SnpPlm {aroma.affymetrix} | R Documentation |
The SnpPlm interface class
Description
Package: aroma.affymetrix
Class SnpPlm
Interface
~~|
~~+--
SnpPlm
Directly known subclasses:
AffineCnPlm, AffineSnpPlm, AvgCnPlm, AvgSnpPlm, CnPlm, HetLogAddCnPlm, HetLogAddSnpPlm, MbeiCnPlm, MbeiSnpPlm, RmaCnPlm, RmaSnpPlm
public class SnpPlm
extends Interface
An Interface
implementing methods special for
ProbeLevelModel
s specific to SNP arrays.
Usage
SnpPlm(...)
Arguments
... |
Not used. |
Methods
Methods:
getCellIndices | - | |
getChipEffectSet | - | |
getMergeStrands | - | |
getProbeAffinityFile | - | |
setMergeStrands | - | |
Methods inherited from Interface:
extend, print, uses
Requirements
Classes inheriting from this Interface
must provide the
following fields:
- mergeStrands
A
logical
value indicating if strands should be merged or not.
Author(s)
Henrik Bengtsson
Examples
for (zzz in 0) {
# Setup verbose output
verbose <- Arguments$getVerbose(-2)
timestampOn(verbose)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Define an example dataset using this path
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Find any SNP dataset
path <- NULL
if (is.null(path))
break
if (!exists("ds")) {
ds <- AffymetrixCelSet$fromFiles(path)
}
print(ds)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Create a set of various PLMs for this dataset
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
if (!exists("models", mode="list")) {
mergeStrands <- TRUE
models <- list(
rma = RmaSnpPlm(ds, mergeStrands=mergeStrands),
mbei = MbeiSnpPlm(ds, mergeStrands=mergeStrands)
# affine = AffineSnpPlm(ds, background=FALSE, mergeStrands=mergeStrands)
)
}
print(models)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# For each model, fit a few units
#
# Note, by fitting the same set of units across models, the internal
# caching mechanisms of aroma.affymetrix makes sure that the data is
# only read into memory once. See log for reading speed.
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
units <- 55+1:100
for (model in models) {
ruler(verbose)
fit(model, units=units, force=TRUE, verbose=verbose)
}
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# For each unit, plot the estimated (thetaB,thetaA) for all models
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Should we plot the on the log scale?
log <- TRUE
# Do only user to press ENTER if more than one unit is plotted
opar <- par(ask=(length(units) > 1))
Alab <- expression(theta[A])
Blab <- expression(theta[B])
if (log) {
lim <- c(6, 16)
} else {
lim <- c(0, 2^15)
}
# For each unit...
for (unit in units) {
# For all models...
for (kk in seq_along(models)) {
ces <- getChipEffects(models[[kk]])
ceUnit <- ces[unit]
snpName <- names(ceUnit)[1]
theta <- ceUnit[[1]]
thetaA <- theta[[1]]$theta
thetaB <- theta[[2]]$theta
if (log) {
thetaA <- log(thetaA, base=2)
thetaB <- log(thetaB, base=2)
}
# Create the plot?
if (kk == 1) {
plot(NA, xlim=lim, ylim=lim, xlab=Blab, ylab=Alab, main=snpName)
abline(a=0, b=1, lty=2)
}
# Plot the estimated parameters
points(thetaB, thetaA, col=kk, pch=19)
}
} # for (unit ...)
# Reset graphical parameter settings
par(opar)
} # for (zzz in 0)
rm(zzz)
[Package aroma.affymetrix version 3.2.2 Index]