Automated post-run analysis of arrayed quantitative PCR amplification curves using machine learning.

Journal: Gates open research
PMID: 39850072

Abstract

BACKGROUND: The TaqMan Array Card (TAC) is an arrayed, high-throughput qPCR platform that can simultaneously detect multiple targets in a single reaction. However, the manual post-run analysis of TAC data is time consuming and subject to interpretation. We sought to automate the post-run analysis of TAC data using machine learning models.

Authors

  • Ben J Brintz
    Department of Internal Medicine, University of Utah, Salt Lake City, Utah.
  • Darwin J Operario
    University of Virginia, Charlottesville, Virginia, USA.
  • David Garrett Brown
    University of Utah Department of Internal Medicine, Salt Lake City, Utah, USA.
  • Shanrui Wu
    Qingdao University School of Public Healh, Qingdao, Shandong, China.
  • Lan Wang
    The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • Eric R Houpt
    University of Virginia, Charlottesville, Virginia, USA.
  • Daniel T Leung
    University of Utah Department of Internal Medicine, Salt Lake City, Utah, USA.
  • Jie Liu
    School of Bioscience and Bioengineering, South China University of Technology, Guangzhou, China.
  • James A Platts-Mills
    University of Virginia, Charlottesville, Virginia, USA.

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