Nature Communications (Jul 2020)

Strategies to enable large-scale proteomics for reproducible research

  • Rebecca C. Poulos,
  • Peter G. Hains,
  • Rohan Shah,
  • Natasha Lucas,
  • Dylan Xavier,
  • Srikanth S. Manda,
  • Asim Anees,
  • Jennifer M. S. Koh,
  • Sadia Mahboob,
  • Max Wittman,
  • Steven G. Williams,
  • Erin K. Sykes,
  • Michael Hecker,
  • Michael Dausmann,
  • Merridee A. Wouters,
  • Keith Ashman,
  • Jean Yang,
  • Peter J. Wild,
  • Anna deFazio,
  • Rosemary L. Balleine,
  • Brett Tully,
  • Ruedi Aebersold,
  • Terence P. Speed,
  • Yansheng Liu,
  • Roger R. Reddel,
  • Phillip J. Robinson,
  • Qing Zhong

DOI
https://doi.org/10.1038/s41467-020-17641-3
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 13

Abstract

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Clinical proteomics critically depends on the ability to acquire highly reproducible data over an extended period of time. Here, the authors assess reproducibility over four months across different mass spectrometers and develop a computational approach to mitigate variation among instruments over time.