The function calibrates for sample-to-sample
variations through shifting and scaling, and transforms the
intensities to a scale where the variance is approximately
independent of the mean intensity. The variance stabilising
transformation is equivalent to the natural logarithm in the
high-intensity range, and to a linear transformation in the
low-intensity range. In an intermediate range, the arsinh
function interpolates smoothly between the two. The
parameters are estimated through a robust variant of maximum
likelihood. This assumes that for the majority of genes the
expression levels are not much different across the samples, i.e.,
that only a minority of genes (less than a fraction
'1-lts.quantile') is differentially expressed [6,7].
NOTE: For
this option the input object should contain raw intensities,
i.e., prior to background correction, log-transformation or any
normalisation. (I.e the RG object returned from the gprload
or AgilentLoad nodes).
Bjørn Kåre Alsberg
2006-04-06