Package: vsn 3.79.6

vsn: Variance stabilization and calibration for microarray data

The package implements a method for normalising microarray intensities from single- and multiple-color arrays. It can also be used for data from other technologies, as long as they have similar format. The method uses a robust variant of the maximum-likelihood estimator for an additive-multiplicative error model and affine calibration. The model incorporates data calibration step (a.k.a. normalization), a model for the dependence of the variance on the mean intensity and a variance stabilizing data transformation. Differences between transformed intensities are analogous to "normalized log-ratios". However, in contrast to the latter, their variance is independent of the mean, and they are usually more sensitive and specific in detecting differential transcription.

Authors:Wolfgang Huber [aut, cre], Anja von Heydebreck [aut], Dennis Kostka [ctb], David Kreil [ctb], Hans-Ulrich Klein [ctb], Robert Gentleman [ctb], Deepayan Sarkar [ctb], Gordon Smyth [ctb], Federal Ministry of Research, Technology and Space of Germany, DHGP [fnd]