vsnh {vsn}R Documentation

A function that transforms a matrix of microarray intensities

Description

A function that transforms a matrix of microarray intensities

Usage

vsnh(y, p, strata)

Arguments

y A numeric matrix containing intensity values from an array experiment. It may contain NA values.
p An array with the transformation parameters. If strata is specified, it must be a 3d array, dim(p)[1] must be greater than or equal to the maximum of strata, dim(p)[2] must be ncol(y), and dim(p)[3] must be 2. If strata is missing, then the first dimension may be omitted. NA values are not allowed. See Details.
strata Integer vector of length nrow(y). See vsn for details.

Details

The transformation is:

vsnh(y, p, s)[k, i] = asinh( p[s[k], i, 1] + p[s[k], i, 2] * y[k, i] ) - log(2*p[s[1], 1, 2])

where k=1:nrow(y) counts over the probes, i=1:ncol(y) counts over the samples, p[s[k], i, 1] is the calibration offset for stratum s[k] in sample i, p[s[k], i, 2] is the calibration factor for stratum s[k] in sample i, and s[k] is the stratum of the the k-th probe.

The constant offset - log(2*p[s[1], 1, 2]) is there to make sure that for large y, vsnh(y) for the first stratum on the first chip is approximately the same as log(y). This has no effect on the generalized log-ratios (glog-ratios), which are differences between transformed intensities, but some users are more comfortable with the absolute values that are obtained this way, since they are more comparable to the log scale.

Value

A numeric matrix of the same size as y, with the transformed data.

Author(s)

Wolfgang Huber http://www.ebi.ac.uk/huber

References

Variance stabilization applied to microarray data calibration and to the quantification of differential expression, Wolfgang Huber, Anja von Heydebreck, Holger Sueltmann, Annemarie Poustka, Martin Vingron; Bioinformatics (2002) 18 Suppl.1 S96-S104.

Parameter estimation for the calibration and variance stabilization of microarray data, Wolfgang Huber, Anja von Heydebreck, Holger Sueltmann, Annemarie Poustka, and Martin Vingron; Statistical Applications in Genetics and Molecular Biology (2003) Vol. 2 No. 1, Article 3. http://www.bepress.com/sagmb/vol2/iss1/art3.

See Also

vsn

Examples

data(kidney)
y      = exprs(kidney)
p      = array(c(-0.2, -0.1, 0.1, 0.2, 0.0026, 0.0028, 0.0030, 0.0032), dim=c(2,2,2))
strata = sample(1:2, nrow(y), replace=TRUE)
res1   = vsnh(exprs(kidney), p, strata)

res2   = asinh(p[strata,,1] + p[strata,,2] * y) - log(2*p[strata,1,2])

stopifnot(max(abs(res1 - res2)) < 1e-10)


[Package vsn version 1.8.0 Index]