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unifiedWMWqPCR: the unified Wilcoxon–Mann–Whitney test for analyzing RT-qPCR data in R

Jan De Neve (UGent) , Joris Meys (UGent) , Jean-Pierre Ottoy (UGent) , Lieven Clement (UGent) and Olivier Thas (UGent)
(2014) BIOINFORMATICS. 30(17). p.2494-2495
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Abstract
Motivation: Recently, De Neve et al. proposed a modification of the Wilcoxon-Mann-Whitney (WMW) test for assessing differential expression based on RT-qPCR data. Their test, referred to as the unified WMW (uWMW) test, incorporates a robust and intuitive normalization and quantifies the probability that the expression from one treatment group exceeds the expression from another treatment group. However, no software package for this test was available yet. Results: We have developed a Bioconductor package for analyzing RT-qPCR data with the uWMW test. The package also provides graphical tools for visualizing the effect sizes.

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Chicago
De Neve, Jan, Joris Meys, Jean-Pierre Ottoy, Lieven Clement, and Olivier Thas. 2014. “unifiedWMWqPCR: The Unified Wilcoxon–Mann–Whitney Test for Analyzing RT-qPCR Data in R.” Bioinformatics 30 (17): 2494–2495.
APA
De Neve, Jan, Meys, J., Ottoy, J.-P., Clement, L., & Thas, O. (2014). unifiedWMWqPCR: the unified Wilcoxon–Mann–Whitney test for analyzing RT-qPCR data in R. BIOINFORMATICS, 30(17), 2494–2495.
Vancouver
1.
De Neve J, Meys J, Ottoy J-P, Clement L, Thas O. unifiedWMWqPCR: the unified Wilcoxon–Mann–Whitney test for analyzing RT-qPCR data in R. BIOINFORMATICS. 2014;30(17):2494–5.
MLA
De Neve, Jan, Joris Meys, Jean-Pierre Ottoy, et al. “unifiedWMWqPCR: The Unified Wilcoxon–Mann–Whitney Test for Analyzing RT-qPCR Data in R.” BIOINFORMATICS 30.17 (2014): 2494–2495. Print.
@article{4376165,
  abstract     = {Motivation: Recently, De Neve et al. proposed a modification of the Wilcoxon-Mann-Whitney (WMW) test for assessing differential expression based on RT-qPCR data. Their test, referred to as the unified WMW (uWMW) test, incorporates a robust and intuitive normalization and quantifies the probability that the expression from one treatment group exceeds the expression from another treatment group. However, no software package for this test was available yet. 
Results: We have developed a Bioconductor package for analyzing RT-qPCR data with the uWMW test. The package also provides graphical tools for visualizing the effect sizes.},
  author       = {De Neve, Jan and Meys, Joris and Ottoy, Jean-Pierre and Clement, Lieven and Thas, Olivier},
  issn         = {1367-4803},
  journal      = {BIOINFORMATICS},
  language     = {eng},
  number       = {17},
  pages        = {2494--2495},
  title        = {unifiedWMWqPCR: the unified Wilcoxon--Mann--Whitney test for analyzing RT-qPCR data in R},
  url          = {http://dx.doi.org/10.1093/bioinformatics/btu313},
  volume       = {30},
  year         = {2014},
}

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