simdurbin2: Gene intensities simulator

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

Gene intensities simulator

Description

Simulates gene intensities from the two components model of Durbin and Rocke.

Usage

simdurbin2(mu, alpha, seta, seps)

Arguments

mu	the means where the gene intensities are simulated from
alpha	background mean of gene intensities
seta	standard deviation of high-level gene intensities
seps	standard deviation of low-level gene intensities

Value

Like simdurbin this function simulates gene intensities from the Durbin and Rocke two component model (see Durbin and Rocke, 2001). Unlike simdurbin this function generates each intensity with a mean specified by an entry in mu. So, length(mu) intensities are generated with intensity i having mean mu[i].

Author(s)

Guy Nason <[e-mail]>

References

Rocke, D.M. and Durbin, B.P. (2001), A model for measurement error for gene expression arrays, Journal of Computational Biology, 8, 557-569

See Also

simdurbin

Examples

#
# Generate data with mu equal to 80 and mu equal to 80000 with 10 replicates each
#
#
v <- simdurbin2( c(rep(80, 10), rep(80000,10)), alpha=24800, seta=0.227, seps=4800)
#
# Let's look at the mean of the first 10 and the last 10
#
mean(v[1:10])
#[1] 27361.95
#
mean(v[11:20])
#[1] 92455.66

DDHFm documentation built on Nov. 26, 2022, 1:06 a.m.