False discovery rate paradigms for statistical analyses of microarray gene expression data

@article{Cheng2007FalseDR,
  title={False discovery rate paradigms for statistical analyses of microarray gene expression data},
  author={Cheng Cheng and Stan Pounds},
  journal={Bioinformation},
  year={2007},
  volume={1},
  pages={436 - 446}
}
The microarray gene expression applications have greatly stimulated the statistical research on the massive multiple hypothesis tests problem. There is now a large body of literature in this area and basically five paradigms of massive multiple tests: control of the false discovery rate (FDR), estimation of FDR, significance threshold criteria, control of family-wise error rate (FWER) or generalized FWER (gFWER), and empirical Bayes approaches. This paper contains a technical survey of the… CONTINUE READING

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