plotCompareMethodsAll: Plots pie charts for comparison of two methods of identifying...

In Mathelab/ALTRE: Workflow for Identifying Regulatory Elements from Chromatin Accessibility Assay Data

Description

Plots pie charts for comparison of two methods of identifying altered regulatory regions. Makes pie charts for TSS-proximal, TSS-distal, and combined for both intensity-based peaks and for peaks identified by hotspot calling algorithms. There is no return value. Six pie charts swill be plotted.

Usage

plotCompareMethodsAll(analysisresultsmatrix, viewer = TRUE,
  palette = c("#C71585", "#d3d3d3", "#00E5EE", "#000080"), title11 = NULL,
  title12 = NULL, title13 = NULL, title21 = NULL, title22 = NULL,
  title23 = NULL, maintitlesize = "20px")

Arguments

analysisresultsmatrix	analysisresults of countanalysis function place into a a analysisresults matrix by the analyzeanalysisresults function
viewer	whether the plot should be displayed in the RStudio viewer or in Shiny/Knittr
palette	choose an RColorBrewer palette ("Set1", "Set2", "Set3", "Pastel1", "Pastel2", "Paired", etc.) or submit a vector of colors
title11	title of the first graph in the first row
title12	title of the second graph in the first row
title13	title of the third graph in the first row
title21	title of the first graph in the second row
title22	title of the second graph in the second row
title23	title of the third graph in the second row
maintitlesize	main title size (default, 20px)

Examples

## Not run: 
csvfile <- loadCSVFile("DNaseEncodeExample.csv")
samplePeaks <- loadBedFiles(csvfile)
consensusPeaks <- getConsensusPeaks(samplepeaks = samplePeaks,
minreps = 2)
TSSannot <- getTSS()
consensusPeaksAnnotated <- combineAnnotatePeaks(conspeaks = consensusPeaks,
TSS = TSSannot,
merge = TRUE,
regionspecific = TRUE,
distancefromTSSdist = 1500,
distancefromTSSprox = 1000)
consensusPeaksCounts <- getCounts(annotpeaks = consensusPeaksAnnotated,
                                 sampleinfo = csvfile,
                                 reference = 'SAEC',
                                 chrom = 'chr21')
alteredPeaks <- countanalysis(counts = consensusPeaksCounts,
pval = 0.01,
lfcvalue = 1)
alteredPeaksCategorized <- categAltrePeaks(alteredPeaks,
                                          lfctypespecific = 1.5,
                                          lfcshared = 1.2,
                                          pvaltypespecific = 0.01,
                                          pvalshared = 0.05)
comparePeaksAnalysisResults <- comparePeaksAltre(alteredPeaksCategorized)
plotCompareMethodsAll(comparePeaksAnalysisResults)

## End(Not run)

Mathelab/ALTRE documentation built on May 7, 2019, 3:41 p.m.