Ng & Emily H. Turner & Peggy D. Robertson & Steven D. Flygare & Abigail W. Bigham & Choli Lee & Tristan Shaffer & Michelle Wong & Arindam Bhattacharjee & Evan E. Eichler & Michael Bamshad & D, 2009. "Targeted capture and massively parallel sequencing of 12 human exomes," Nature, Nature, vol. 461(7261), pages 272-276, September.
    4. Zura Kakushadze & Willie Yu, 2016. "Statistical Risk Models," Papers 1602.08070, arXiv.org, revised Jan 2017.
    5. Kakushadze, Zura & Yu, Willie, 2016. "Factor models for cancer signatures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 527-559.
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    Cited by:

    1. Zura Kakushadze & Willie Yu, 2020. "Machine Learning Treasury Yields," Bulletin of Applied Economics, Risk Market Journals, vol. 7(1), pages 1-65.
    2. Zura Kakushadze & Willie Yu, 2020. "Machine Learning Treasury Yields," Papers 2003.05095, arXiv.org.

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