posNegCorrPlot: posNegCorrPlot
In TIN: Transcriptome instability analysis

Description Usage Arguments Value Examples

The posNegCorrPlot is a scatterPlot that compares the amount of splicing factor genes (red) for which expression levels are significant positively (vertical axis) and negatively (horizontal axis) correlated with the total relative amounts of aberrant exon usage per sample. The plot can also include results from permutations of the sample-wise aberrant exon usage amounts (dark blue), and randomly constructed gene sets of 280 genes.

1 2	posNegCorrPlot(fileName, tra, geneSummaries, splicingFactors, randomGeneSets, traPermutations)

`fileName`	Output filename. File format is optional, but must be one of png, jpg, eps or pdf.
`tra`	List object with total relative amounts of aberrant exon usage per sample. The object is returned by the function 'aberrantExonUsage'.
`geneSummaries`	The data.frame with gene-level expression values for each sample, returned from the function 'readGeneSummaries'.
`splicingFactors`	List of genes (Affymetrix transcript cluster id's and gene symbols) involved in pre-mRNA splicing. An example set of 280 genes is obtained by issuing the command 'data(splicingFactors)', but the input list can include any set of genes included in the data.frame returned from the function 'readGeneSummaries'.
`randomGeneSets`	Number of random gene sets of 280 genes to be created and included in the analysis.
`traPermutations`	Number of permutations of the sample-wise amounts of aberrant exon usage to be performed and included in the analysis.

posNegCorrPlot is used for the side-effect of producing a scatter plot that compares the amount of splicing factor genes (red) for which expression levels are significant positively (vertical axis) and negatively (horizontal axis) correlated with the total relative amounts of aberrant exon usage per sample. In addition, the plot can also include results from permutations of the sample-wise aberrant exon usage amounts (dark blue), and randomly constructed gene sets of 280 genes.

    data(splicingFactors)
    fs <- firmaAnalysis(useToyData=TRUE)
    gs <- readGeneSummaries(useToyData=TRUE)
    tra <- aberrantExonUsage(1.0, fs)

# Create plot that compares the amount of splicing factor genes for which
# expression levels are significant positively and negatively correlated
# with the total relative amounts of aberrant exon usage per sample
    posNegCorrPlot("cg.png", tra, gs, splicingFactors, 1000, 1000)