Selecting precise reference normal tissue samples for cancer research using a deep learning approach.

Journal: BMC medical genomics
PMID: 30704474

Abstract

BACKGROUND: Normal tissue samples are often employed as a control for understanding disease mechanisms, however, collecting matched normal tissues from patients is difficult in many instances. In cancer research, for example, the open cancer resources such as TCGA and TARGET do not provide matched tissue samples for every cancer or cancer subtype. The recent GTEx project has profiled samples from healthy individuals, providing an excellent resource for this field, yet the feasibility of using GTEx samples as the reference remains unanswered.

Authors

  • William Z D Zeng
    Institute for Computational Health Sciences, University of California, San Francisco, CA, USA.
  • Benjamin S Glicksberg
    The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, 770 Lexington Ave, 15th Fl, New York, NY, 10065, USA.
  • Yangyan Li
    Shandong University, Qingdao, Shandong, China.
  • Bin Chen
    Department of Otorhinolaryngology, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University, Shanghai 200233, China.

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