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Tests for Differentiation in Gene Expression Using a Data‐Driven Order or Weights for Hypotheses
Author(s) -
Hommel Gerhard,
Kropf Siegfried
Publication year - 2005
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.200410118
Subject(s) - permutation (music) , weighting , sorting , sort , type i and type ii errors , mathematics , sequence (biology) , expression (computer science) , multiple comparisons problem , algorithm , statistics , computer science , arithmetic , genetics , biology , medicine , physics , acoustics , radiology , programming language
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. In this paper, we consider an alternative procedure, which is based on completely sorting the endpoints, but smoothed in the sense that some perturbations in the sequence of the p ‐values are allowed. The procedure is relatively easy to perform, but has high power under the same restrictions as for the weight‐based procedures. (© 2005 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)