dhhrcomp: Simulated genes, apply DDHFm then compute and return...

In DDHFm: Variance Stabilization by Data-Driven Haar-Fisz (for Microarrays)

Simulated genes, apply DDHFm then compute and return variance, skewness and kurtosis values

Description

An example gene intensity simulator with given mean values mu0 which then returns the variance, skew and kurtosis of the DDHF transformed intensities. The gene intensity simulation is performed using simdurbin2

Usage

dhhrcomp(nsims = 1024, nmu = 4,
	mu0 = c(0, 5, 10, 15, 20, 25, 30, 40, 50, 60,
	65, 70, 80, 100, 200, 300, 500, 1000) * 1000)

Arguments

nsims	Number of replicates for each mu
nmu	Selects first nmu genes from mu for use
mu0	The possible gene intensity means

Details

This function simulates some gene intensities. A list of possible intensity means are supplied in mu0. The first nmu of these are selected. Then for each of the selected means nsims gene intensities are generated.

The intensities are them subjected to DDHF transformation.

Value

mu	A vector of length nmu of the mean intensities considered
v.hft	A vector of nmu variances, one for each mean in mu0. The variance is the variance of the DDHFm transformed simulated intensity data.
s.hft	A vector of nmu skewnesses, one for each mean in mu0. The skewness is the skewness of the DDHFm transformed simulated intensity data.
k.hft	A vector of nmu kurtoses, one for each mean in mu0. The kurtosis is the kurtosis of the DDHFm transformed simulated intensity data.

Author(s)

Guy Nason <[e-mail].

References

Durbin, B.P., Hardin, J.S., Hawkins, D.M. and Rocke, D.M. (2002), A variance-stabilizing transformation for gene expression microarray data, Bioinformatics, 18, S105-S110

See Also

simdurbin2

DDHFm documentation built on Oct. 4, 2024, 5:11 p.m.