Statistical significance threshold criteria for analysis of microarray gene expression data

Statistical Applications in Genetics and Molecular Biology
Cheng ChengMartine F Roussel

Abstract

The methodological advancement in microarray data analysis on the basis of false discovery rate (FDR) control, such as the q-value plots, allows the investigator to examine the FDR from several perspectives. However, when FDR control at the "customary" levels 0.01, 0.05, or 0.1 does not provide fruitful findings, there is little guidance for making the trade off between the significance threshold and the FDR level by sound statistical or biological considerations. Thus, meaningful statistical significance criteria that complement the existing FDR methods for large-scale multiple tests are desirable. Three statistical significance criteria, the profile information criterion, the total error proportion, and the guide-gene driven selection, are developed in this research. The first two are general significance threshold criteria for large-scale multiple tests; the profile information criterion is related to the recent theoretical studies of the connection between FDR control and minimax estimation, and the total error proportion is closely related to the asymptotic properties of FDR control in terms of the total error risk. The guide-gene driven selection is an approach to combining statistical significance and the existing biolog...Continue Reading

Citations

Mar 24, 2010·Journal of Biopharmaceutical Statistics·Xinping CuiJason Wilson
Dec 19, 2015·Computational Statistics & Data Analysis·Cheng Cheng
Jan 20, 2010·Computational Statistics & Data Analysis·Cheng Cheng
Mar 31, 2010·Computational Statistics & Data Analysis·Daniel L HuntStanley Pounds
Jun 17, 2009·Bioinformatics·Kathleen F Kerr
Jun 20, 2017·Pharmacogenetics and Genomics·Laura B RamseyMary V Relling
May 23, 2008·Pharmacogenetics and Genomics·Landry K KamdemMary V Relling
Dec 22, 2017·Cancer·Hiroto InabaSue C Kaste
Dec 17, 2009·Cancer Control : Journal of the Moffitt Cancer Center·James J ChenMichael J Schell

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