plotDistCountAnalysis: Creates a boxplot to see the distribution of read counts in...

Description Usage Arguments Value Examples

Description

Takes the rlog transformation of the RRKM (Reads Per Kilobase of transcript per Million) of the read counts of type-specific and shared regulatory regions and plots the distribution of those read counts in all sample types analyzed in the workflow.

Usage

1
plotDistCountAnalysis(analysisresults, counts)

Arguments

analysisresults

output generated from countanalysis() then categAltrePeaks()

counts

output generated from getCounts()

Value

a ggplot

Examples

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## Not run: 
dir <- system.file('extdata', package='ALTRE', mustWork=TRUE)
csvfile <- file.path(dir, 'lung.csv')
sampleinfo <- loadCSVFile(csvfile)
samplePeaks <- loadBedFiles(sampleinfo)
consPeaks <- getConsensusPeaks(samplepeaks=samplePeaks,minreps=2)
plotConsensusPeaks(samplepeaks=consPeaks)
TSSannot<- getTSS()
consPeaksAnnotated <- combineAnnotatePeaks(conspeaks = consPeaks,
                                          TSS = TSSannot,
                                          merge = TRUE,
                                          regionspecific = TRUE,
                                          mergedistenh = 1500,
                                          mergedistprom = 1000)
counts_consPeaks <- getCounts(annotpeaks = consPeaksAnnotated,
                              sampleinfo = sampleinfo,
                              reference = 'SAEC',
                              chrom = 'chr21')
altre_peaks <- countanalysis(counts = counts_consPeaks,
                             pval = 0.01,
                             lfcvalue = 1)
categaltre_peaks <- categAltrePeaks(altre_peaks,
                                    lfctypespecific = 1.5,
                                    lfcshared = 1.2,
                                    pvaltypespecific = 0.01,
                                    pvalshared = 0.05)
plotDistCountAnalysis(categaltre_peaks, counts_consPeaks)

## End(Not run)

ewymathe/testALTREinstall documentation built on May 16, 2019, 9:42 a.m.