A Comparison of Procedures for Controlling the False Discovery Rate in the Presence of Small Variance Genes: A Simulation Study |
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Authors: | Dan Lin Ziv Shkedy Tomasz Burzykowski Willem Talloen Luc Bijnens |
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Institution: | 1. I-Biostat, Hasselt University , Diepenbeek , Belgium dan.lin@uhasselt.be;3. I-Biostat, Hasselt University , Diepenbeek , Belgium;4. J&5. JPRD, Biometrics and Clinical Informatics , Beerse , Belgium |
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Abstract: | The Significance Analysis of Microarrays (SAM; Tusher et al., 2001
Tusher , V. G. ,
Tibshirani , R. ,
Chu , G. ( 2001 ). Significance analysis of microarrys applied to the ionizing radiation response . Proceedings of the National Academy of Sciences 98 : 5116 – 5121 .Crossref], PubMed], Web of Science ®] , Google Scholar]) method is widely used in analyzing gene expression data while controlling the FDR by using resampling-based procedure in the microarray setting. One of the main components of the SAM procedure is the adjustment of the test statistic. The introduction of the fudge factor to the test statistic aims at deflating the large value of test statistics due to the small standard error of gene-expression. Lin et al. (2008
Lin , D. ,
Shkedy , Z. ,
Burzykowski , T. ,
Göhlmann , H. W. H. ,
De Bondt , A. ,
Perera , T. ,
Geerts , T. ,
Bijnens , L. ( 2008 ). Significance analysis of microarray (SAM) for comparisons of several treatments with one control . Biometric Journal, MCP 50 ( 5 ): 801 – 823 .Crossref], PubMed], Web of Science ®] , Google Scholar]) pointed out that the fudge factor does not effectively improve the power and the control of the FDR as compared to the SAM procedure without the fudge factor in the presence of small variance genes. Motivated by the simulation results presented in Lin et al. (2008
Lin , D. ,
Shkedy , Z. ,
Burzykowski , T. ,
Göhlmann , H. W. H. ,
De Bondt , A. ,
Perera , T. ,
Geerts , T. ,
Bijnens , L. ( 2008 ). Significance analysis of microarray (SAM) for comparisons of several treatments with one control . Biometric Journal, MCP 50 ( 5 ): 801 – 823 .Crossref], PubMed], Web of Science ®] , Google Scholar]), in this article, we extend our study to compare several methods for choosing the fudge factor in the modified t-type test statistics and use simulation studies to investigate the power and the control of the FDR of the considered methods. |
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Keywords: | Control of the FDR Fudge factor Power SAM |
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