MS Metabolomics Data Processing Utilities

Description Usage Arguments Value References See Also Examples

Apply variance stabilizing normalization (VSN) to a matrix or poplin object. This is an interface to the vsnMatrix function from the vsn package (see the vsn2 function for help). The vsn produces normalized intensities based on a glog (generalized logarithm) scale to base 2. See Huber et al. (2002) for details.

## S4 method for signature 'matrix'
normalize_vsn(x, meanSdPlot = FALSE, ...)

## S4 method for signature 'poplin'
normalize_vsn(x, xin, xout, meanSdPlot = FALSE, ...)

`x`	A matrix or poplin object.
`meanSdPlot`	Logical controlling whether the function displays meanSdPlot from the vsn package to visually check a dependence of the standard deviation on the mean.
`...`	Additional arguments passed to vsnMatrix.
`xin`	Character specifying the name of data to retrieve from `x` when `x` is a poplin object.
`xout`	Character specifying the name of data to store in `x` when `x` is a poplin object.

A matrix or poplin object of the same dimension as x containing the normalized intensities.

Huber W, von Heydebreck A, Sültmann H, Poustka A, Vingron M. Variance stabilization applied to microarray data calibration and to the quantification of differential expression. Bioinformatics. 2002;18 Suppl 1:S96-104. doi: 10.1093/bioinformatics/18.suppl_1.s96. PMID: 12169536.

Other normalization methods: normalize_cyclicloess(), normalize_mad(), normalize_mean(), normalize_median(), normalize_pqn(), normalize_scale(), normalize_sum(), poplin_normalize()

data(faahko_poplin)

if (requireNamespace("vsn", quietly = TRUE)) {
  ## poplin object
  normalize_vsn(faahko_poplin, xin = "knn", xout = "knn_vsn")

  ## matrix
  m <- poplin_data(faahko_poplin, "knn")
  normalize_vsn(m)
}