Abstract

This is a bonus talk to the bioinformatics journal club due to the opportunity of Wolfgang Huber coming to speak. Dr Wolfgang Huber from the European Bioinformatics Institute, Hinxton will be speaking about the vsn method he developed to simultaneously stabilise the variance and calibrate microarray data. The Huber group develops mathematical and statistical methods for the understanding of functional genomics data.

Paper details: Huber W., Von Heydebreck A., Sültmann H., Poustka A. and Vingron M. (2002) Variance stabilization applied to microarray data calibration and to the quantification of differential expression. ioinformatics 18: suppl. 1 (2002), S96 -S104.

Paper abstract: We introduce a statistical model for microarray gene expression data that comprises data calibration, the quantification of differential expression, and the quantification of measurement error. In particular, we derive a transformation h for intensity measurements, and a difference statistic Deltah whose variance is approximately constant along the whole intensity range. This forms a basis for statistical inference from microarray data, and provides a rational data pre-processing strategy for multivariate analyses. For the transformation h, the parametric form h(x)=arsinh(a+bx) is derived from a model of the variance-versus-mean dependence for microarray intensity data, using the method of variance stabilizing transformations. For large intensities, h coincides with the logarithmic transformation, and Deltah with the log-ratio. The parameters of h together with those of the calibration between experiments are estimated with a robust variant of maximum-likelihood estimation. We demonstrate our approach on data sets from different experimental platforms, including two-colour cDNA arrays and a series of Affymetrix oligonucleotide arrays.

Anyone is welcome to attend.