qcPlots: Plots for Quality Assessment

Description

It creates BoxPlots, Density Plots, MA plots, RLE plots and hierachical clustering plots with the sample data set.

Usage

qcPlots(dd, 
	offset, 
	MeanSignal=TRUE, 
	ProcessedSignal=FALSE, 
	TotalProbeSignal=FALSE, 
	TotalGeneSignal=FALSE, 
	BGMedianSignal=FALSE, 
	BGUsed=FALSE, 
	targets)

Arguments

A uRNAList object containing the ouput from readMicroRnaAFE

offset

numeric value to add to the intensities before log transforming

MeanSignal

logical, if TRUE "gMeanSignal" is used

ProcessedSignal

logical, if TRUE "gProcessedSignal" is used

TotalProbeSignal

logical, if TRUE "gTotalProbeSignal" is used

TotalGeneSignal

logical, if TRUE "gTotalGeneSignal" is used

BGMedianSignal

logical, if TRUE "gBGMedianSignal" is used

BGUsed

logical, if TRUE "gBGUsed" is used

targets

data.frame with the target structure

Details

The signals loaded from the AFE data files can be used for the quality assesment using the graphical utilities included in the qcPlots function. For the gMeanSignal, the BoxPlots, Density Plots, MA plots, RLE plots and hierachical clustering plots are done. For the gProcessedSignal the same plots are done, except the hierarchical clustering. For the gTotalProbeSignal and the gTotalGeneSignal only the BoxPlots and Density Plots are done, and finally, for the Background signals only the Boxplots are done.

References

Boldstad B.M., Collin F., Brettschneider J., Simpson, K., Cope L., Irizarry R. A., Speed T. P. Quality Assesement of Affymetrix GeneChip Data. In Bioinformatics and Computational Biology Solutions Using R and Bioconductor. (eds.) Gentleman R., Carey V. J., Huber W., Irizarry R. A., Dudoit S. (2005). Springer.

Examples

Run this code

## Not run: 
# data(dd.micro)
# qcPlots(dd.micro,offset=5,
#        		MeanSignal=TRUE,
#         	ProcessedSignal=TRUE,
#         	TotalProbeSignal=TRUE,
#         	TotalGeneSignal=TRUE,
#         	BGMedianSignal=TRUE,
#         	BGUsed=TRUE,
# 		targets.micro)
# graphics.off()
# 
# ## End(Not run)