Description Usage Arguments Details Value Author(s) References Examples
View source: R/sagmbSimulateData.R
Functions to validate and assess the performance of vsn through simulation of data.
1 2 | sagmbSimulateData(n=8064, d=2, de=0, up=0.5, nrstrata=1, miss=0, log2scale=FALSE)
sagmbAssess(h1, sim)
|
n |
Numeric. Number of probes (rows). |
d |
Numeric. Number of arrays (columns). |
de |
Numeric. Fraction of differentially expressed genes. |
up |
Numeric. Fraction of up-regulated genes among the differentially expressed genes. |
nrstrata |
Numeric. Number of probe strata. |
miss |
Numeric. Fraction of data points that is randomly sampled
and set to |
log2scale |
Logical. If |
h1 |
Matrix. Calibrated and transformed data, according, e.g., to vsn |
sim |
List. The output of a previous call to
|
Please see the vignette.
For sagmbSimulateData
, a list with four components:
hy
, an n x d
matrix with the true (=simulated)
calibrated, transformed data;
y
, an n x d
matrix with the simulated
uncalibrated raw data - this is intended to be fed into
vsn2
;
is.de
, a logical vector of length n
, specifying
which probes are simulated to be differentially expressed.
strata
, a factor of length n
.
For sagmbSimulateData
, a number: the root mean squared
difference between true and estimated transformed data.
Wolfgang Huber
Wolfgang Huber, Anja von Heydebreck, Holger Sueltmann, Annemarie Poustka, and Martin Vingron (2003) "Parameter estimation for the calibration and variance stabilization of microarray data", Statistical Applications in Genetics and Molecular Biology: Vol. 2: No. 1, Article 3. http://www.bepress.com/sagmb/vol2/iss1/art3
1 2 3 4 | sim <- sagmbSimulateData(nrstrata = 4)
ny <- vsn2(sim$y, strata = sim$strata)
res <- sagmbAssess(exprs(ny), sim)
res
|
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