Tests for Differentiation in Gene Expression Using a Data‐Driven Order or Weights for Hypotheses

In the analysis of gene expression by microarrays there are usually few subjects, but high‐dimensional data. By means of techniques, such as the theory of spherical tests or with suitable permutation tests, it is possible to sort the endpoints or to give weights to them according to specific criteria determined by the data while controlling the multiple type I error rate. The procedures developed so far are based on a sequential analysis of weighted p ‐values (corresponding to the endpoints), including the most extreme situation of weighting leading to a complete order of p ‐values. When the data for the endpoints have approximately equal variances, these procedures show good power properties.

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