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Consistency in large pharmacogenomic studies

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A Brief Communications Arising to this article was published on 30 November 2016

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Figure 1: Limitations of using a correlation metric for the assessment of concordance between the CGP and CCLE drug sensitivity data.

Change history

  • 13 December 2016

    The received date and affiliation details for author P.G. were corrected in the HTML.

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Author information

Authors and Affiliations

  1. Department of Medicine, The University of Chicago, Chicago, 60637, Illinois, USA

    Paul Geeleher, Eric R. Gamazon, Nancy J. Cox & R. Stephanie Huang

  2. Division of Genetic Medicine, Vanderbilt University, Nashville, 37232, Tennessee, USA

    Eric R. Gamazon & Nancy J. Cox

  3. Academic Medical Center, University of Amsterdam, Amsterdam, 1105 AZ, The Netherlands

    Eric R. Gamazon

  4. Department of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, Ireland

    Cathal Seoighe

Authors
  1. Paul Geeleher
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  2. Eric R. Gamazon
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  3. Cathal Seoighe
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  4. Nancy J. Cox
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  5. R. Stephanie Huang
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Corresponding authors

Correspondence to Nancy J. Cox or R. Stephanie Huang.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Table 1

This file shows a summary of the results reported with the Supplementary Data of CGP and CCLE for the 15 compounds assessed by Haibe-Kains et al. These results were obtained from either the CGP web portal (www.cancerrxgene.org) or the supplementary tables S6 & S7 or supplementary figure 9 provided with the publication of the CCLE data. These already published results show a very clear trend of both studies reliably identifying many canonical drug targets. (XLSX 15 kb)

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Geeleher, P., Gamazon, E., Seoighe, C. et al. Consistency in large pharmacogenomic studies. Nature 540, E1–E2 (2016). https://doi.org/10.1038/nature19838

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