Aug 25, 2006

The optimal discovery procedure for large-scale significance testing, with applications to comparative microarray experiments

John D StoreyJeffrey T Leek


As much of the focus of genetics and molecular biology has shifted toward the systems level, it has become increasingly important to accurately extract biologically relevant signal from thousands of related measurements. The common property among these high-dimensional biological studies is that the measured features have a rich and largely unknown underlying structure. One example of much recent interest is identifying differentially expressed genes in comparative microarray experiments. We propose a new approach aimed at optimally performing many hypothesis tests in a high-dimensional study. This approach estimates the optimal discovery procedure (ODP), which has recently been introduced and theoretically shown to optimally perform multiple significance tests. Whereas existing procedures essentially use data from only one feature at a time, the ODP approach uses the relevant information from the entire data set when testing each feature. In particular, we propose a generally applicable estimate of the ODP for identifying differentially expressed genes in microarray experiments. This microarray method consistently shows favorable performance over five highly used existing methods. For example, in testing for differential expre...Continue Reading

  • References13
  • Citations63
  • References13
  • Citations63


Mentioned in this Paper

BRCA2 Protein
BLID protein, human
BRCA1-IRIS protein, human
Data Interpretation, Statistical
False Positive Reactions
Molecular Biology
Mammary Neoplasms, Human
Cdna Microarrays
Apoptosis Regulatory Proteins
BRCA2 protein, human

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