Mercurial > repos > bornea > apostl_static_bubblegraph_generator
view Static_Bubble_Plot_Cmdln.R @ 25:f0901a52b310 draft
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| author | bornea |
|---|---|
| date | Tue, 17 May 2016 13:00:42 -0400 |
| parents | c0981e643ee6 |
| children |
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################################################################################################### # R-code: APOSTL Global Variables # Author: Brent Kuenzi ################################## Dependencies ################################################### library(dplyr); library(tidyr); library(ggplot2); library(ggrepel) colors <- c("AirForceblue"="#5D8AA8","Aliceblue"="#F0F8FF","Alizarincrimson"="#E32636","Almond"="#EFDECD","Amaranth"="#E52B50","Amber"="#FFBF00","Americanrose"="#FF033E","Amethyst"="#9966CC","AndroidGreen"="#A4C639","Antiflashwhite"="#F2F3F4","Antiquebrass"="#CD9575","Antiquefuchsia"="#915C83","Antiquewhite"="#FAEBD7","Ao"="#008000","Applegreen"="#8DB600","Apricot"="#FBCEB1","Aqua"="#00FFFF","Aquamarine"="#7FFFD4","Armygreen"="#4B5320","Arsenic"="#3B444B","Arylideyellow"="#E9D66B","Ashgray"="#B2BEB5","Asparagus"="#87A96B","Atomictangerine"="#FF9966","Auburn"="#A52A2A","Aureolin"="#FDEE00","AuroMetalSaurus"="#6E7F80","Awesome"="#FF2052","Azure"="#007FFF","Azuremist"="#F0FFFF","Babyblue"="#89CFF0","Babyblueeyes"="#A1CAF1","Babypink"="#F4C2C2","BallBlue"="#21ABCD","BananaMania"="#FAE7B5","Bananayellow"="#FFE135","Battleshipgray"="#848482","Bazaar"="#98777B","Beaublue"="#BCD4E6","Beaver"="#9F8170","Beige"="#F5F5DC","Bisque"="#FFE4C4","Bistre"="#3D2B1F","Bittersweet"="#FE6F5E","Obsidian"="#000000","Onyx"="#000000","LostSoul"="#000000","Midnight"="#000000","RollingBlackout"="#000000","SleepingPanther"="#000000","VoidbyArmani"="#000000","BlanchedAlmond"="#FFEBCD","BleudeFrance"="#318CE7","BlizzardBlue"="#ACE5EE","Blond"="#FAF0BE","Blue"="#0000FF","BlueBell"="#A2A2D0","BlueGray"="#6699CC","Bluegreen"="#00DDDD","Blueviolet"="#8A2BE2","Blush"="#DE5D83","Bole"="#79443B","Bondiblue"="#0095B6","BostonUniversityRed"="#CC0000","Brandeisblue"="#0070FF","Brass"="#B5A642","Brickred"="#CB4154","Brightcerulean"="#1DACD6","Brightgreen"="#66FF00","Brightlavender"="#BF94E4","Brightmaroon"="#C32148","Brightpink"="#FF007F","Brightturquoise"="#08E8DE","Brightube"="#D19FE8","Brilliantlavender"="#F4BBFF","Brilliantrose"="#FF55A3","Brinkpink"="#FB607F","Britishracinggreen"="#004225","Bronze"="#CD7F32","Brown"="#964B00","Bubblegum"="#FFC1CC","Bubbles"="#E7FEFF","Buff"="#F0DC82","Bulgarianrose"="#480607","Burgundy"="#800020","Burlywood"="#DEB887","Burntorange"="#CC5500","Burntsienna"="#E97451","Burntumber"="#8A3324","Byzantine"="#BD33A4","Byzantium"="#702963","Cadet"="#536872","Cadetblue"="#5F9EA0","Cadetgray"="#91A3B0","CadmiumGreen"="#006B3C","CadmiumOrange"="#ED872D","CadmiumRed"="#E30022","CadmiumYellow"="#FFF600","CalPolyPomonagreen"="#1E4D2B","CambridgeBlue"="#A3C1AD","Camel"="#C19A6B","Camouflagegreen"="#78866B","Canaryyellow"="#FFEF00","Candyapplered"="#FF0800","Candypink"="#E4717A","Capri"="#00BFFF","Caputmortuum"="#592720","Cardinal"="#C41E3A","Caribbeangreen"="#00CC99","Carmine"="#960018","Carminepink"="#EB4C42","Carminered"="#FF0038","Carnationpink"="#FFA6C9","Carnelian"="#B31B1B","Carolinablue"="#99BADD","Carrotorange"="#ED9121","Ceil"="#92A1CF","Celadon"="#ACE1AF","Celestialblue"="#4997D0","Cerise"="#DE3163","Cerisepink"="#EC3B83","Cerulean"="#007BA7","Ceruleanblue"="#2A52BE","CGBlue"="#007AA5","CGRed"="#E03C31","Chamoisee"="#A0785A","Champagne"="#F7E7CE","Charcoal"="#36454F","Chartreuse"="#DFFF00","Cherryblossompink"="#FFB7C5","Chestnut"="#CD5C5C","Chocolate"="#7B3F00","Chromeyellow"="#FFA700","Cinereous"="#98817B","Cinnabar"="#E34234","Cinnamon"="#D2691E","Citrine"="#E4D00A","Classicrose"="#FBCCE7","Cobalt"="#0047AB","Coffee"="#C86428","Columbiablue"="#9BDDFF","Coolblack"="#002E63","Coolgray"="#8C92AC","Copper"="#B87333","Copperrose"="#996666","Coquelicot"="#FF3800","Coral"="#FF7F50","Coralpink"="#F88379","Coralred"="#FF4040","Cordovan"="#893F45","Corn"="#FBEC5D","Cornflowerblue"="#6495ED","Cornsilk"="#FFF8DC","Cosmiclatte"="#FFF8E7","Cottoncandy"="#FFBCD9","Cream"="#FFFDD0","Crimson"="#DC143C","Crimsonglory"="#BE0032","Cyan"="#00B7EB","Daffodil"="#FFFF31","Dandelion"="#F0E130","Darkblue"="#00008B","Darkbrown"="#654321","Darkbyzantium"="#5D3954","Darkcandyapplered"="#A40000","Darkcerulean"="#08457E","Darkchampagne"="#C2B280","Darkchestnut"="#986960","Darkcoral"="#CD5B45","Darkcyan"="#008B8B","Darkelectricblue"="#536878","Darkgoldenrod"="#B8860B","Darkgray"="#A9A9A9","Darkgreen"="#013220","Darkjunglegreen"="#1A2421","Darkkhaki"="#BDB76B","Darklava"="#483C32","Darklavender"="#734F96","Darkmagenta"="#8B008B","Darkmidnightblue"="#003366","Darkolivegreen"="#556B2F","Darkorange"="#FF8C00","Darkorchid"="#9932CC","Darkpastelblue"="#779ECB","Darkpastelgreen"="#03C03C","Darkpastelpurple"="#966FD6","Darkpastelred"="#C23B22","Darkpink"="#E75480","Darkpowderblue"="#003399","Darkraspberry"="#872657","Darkred"="#8B0000","Darksalmon"="#E9967A","Darkscarlet"="#560319","Darkseagreen"="#8FBC8F","Darksienna"="#3C1414","Darkslateblue"="#483D8B","Darkslategray"="#2F4F4F","Darkspringgreen"="#177245","Darktan"="#918151","Darktangerine"="#FFA812","Darkterracotta"="#CC4E5C","Darkturquoise"="#00CED1","Darkviolet"="#9400D3","Dartmouthgreen"="#00693E","Davysgray"="#555555","Debianred"="#D70A53","Deepcarmine"="#A9203E","Deepcarminepink"="#EF3038","Deepcarrotorange"="#E9692C","Deepcerise"="#DA3287","Deepchampagne"="#FAD6A5","Deepchestnut"="#B94E48","Deepfuchsia"="#C154C1","Deepjunglegreen"="#004B49","Deeplilac"="#9955BB","Deepmagenta"="#CC00CC","Deeppeach"="#FFC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"="#C5B358","Venetianred"="#C80815","Verdigris"="#43B3AE","Veronica"="#A020F0","Violet"="#7F00FF","Viridian"="#40826D","Vividauburn"="#922724","Vividburgundy"="#9F1D35","Vividcerise"="#DA1D81","Vividtangerine"="#FFA089","Vividviolet"="#9F00FF","Warmblack"="#004242","Wenge"="#645452","Wheat"="#F5DEB3","White"="#FFFFFF","Whitesmoke"="#F5F5F5","Wildblueyonder"="#A2ADD0","WildStrawberry"="#FF43A4","WildWatermelon"="#FC6C85","Wine"="#722F37","Wisteria"="#C9A0DC","Xanadu"="#738678","YaleBlue"="#0F4D92","Yellow"="#FFFF00","Yellowgreen"="#9ACD32","YellowOrange"="#FFEF02","Zaffre"="#0014A8","Zinnwalditebrown"="#2C1608") ################################# Read in Data #################################################### ## REQUIRED INPUTS ## # 1) listfile (filename) #listfile <- "EGFR_list.txt" # 2) Prey File (filename) #preyfile <- "EGFR_prey.txt" # 3) crapome File (filename or FALSE) #crapfile <- "EGFR_crap.txt" # 4) Inter File (filename) #interfile <- "inter.txt" # 5) X axis ("ln(NSAF)","SpecSum", "log2(FoldChange)", "SaintScore", "logOddsScore","NSAFScore") #input.main.x <- "ln(NSAF)" # 6) Y axis ("ln(NSAF)","SpecSum", "log2(FoldChange)", "SaintScore", "logOddsScore","NSAFScore") #input.main.y <- "log2(FoldChange)" # 7) Bubble Size ("ln(NSAF)","SpecSum", "log2(FoldChange)", "SaintScore", "logOddsScore","NSAFScore") #input.main.size <- "SpecSum" # 8) Coloring ("fixed" or "crapome") #input.main.color <- "crapome" # 9) Saint Score Cutoff (0 - 1) #input.SS_cutoff <- 0.8 # 10) Fold change Cutoff (-inf - inf) #input.FC_cutoff <- 0 # 11) NSAF Score Cutoff (-inf - inf) #input.NS_cutoff <- 0 # 12) Plotting Theme ("Default","b/w","minimal","classic","dark","linedraw") #input.plot_theme <- "Default" # 13) Bubble Labels ("none",">cutoff","all") #input.bubble_label <- ">cutoff" # 14) Label Color ("white","black") #input.label_color <- "black" # 15) Bubble Color (colors listed above) #input.bubble_color <- colors[["Alizarin crimson"]] # 16) Bubble outline color ("white","black") #input.outline_color <- "black" # 17) CRAPome Filtered Bubble Color (colors listed above) #input.filt_color <- colors[["Tan"]] # 18) Bubble scale ((0-100),(0-100)) # SECOND NUMBER MUST BE LARGER THAN OR EQUAL TO THE FIRST #input.plot_scale <- c(0,10) # 19) File Type (".pdf",".png",".tif",".svg",".eps",".jpg") #input.file_type <- ".png" ################################################################################ # Define merge function and calculate crapome % merge_files <- function(SAINT_DF, prey_DF, crapome=FALSE) { SAINT <- read.table(SAINT_DF, sep='\t', header=TRUE) prey <- read.table(prey_DF, sep='\t', header=FALSE); colnames(prey) <- c("Prey", "Length", "PreyGene") DF <- merge(SAINT,prey) if(crapome!=FALSE) { crapome <- read.table(crapome, sep='\t', header=TRUE) colnames(crapome) <- c("Prey", "Symbol", "Num.of.Exp", "Ave.SC", "Max.SC") DF1 <- merge(DF, crapome); as.character(DF1$Num.of.Exp); DF1$Symbol <- NULL; DF1$Ave.SC <- NULL; DF1$Max.SC <- NULL #remove unnecessary columns DF1$Num.of.Exp <- sub("^$", "0 / 1", DF1$Num.of.Exp ) #replace blank values with 0 / 1 DF <- DF1 %>% separate(Num.of.Exp, c("NumExp", "TotalExp"), " / ") #split into 2 columns DF$CrapomePCT <- round(100 - (as.integer(DF$NumExp) / as.integer(DF$TotalExp) * 100), digits=2) #calculate crapome % } DF$FoldChange <- round(log2(DF$FoldChange),digits=2) colnames(DF)[(colnames(DF)=="FoldChange")] <- "log2(FoldChange)" DF$SAF <- DF$AvgSpec / DF$Length by_bait <- DF %>% group_by(Bait) %>% mutate("NSAF" = SAF/sum(SAF)) by_bait$SAF <- NULL return(by_bait[!duplicated(by_bait),]) } ################################################################################ bubblebeam <- function(main.data,main.exclude,main.x,main.y,main.size,main.color,SS_cutoff,FC_cutoff,NS_cutoff, plot_theme,bubble_label,label_color,bubble_color, outline_color,filt_color,plot_scale, file_type){ str_x=paste0(main.x) str_y=paste0(main.y) str_color=paste0(main.color) str_size=paste0(main.size) str_cutoff= paste0(SS_cutoff) str_label= bubble_label scl_size = plot_scale main.data2 <- main.data[!(main.data$PreyGene %in% main.exclude),] main.data2 <- subset(main.data2, main.data2[(colnames(main.data2)=="log2(FoldChange)")] >= FC_cutoff) main.data2 <- subset(main.data2, main.data2[(colnames(main.data2)=="NSAFScore")] >= NS_cutoff) c <- subset(main.data2, SaintScore>=as.numeric(str_cutoff), select = c(str_x,str_y,"Bait","PreyGene",str_size)) colnames(c) <- c("x","y","Bait","PreyGene","size") p <- ggplot(data=c, x=x, y=y,size=size)+ geom_point(data=c, aes(x=x, y=y,size=size), fill=bubble_color,color=outline_color,pch=21) + scale_size(range=scl_size) p <- p + labs(x=str_x, y=str_y, size=str_size) + scale_size(range=scl_size) if(length(levels(c$Bait) > 1)) {p <- p + facet_wrap(~Bait)} if(str_label== 'all' & length(c$x)>=1) {set.seed=42; p <- p + ggrepel::geom_text_repel(data=c, aes(x=x,y=y,label=PreyGene), segment.color="black",force=1, fontface='bold', box.padding=unit(0.25,'lines'), point.padding=unit(0.25,'lines'), max.iter=1e4, segment.size=0.5)} if(plot_theme== "classic") {p <- p + theme_classic()} if(plot_theme== "b/w") {p <- p + theme_bw()} if(plot_theme== "minimal") {p <- p + theme_minimal()} if(plot_theme== "dark") {p <- p + theme_dark()} if(plot_theme== "linedraw") {p <- p + theme_linedraw()} if(str_color=="crapome") { a <- subset(main.data2, CrapomePCT <80 & SaintScore >=as.numeric(str_cutoff), select = c(str_x,str_y,"Bait","PreyGene",str_size,"CrapomePCT")) b <- subset(main.data2, CrapomePCT >=80 & SaintScore >=as.numeric(str_cutoff), select = c(str_x,str_y,"Bait","PreyGene",str_size,"CrapomePCT")) colnames(a) <- c("x","y","Bait","PreyGene","size", "CrapomePCT") colnames(b) <- c("x","y","Bait","PreyGene","size","CrapomePCT") p <- ggplot(data=a, x=x, y=y,size=size) + geom_point(data=a,aes(x=x,y=y,size=size),fill=filt_color,pch=21,color=outline_color) + scale_size(range=scl_size) if(length(levels(a$Bait) > 1)) {p <- p + facet_wrap(~Bait)} if(str_label== "all" & length(a$x)>=1) {set.seed=42; p <- p + ggrepel::geom_text_repel(data=a, aes(x=x,y=y,label=PreyGene), segment.color=label_color,force=1, fontface='bold', box.padding=unit(0.25,'lines'), point.padding=unit(0.25,'lines'), color=label_color, max.iter=1e4, segment.size=0.5)} p <- p + geom_point(data=b, aes(x=x, y=y, size=size, fill=CrapomePCT),color=outline_color,pch=21) + scale_fill_gradient(limits=c(80, 100), low=filt_color, high=bubble_color) + labs(colour="CRAPome Probability \nof Specific Interaction (%)", x=str_x, y=str_y,size=str_size) if(str_label== '>cutoff' & length(b$x)>=1) {set.seed=42; p <- p + ggrepel::geom_text_repel(data=b, aes(x=x,y=y,label=PreyGene), segment.color=label_color,force=1, fontface='bold', box.padding=unit(0.25,'lines'), point.padding=unit(0.25,'lines'), color=label_color, max.iter=1e4, segment.size=0.5)} if(str_label== 'all' & length(b$x)>=1) {set.seed=42; p <- p + ggrepel::geom_text_repel(data=b, aes(x=x,y=y,label=PreyGene), segment.color=label_color,force=1, fontface='bold', box.padding=unit(0.25,'lines'), point.padding=unit(0.25,'lines'), color=label_color, max.iter=1e4, segment.size=0.5)} if(plot_theme== "classic") {p <- p + theme_classic()} if(plot_theme== "b/w") {p <- p + theme_bw()} if(plot_theme== "minimal") {p <- p + theme_minimal()} if(plot_theme== "dark") {p <- p + theme_dark()} if(plot_theme== "linedraw") {p <- p + theme_linedraw()} } p <- p + theme(axis.title.y = element_text(size=rel(1.5),face="bold"), axis.title.x = element_text(size=rel(1.5),face="bold"), axis.text.x = element_text(size=rel(1.5),face="bold"), axis.text.y = element_text(size=rel(1.5),face="bold"), strip.text.x = element_text(size=rel(1.5),face="bold"), legend.text = element_text(face="bold"), legend.title = element_text(face="bold")) if(file_type == ".png"){png(paste("BubbleGraph",file_type,sep="")); print(p); dev.off()} if(file_type == ".pdf"){pdf(paste("BubbleGraph",file_type,sep="")); print(p); dev.off()} if(file_type == ".tif"){tiff(paste("BubbleGraph",file_type,sep="")); print(p); dev.off()} if(file_type == ".jpg"){jpeg(paste("BubbleGraph",file_type,sep="")); print(p); dev.off()} if(file_type == ".svg"){svg(paste("BubbleGraph",file_type,sep="")); print(p); dev.off()} if(file_type == ".eps"){postscript(paste("BubbleGraph",file_type,sep="")); print(p); dev.off()} } ################################################################################ args <- commandArgs(trailingOnly = TRUE) working <- as.data.frame(merge_files(args[1], args[2], args[3])) inter_df <- read.table(args[4], sep='\t', header=FALSE) working$temp <- strsplit(as.character(working$ctrlCounts),"[|]") cnt <- 0 for(i in working$temp){ cnt <- cnt+1 working$ctrl_mean[cnt] <- mean(as.numeric(unlist(i))) working$ctrl_number[cnt] <- length(i)} working$ctrl_SAF <- working$ctrl_mean / working$Length main.data <- working %>% group_by(Bait) %>% mutate("control_NSAF" = ctrl_SAF/sum(ctrl_SAF)) ctrl_SAF_constant <- 1/mean(main.data$ctrl_SAF) # add ctrl_SAF_constant to prevent dividing by 0 cnt <- 0 for(i in main.data$control_NSAF){ cnt <- cnt + 1 main.data$nsafScore[cnt] <- ((main.data$NSAF[cnt])+ctrl_SAF_constant)/((i/main.data$ctrl_number[cnt])+ctrl_SAF_constant) } main.data$NSAF <- log(main.data$NSAF) main.data$nsafScore <- log(main.data$nsafScore) main.data <- filter(main.data, NSAF > -Inf) colnames(main.data)[colnames(main.data)=="NSAF"] <- "ln(NSAF)" colnames(main.data)[colnames(main.data)=="nsafScore"] <- "NSAFScore" main.data$SAF <- NULL; main.data$ctrl_SAF <- NULL main.data$control_NSAF <- NULL; main.data$temp <- NULL main.data$ctrl_mean <- NULL ################################################################################ if (args[7] == "fixed"){ input.main.size <- "SpecSum" input.plot_scale <- c(2,2) } else { input.main.size <- args[7] input.plot_scale <- c(0,10) } input.bubble_color <- colors[[args[15]]] input.filt_color <- colors[[args[17]]] bubblebeam(main.data = main.data, main.exclude = FALSE,main.x = args[5], main.y = args[6],main.size = input.main.size,main.color = args[8], SS_cutoff = args[9],FC_cutoff = args[10], NS_cutoff = args[11], plot_theme = args[12], bubble_label = args[13],label_color = args[14], bubble_color = input.bubble_color, outline_color = args[16], filt_color = input.filt_color, plot_scale = input.plot_scale, file_type = ".png") ################################################################################