Rank-invariant resampling based estimation of false discovery rate for analysis of small sample microarray data |
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Authors: | Nitin?Jain HyungJun?Cho Michael?O'Connell Email author" target="_blank">Jae?K?LeeEmail author |
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Institution: | (1) Division of Biostatistics and Epidemiology, Department of Health Evaluation Sciences, University of Virginia School of Medicine, Hospital West Complex, Room. 3181, P.O. Box 800717, Charlottesville, VA 22908-0717, USA;(2) Insightful Corporation, 2505 Meridian Parkway Suite 175, Durham, NC 27713, USA |
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Abstract: | Background The evaluation of statistical significance has become a critical process in identifying differentially expressed genes in
microarray studies. Classical p-value adjustment methods for multiple comparisons such as family-wise error rate (FWER) have
been found to be too conservative in analyzing large-screening microarray data, and the False Discovery Rate (FDR), the expected
proportion of false positives among all positives, has been recently suggested as an alternative for controlling false positives.
Several statistical approaches have been used to estimate and control FDR, but these may not provide reliable FDR estimation
when applied to microarray data sets with a small number of replicates. |
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Keywords: | |
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