library(ggplot2) library(cowplot) library(plyr) library(scales) library(gridExtra) library(grid) library(ggplotify) dat <- read.table('output/statsFiles/all.tmerge.min2reads.endSupport-all.novelLoci.stats.tsv', header=T, as.is=T, sep='\t') dat <- subset(dat, seqTech=='ONT') dat <- subset(dat, sizeFrac=='0+') dat <- subset(dat, sampleRep=='BrainRep1') dat$seqTech <- gsub('-', '\n', dat$seqTech) dat$sampleRep <- gsub('byCapDesign_', '', dat$sampleRep) horizCats <- length(unique(dat$capDesign)) * length(unique(dat$sampleRep)) vertCats <- length(unique(dat$seqTech)) wXyPlot = (horizCats * 0.9) +1.7 hXyPlot = (vertCats * 0.6) + 1.7 geom_textSize=1.4 themeSize = (14/5) * geom_textSize # https://stackoverflow.com/questions/25061822/ggplot-geom-text-font-size-control/25062509 lineSize=geom_textSize/8 minorLineSize=lineSize/2 dat$category<-factor(dat$category, ordered=TRUE, levels=rev(c('intronic', 'intergenic'))) plotBase <- "p <- ggplot(dat[order(dat$category), ], aes(x=1, y=count, fill=category)) + geom_bar(stat='identity') + ylab('# Novel loci') + scale_y_continuous(labels=comma)+ scale_fill_manual (values=c(intronic='#8cd9b3', intergenic='#00b386'))+ xlab('') + guides(fill = guide_legend(title='Category\n(w.r.t. GENCODE)'))+ geom_text(position = 'stack', size=geom_textSize, aes( y = count, label = comma(count), hjust = 0.5, vjust = 1))+ theme(axis.ticks.x = element_blank(), axis.text.x = element_blank()) + theme(axis.text= element_text(size=themeSize*1.8), axis.ticks = element_line(size=lineSize), axis.line = element_line(colour = '#595959', size=lineSize), axis.title=element_text(size = themeSize*2), panel.grid.major = element_line(colour='#d9d9d9', size=lineSize),panel.grid.minor = element_line(colour='#e6e6e6', size=minorLineSize),panel.border = element_blank(),panel.background = element_blank(), strip.background = element_rect(colour='#737373',fill='white'), legend.key.size=unit(0.5,'line'), legend.title=element_text(size=themeSize*1.2), legend.text=element_text(size=themeSize), strip.text = element_text(size = themeSize)) + theme(axis.ticks.x = element_blank(), axis.text.x = element_blank()) + " plotFacetXy <- parse(text =paste(plotBase, "facet_grid( seqTech ~ capDesign + sampleRep, scales='free_y')")) plotFacetYx <- parse(text=paste(plotBase, "facet_grid( capDesign + sampleRep ~ seqTech, scales='free_y')")) pXy <- eval(plotFacetXy) pYx <- eval(plotFacetYx) legend <- get_legend(pXy) pXyNoLegend <- pXy + theme(legend.position='none') pYxNoLegend <- pYx + theme(legend.position='none') legendOnly <- grid.arrange(legend) pXyGrob <- as.grob(pXy) pYxGrob <- as.grob(pYx) pXyNoLegendGrob <- as.grob(pXyNoLegend) pYxNoLegendGrob <- as.grob(pYxNoLegend) hLegendOnly <- convertUnit(sum(legend$heights), 'in', valueOnly=TRUE) wLegendOnly <- convertUnit(sum(legend$widths), 'in', valueOnly=TRUE) hYxPlot <- wXyPlot wYxPlot <- hXyPlot hXyNoLegendPlot<- hXyPlot wXyNoLegendPlot<- wXyPlot - wLegendOnly hYxNoLegendPlot<- hYxPlot wYxNoLegendPlot<- wYxPlot - wLegendOnly save_plot('output/plots/tmerge.novelLoci.stats/ONT/byCapDesign/ONT_byCapDesign_0+_BrainRep1.tmerge.min2reads.endSupport-all.novelLoci.stats.legendOnly.png', legendOnly, base_width=wLegendOnly, base_height=hLegendOnly) save_plot('output/plots/tmerge.novelLoci.stats/ONT/byCapDesign/ONT_byCapDesign_0+_BrainRep1.tmerge.min2reads.endSupport-all.novelLoci.stats.xy.wLegend.png', pXy, base_width=wXyPlot, base_height=hXyPlot) save_plot('output/plots/tmerge.novelLoci.stats/ONT/byCapDesign/ONT_byCapDesign_0+_BrainRep1.tmerge.min2reads.endSupport-all.novelLoci.stats.xy.woLegend.png', pXyNoLegend, base_width=wXyNoLegendPlot, base_height=hXyNoLegendPlot) save_plot('output/plots/tmerge.novelLoci.stats/ONT/byCapDesign/ONT_byCapDesign_0+_BrainRep1.tmerge.min2reads.endSupport-all.novelLoci.stats.yx.wLegend.png', pYx, base_width=wYxPlot, base_height=hYxPlot) save_plot('output/plots/tmerge.novelLoci.stats/ONT/byCapDesign/ONT_byCapDesign_0+_BrainRep1.tmerge.min2reads.endSupport-all.novelLoci.stats.yx.woLegend.png', pYxNoLegend, base_width=wYxNoLegendPlot, base_height=hYxNoLegendPlot)