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Safikhani et al. reply

Nature volume 540, pages E11–E12 (2016)Cite this article

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replying to M. Bouhaddou et al. Nature 540, 10.1038/nature20580 (2016).

In the accompanying Comment1, the authors make two main claims: (1) that viability metrics computed over the drug concentration range shared between datasets yield higher consistency than the same metrics computed over the full, often only partially overlapping, drug concentration range; and (2) that binary drug sensitivity classification (insensitive versus sensitive) as determined by manual curators increases the consistency of pharmacological profiles between the Cancer Genome Project (CGP)2 and Cancer Cell Line Encyclopedia (CCLE)3. We appreciate the innovative approach followed by the authors, and our reanalysis confirms the marginal, but statistically significant, increase in consistency achieved through the use of viability metrics computed across a reduced but common range. However, our results indicate that manual classification of drug dose–response curves does not significantly increase the agreement between drug sensitivity calls compared to computational approaches. Notably, it is unclear whether the authors’ manual approach will improve reproducibility of the biomarker discovery process, as collapsing of complex curves into discrete categories may result in a substantial information loss. Here we provide specific responses to the main results reported by Bouhaddou et al.1

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References

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Authors and Affiliations

  1. Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario M5G 2M9, Canada.email: benjamin.haibe.kains@utoronto.ca,

    Zhaleh Safikhani, Petr Smirnov, Mark Freeman & Benjamin Haibe-Kains

  2. Department of Medical Biophysics, University of Toronto, Toronto, M5G 1L7, Ontario, Canada

    Zhaleh Safikhani & Benjamin Haibe-Kains

  3. Institut de recherches cliniques de Montréal, Montreal, H2W 1R7, Quebec, Canada

    Nehme El-Hachem

  4. Hospital for Sick Children, Toronto, M5G 1X8, Ontario, Canada

    Anna Goldenberg

  5. Department of Computer Science, University of Toronto, Toronto, M5S 2E4, Ontario, Canada

    Anna Goldenberg & Benjamin Haibe-Kains

  6. The Francis Crick Institute, University College London, London, NW1 1AT, UK

    Nicolai J. Birkbak

  7. Beth Israel Deaconess Medical Center, Boston, 02215, Massachusetts, USA

    Andrew H. Beck

  8. Harvard Medical School, Boston, 02115, Massachusetts, USA

    Andrew H. Beck & Hugo J. W. L. Aerts

  9. Dana-Farber Cancer Institute, Boston, 02115, Massachusetts, USA

    Hugo J. W. L. Aerts & John Quackenbush

  10. Brigham and Women’s Hospital, Boston, 02115, Massachusetts, USA

    Hugo J. W. L. Aerts

  11. Harvard School of Public Health, Boston, 02115, Massachusetts, USA

    John Quackenbush

  12. Ontario Institute of Cancer Research, Toronto, M5G 1L7, Ontario, Canada

    Benjamin Haibe-Kains

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Safikhani, Z., El-Hachem, N., Smirnov, P. et al. Safikhani et al. reply. Nature 540, E11–E12 (2016). https://doi.org/10.1038/nature20581

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