crosshybMCplot {crosshybDetector}R Documentation

Plot of Monte Carlo simulations

Description

Plot the results of Monte Carlo simulations.

Usage

crosshybMCplot(input, pVal = 0.001, arrayName = NULL, doPlot = FALSE)

Arguments

input the output of crosshyb containing the pvalues obtained from Monte Carlo simulations
pVal if the pvalue of a probe is < pVal, the probe is flagged as corruptor
arrayName the name of the array, used to create the output file name
doPlot logical, if TRUE writes the plot to file

Details

This function draws two scatter plots, one for each channel (red and green), containing the pvalue from Monte Carlo simulations ordered by raw intensity. A red line corresponding to the pVal parameter is added. All the probes above the red line (i.e. whose pvalue < pVal) are considered as corruptors and their number is shown in the title. Such a number reflects the amount of cross-hybridization in the microarray experiment.
The degree of the cross-hybridization effect is proportional to the relative abundance of the non-target sequence versus the target sequence. As a consequence, abundant target sequences can generate high signal intensities on their related chip spots as well as increasing the intensity values of spots carrying similar probes. For this reason most of the probes identified as corruptors fall into the left part of the plot corresponding to those probes with the higher raw intensity signals.

Value

If doPlot is FALSE the plot is created on the current graphics device. If doPlot is TRUE the plot is only written to file.

Author(s)

Paolo Uva

See Also

crosshyb

Examples

## Not run: 
# Run crosshyb algorithm...
# This function will take several minutes to finish
data(raw)
data(probeSeq)
crosshyb.out <- crosshyb(raw, probeSeq, plate=1, numPermut=10000, probeNameID="Name",
                         probes=c("probes", "spike"), satValue = 65535, maxProbes=100)                      
## End(Not run)

# ... or load directly the crosshyb output
data(crosshyb.out)

# Plot p-values obtained with Monte Carlo simulations
crosshybMCplot(crosshyb.out, pVal=0.01, arrayName="myArray", doPlot=FALSE)


[Package crosshybDetector version 1.0.4 Index]