simdurbin2: Gene intensities simulator
In DDHFm: Variance Stabilization by Data-Driven Haar-Fisz (for Microarrays)

Description Usage Arguments Value Author(s) References See Also Examples

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

1	simdurbin2(mu, alpha, seta, seps)

`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

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].

Guy Nason <g.p.nason@bris.ac.uk>

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

simdurbin

#
# 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