getProbeLevel-methods: Returns the probe levels from the normalized expression...
In demi: Differential Expression from Multiple Indicators

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

The function getProbeLevel returns the probe levels in the normalized expression matrix specified by the probe ID's.

getProbeLevel(object, probes, verbose)

## S4 method for signature 'DEMIDiff,vector,logical'
getProbeLevel(object, probes, verbose)

## S4 method for signature 'DEMIExperiment,vector,logical'
getProbeLevel(object, probes,
  verbose = TRUE)

`object`	A `DEMIExperiment` or `DEMIDiff` object.
`probes`	A `vector`. A vector of probe ID's whose expression levels should be returned.
`verbose`	A `logical`. If TRUE it will print out the probe ID's that were not found in normalized expression matrix.

To see what are the available probes in the normalized expression matrix you can try row.names(getNormMatrix(x)) where x is an object of class DEMIExperiment.

Returns the probe levels in the normalized expression matrix for the specified probes.

Sten Ilmjarv

DEMIExperiment, DEMIDiff

## Not run: 

# To use the example we need to download a subset of CEL files from
# http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE9819 published
# by Pradervand et al. 2008.

# Set the destination folder where the downloaded files fill be located.
# It can be any folder of your choosing.
destfolder <- "demitest/testdata/"

# Download packed CEL files and change the names according to the feature
# they represent (for example to include UHR or BRAIN in them to denote the
# features).
# It is good practice to name the files according to their features which
# allows easier identification of the files later.

ftpaddress <- "ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM247nnn"
download.file( paste( ftpaddress, "GSM247694/suppl/GSM247694.CEL.gz", sep = "/" ),
		destfile = paste( destfolder, "UHR01_GSM247694.CEL.gz", sep = "" ) )
download.file( paste( ftpaddress, "GSM247695/suppl/GSM247695.CEL.gz", sep = "/" ),
		destfile = paste( destfolder, "UHR02_GSM247695.CEL.gz", sep = "" ) )
download.file( paste( ftpaddress, "GSM247698/suppl/GSM247698.CEL.gz", sep = "/" ),
		destfile = paste( destfolder, "UHR03_GSM247698.CEL.gz", sep = "" ) )
download.file( paste( ftpaddress, "GSM247699/suppl/GSM247699.CEL.gz", sep = "/" ),
		destfile = paste( destfolder, "UHR04_GSM247699.CEL.gz", sep = "" ) )
download.file( paste( ftpaddress, "GSM247696/suppl/GSM247696.CEL.gz", sep = "/" ),
		destfile = paste( destfolder, "BRAIN01_GSM247696.CEL.gz", sep = "" ) )
download.file( paste( ftpaddress, "GSM247697/suppl/GSM247697.CEL.gz", sep = "/" ),
		destfile = paste( destfolder, "BRAIN02_GSM247697.CEL.gz", sep = "" ) )
download.file( paste( ftpaddress, "GSM247700/suppl/GSM247700.CEL.gz", sep = "/" ),
		destfile = paste( destfolder, "BRAIN03_GSM247700.CEL.gz", sep = "" ) )
download.file( paste( ftpaddress, "GSM247701/suppl/GSM247701.CEL.gz", sep = "/" ),
		destfile = paste( destfolder, "BRAIN04_GSM247701.CEL.gz", sep = "" ) )

# We need the gunzip function (located in the R.utils package) to unpack the gz files.
# Also we will remove the original unpacked files for we won't need them.
library( R.utils )
for( i in list.files( destfolder ) ) {
	gunzip( paste( destfolder, i, sep = "" ), remove = TRUE )
}

# Now we can continue the example of the function getProbeLevel

# Set up an experiment
demiexp <- DEMIExperiment( analysis = 'gene', celpath = destfolder,
			experiment = 'myexperiment', organism = 'homo_sapiens' )

# Create clusters with an optimized wilcoxon's rank sum test incorporated within demi that
# precalculates the probabilities
demiclust <- DEMIClust( demiexp, group = c( "BRAIN", "UHR" ), clust.method = demi.wilcox.test.fast )

# Calcuate differential expression
demidiff <- DEMIDiff( demiclust )

# Retrieve the probe levels specified by probe ID's of the normalized expression matrix
getProbeLevel( demiexp, c( 1171,1182 ), TRUE )
getProbeLevel( demidiff, c( 1171,1182 ), TRUE )


## End(Not run)