flowVS (version 1.4.2)

microVS: Variance stabilization for microarray data.

Description

Variance-stabilizing inverse hyperbolic sine (asinh) transformation for microarray data.

Usage

microVS(data, cfLow=0, cfHigh=10, frac=1)

Arguments

data

The microarray data in a Matrix.

cfLow

lowest possible value of cofactor (log scale).

cfHigh

highest possible value of cofactor (log scale).

frac

fraction of differentially expressed genes used in variance stabilization (0< frac

Value

• microVS returns a matrix of the variance-stabilizing microarray data.

Details

This function transforms a microarray data matrix z by asinh(z/c) transformation where c is a normalizing cofactor. The cofactor is searched in the range [cfLow, cfHigh] and an optimum cofactor is obtained for which the transformed data is variance stabilized. The optimum cofactor is obtained by minimizing Bartlett's test statistics for homogeneity of variance. If the parameter frac is less then one, a fraction of differentially expressed genes are used in estimating the cofactor.

References

Ariful Azad, Bartek Rajwa, and Alex Pothen (2015), "flowVS: Channel-Specific Variance Stabilization in Flow Cytometry", manuscript submitted for publication.

Examples

# stabilize variance of the Kidney microarray data from the vsn package
library(vsn)
data(kidney)
kidney.t = microVS(exprs(kidney))
plotMeanSd(kidney.t)