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The Reproducibility of Lists of Differentially Expressed Genes in Microarray Studies
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  • Published: 02 July 2007

The Reproducibility of Lists of Differentially Expressed Genes in Microarray Studies

  • Leming Shi1,
  • Wendell Jones2,
  • Roderick Jensen3,
  • Stephen Harris1,
  • Roger Perkins4,
  • Federico Goodsaid5,
  • Lei Guo1,
  • Lisa Croner6,
  • Cecilie Boysen7,
  • Hong Fang4,
  • Shashi Amur5,
  • Wenjun Bao8,
  • Catalin Barbacioru9,
  • Vincent Bertholet10,
  • Xiaoxi Megan Cao4,
  • Tzu-Ming Chu8,
  • Patrick Collins11,
  • Xiao-hui Fan1,
  • Felix Frueh5,
  • James Fuscoe1,
  • Xu Guo12,
  • Jing Han13,
  • Damir Herman14,
  • Huixiao Hong4,
  • Ernest Kawasaki15,
  • Quan-Zhen Li16,
  • Yuling Luo17,
  • Yunqing Ma17,
  • Nan Mei1,
  • Ron Peterson18,
  • Raj Puri13,
  • Feng Qian4,
  • Richard Shippy12,
  • Zhenqiang Su1,
  • Yongming Andrew Sun9,
  • Hongmei Sun4,
  • Brett Thorn1,
  • Yaron Turpaz12,
  • Charles Wang19,
  • Sue-Jane Wang5,
  • Janet Warrington12,
  • James Willey20,
  • Jie Wu4,
  • Qian Xie4,
  • Liang Zhang21,
  • Lu Zhang22,
  • Sheng Zhong23,
  • James Chen1,
  • Russell Wolfinger8 &
  • …
  • Weida Tong1 

Nature Precedings (2007)Cite this article

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  • 3 Citations

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Abstract

Reproducibility is a fundamental requirement in scientific experiments and clinical contexts. Recent publications raise concerns about the reliability of microarray technology because of the apparent lack of agreement between lists of differentially expressed genes (DEGs). In this study we demonstrate that (1) such discordance may stem from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion, the lists become much more reproducible, especially when fewer genes are selected; and (3) the instability of short DEG lists based on P cutoffs is an expected mathematical consequence of the high variability of the t-values. We recommend the use of FC ranking plus a non-stringent P cutoff as a baseline practice in order to generate more reproducible DEG lists. The FC criterion enhances reproducibility while the P criterion balances sensitivity and specificity.

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Authors and Affiliations

  1. US FDA, National Center for Toxicological Research https://www.nature.com/nature

    Leming Shi, Stephen Harris, Lei Guo, Xiao-hui Fan, James Fuscoe, Nan Mei, Zhenqiang Su, Brett Thorn, James Chen & Weida Tong

  2. Expression Analysis Inc. https://www.nature.com/nature

    Wendell Jones

  3. Virginia Bioinformatics Institute https://www.nature.com/nature

    Roderick Jensen

  4. Z-Tech at FDA/NCTR https://www.nature.com/nature

    Roger Perkins, Hong Fang, Xiaoxi Megan Cao, Huixiao Hong, Feng Qian, Hongmei Sun, Jie Wu & Qian Xie

  5. US FDA, Center for Drug Evaluation and Research https://www.nature.com/nature

    Federico Goodsaid, Shashi Amur, Felix Frueh & Sue-Jane Wang

  6. Biogen Idec https://www.nature.com/nature

    Lisa Croner

  7. ViaLogy Inc. https://www.nature.com/nature

    Cecilie Boysen

  8. SAS Institute Inc. https://www.nature.com/nature

    Wenjun Bao, Tzu-Ming Chu & Russell Wolfinger

  9. Applied Biosystems https://www.nature.com/nature

    Catalin Barbacioru & Yongming Andrew Sun

  10. Eppendorf Array Technologies https://www.nature.com/nature

    Vincent Bertholet

  11. Agilent Technologies Inc. https://www.nature.com/nature

    Patrick Collins

  12. Affymetrix Inc. https://www.nature.com/nature

    Xu Guo, Richard Shippy, Yaron Turpaz & Janet Warrington

  13. US FDA, Center for Biologics Evaluation and Research https://www.nature.com/nature

    Jing Han & Raj Puri

  14. University of Arkansas for Medical Sciences https://www.nature.com/nature

    Damir Herman

  15. US NIH, National Cancer Institute https://www.nature.com/nature

    Ernest Kawasaki

  16. University Texas Southwestern Medical Center https://www.nature.com/nature

    Quan-Zhen Li

  17. Panomics Inc. https://www.nature.com/nature

    Yuling Luo & Yunqing Ma

  18. Novartis https://www.nature.com/nature

    Ron Peterson

  19. UCLA Cedars-Sinai Medical Center https://www.nature.com/nature

    Charles Wang

  20. University of Toledo https://www.nature.com/nature

    James Willey

  21. CapitalBio Corporation https://www.nature.com/nature

    Liang Zhang

  22. Solexa Inc. https://www.nature.com/nature

    Lu Zhang

  23. University of Illinois at Urbana-Champaign https://www.nature.com/nature

    Sheng Zhong

Authors
  1. Leming Shi
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  2. Wendell Jones
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  3. Roderick Jensen
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  4. Stephen Harris
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  5. Roger Perkins
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  6. Federico Goodsaid
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  7. Lei Guo
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  8. Lisa Croner
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  9. Cecilie Boysen
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  10. Hong Fang
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  11. Shashi Amur
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  12. Wenjun Bao
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  13. Catalin Barbacioru
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  14. Vincent Bertholet
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  15. Xiaoxi Megan Cao
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  16. Tzu-Ming Chu
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  17. Patrick Collins
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  18. Xiao-hui Fan
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  19. Felix Frueh
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  20. James Fuscoe
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  21. Xu Guo
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  22. Jing Han
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  23. Damir Herman
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  24. Huixiao Hong
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  25. Ernest Kawasaki
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  26. Quan-Zhen Li
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  27. Yuling Luo
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  28. Yunqing Ma
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  29. Nan Mei
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  30. Ron Peterson
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  31. Raj Puri
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  32. Feng Qian
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  33. Richard Shippy
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  34. Zhenqiang Su
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  35. Yongming Andrew Sun
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  36. Hongmei Sun
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  37. Brett Thorn
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  38. Yaron Turpaz
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  39. Charles Wang
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  40. Sue-Jane Wang
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  41. Janet Warrington
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  42. James Willey
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  43. Jie Wu
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  44. Qian Xie
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  45. Liang Zhang
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  46. Lu Zhang
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  47. Sheng Zhong
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  48. James Chen
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  49. Russell Wolfinger
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  50. Weida Tong
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Corresponding author

Correspondence to Leming Shi.

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Cite this article

Shi, L., Jones, W., Jensen, R. et al. The Reproducibility of Lists of Differentially Expressed Genes in Microarray Studies. Nat Prec (2007). https://doi.org/10.1038/npre.2007.306.1

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  • Received: 29 June 2007

  • Accepted: 02 July 2007

  • Published: 02 July 2007

  • DOI: https://doi.org/10.1038/npre.2007.306.1

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Keywords

  • microarrays
  • gene
  • selection
  • reproducibility
  • MAQC
  • fold
  • change
  • statistics
  • P-value
  • US
  • FDA
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