Use of pretransformation to cope with extreme values in important candidate features

作者：Boulesteix Anne Laure^*; Guillemot Vincent; Sauerbrei Willi

来源：Biometrical Journal, 2011, 53(4): 673-688.

DOI：10.1002/bimj.201000189

• Aberrant values
• Biomarker ranking
• High-dimensional data
• Instability
• Outliers

Extreme values in predictors often strongly affect the results of statistical analyses in high-dimensional settings. Although they frequently occur with most high-throughput techniques, the problem is often ignored in the literature. We suggest to use a very simple transformation, proposed before in a different context by Royston and Sauerbrei, as an intermediary step between array preprocessing and high-level statistical analysis. This straightforward univariate transformation identifies extreme values in continuous features and can thus be used as a diagnostic tool for outliers. The use of the transformation and its effects is demonstrated for diverse univariate and multivariate statistical analyses using nine publicly available microarray data sets.

• 出版日期2011-7
• 单位河北医科大学