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Single-Patient Molecular Testing with NanoString nCounter Data Using a Reference-Based Strategy for Batch Effect Correction

Author

Listed:
  • Aline Talhouk
  • Stefan Kommoss
  • Robertson Mackenzie
  • Martin Cheung
  • Samuel Leung
  • Derek S Chiu
  • Steve E Kalloger
  • David G Huntsman
  • Stephanie Chen
  • Maria Intermaggio
  • Jacek Gronwald
  • Fong C Chan
  • Susan J Ramus
  • Christian Steidl
  • David W Scott
  • Michael S Anglesio

Abstract

A major weakness in many high-throughput genomic studies is the lack of consideration of a clinical environment where one patient at a time must be evaluated. We examined generalizable and platform-specific sources of variation from NanoString gene expression data on both ovarian cancer and Hodgkin lymphoma patients. A reference-based strategy, applicable to single-patient molecular testing is proposed for batch effect correction. The proposed protocol improved performance in an established Hodgkin lymphoma classifier, reducing batch-to-batch misclassification while retaining accuracy and precision. We suggest this strategy may facilitate development of NanoString and similar molecular assays by accelerating prospective validation and clinical uptake of relevant diagnostics.

Suggested Citation

  • Aline Talhouk & Stefan Kommoss & Robertson Mackenzie & Martin Cheung & Samuel Leung & Derek S Chiu & Steve E Kalloger & David G Huntsman & Stephanie Chen & Maria Intermaggio & Jacek Gronwald & Fong C , 2016. "Single-Patient Molecular Testing with NanoString nCounter Data Using a Reference-Based Strategy for Batch Effect Correction," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-18, April.
    • Handle: RePEc:plo:pone00:0153844
    DOI: 10.1371/journal.pone.0153844
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    References listed on IDEAS

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    3. Jeffrey T Leek & John D Storey, 2007. "Capturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis," PLOS Genetics, Public Library of Science, vol. 3(9), pages 1-12, September.
    4. Parker Hilary S. & Leek Jeffrey T., 2012. "The practical effect of batch on genomic prediction," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(3), pages 1-22, April.
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