plotallvenn: Plots venn diagrams for comparison of two methods of...

In ewymathe/testALTREinstall: Workflow for Identifying Regulatory Elements from Chromatin Accessibility Assay Data

Description

Plots venn diagrams for comparison of two methods of identifying altered regulatory regions Makes venn diagrams for enhancers, promoters, and combined for both intensity-based peaks and for peaks identified by hotspot calling algorithms. There is no return value. Six venn diagrams will be plotted

Usage

plotallvenn(analysisresultsmatrix)

Arguments

analysisresultsmatrix

analysisresults of countanalysis function place into a a analysisresults matrix by the analyzeanalysisresults function

Examples

## 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')
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)
analysisresults <- resultsComparison(altre_peaks, reference= "SAEC")
plotallvenn(analysisresults)

## End(Not run)

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