6533b7d9fe1ef96bd126b8aa

RESEARCH PRODUCT

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

Siegfried KropfGerhard Hommel

subject

Statistics and ProbabilityModels StatisticalModels GeneticBiometricsGene Expression ProfilingWord error rateFamilywise error rateGeneral MedicineData-drivenWeightingData Interpretation StatisticalsortComputer Simulationp-valueStatistics Probability and UncertaintyAlgorithmAlgorithmsOligonucleotide Array Sequence AnalysisMathematicsType I and type II errors

description

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.

yearjournalcountryeditionlanguage
2005-08-01Biometrical Journal
https://doi.org/10.1002/bimj.200410118