demiequal-methods: Cluster probes that have no statistically significant...
In demi: Differential Expression from Multiple Indicators

Description Usage Arguments Value Author(s) See Also Examples

Performs wilcox.test on normalized expression value matrix defined in DEMIClust object and selects only these probes that have no differential signalling.

1	demiequal(x = "DEMIClust")

`x`	A `DEMIClust` object. The DEMIClust object containing normalized expression values used for statistical significance test on differential signalling of probes. The object contains the column indexes of groups (e.g. 'test' and 'control') used in the analysis.

A list. Returns a list containing probes that did not have statistically significant differential signalling.

Sten Ilmjarv

wilcox.test which this function wraps.

## 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 demiequal

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

# Create clusters with default behaviour
demiclust <- DEMIClust( demiexp, group = c( "BRAIN", "UHR" ) )

# Retrieve probes whose differential signalling was not statistically significant
nosigprobes <- demiequal( demiclust )

# However it makes more sense to incorporate the method straight into \code{DEMIClust} object
demiclust <- DEMIClust( demiexp, group = c( "BRAIN", "UHR" ), clust.method = demiequal )

# Retrieve the probes whose differential signalling was not statistically significant
nosigprobes <- getCluster( demiclust )

# Since the function only produces one cluster with a sign '[E]' derming equal
head( nosigprobes[[grep("\\[E\\]", names( nosigprobes ))]] )


## End(Not run)