# HG changeset patch
# User bornea
# Date 1462978850 14400
# Node ID 8fe500f4e2cc099221ec09f3e0f97f683409a6c4
# Parent  019ccec16de8be2abddfb991b152b2a9e3588109
Deleted selected files

diff -r 019ccec16de8 -r 8fe500f4e2cc bubbles_v9_NSAF_natural_log.R
--- a/bubbles_v9_NSAF_natural_log.R	Wed May 11 11:00:44 2016 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,233 +0,0 @@
-rm(list=ls())
-###################################################################################################
-# R-code: Multi-bubble graph generation from SAINTexpress output
-# Author: Brent Kuenzi
-###################################################################################################
-library(dplyr); library(tidyr); library(ggplot2)
-###################################################################################################
-### Run program ###
-
-## REQUIRED INPUT ##
-# 1) listfile: SAINTexpress generated "list.txt" file
-# 2) preyfile: SAINT pre-processing generated "prey.txt" file used to run SAINTexpress
-## OPTIONAL INPUT ##
-# 3) crapome: raw output from crapome Workflow 1 query (http://www.crapome.org)
-# 4) color: bubble color (default = "red")
-#     - color= "crapome": color bubbles based on Crapome(%)
-#     - Also recognizes any color within R's built-in colors() vector
-# 5) label: Adds gene name labels to bubbles within the "zoomed in" graphs (default = FALSE)
-# 6) cutoff: Saintscore cutoff to be assigned for filtering the "zoomed in" graphs (default = 0.8)
-###################################################################################################
-main <- function(listfile, preyfile , crapome=FALSE, color="red", label=FALSE, cutoff=0.8, type="SC", inc_file = "None", exc_file = "None" ) {
-  cutoff_check(cutoff)
-  listfile <- list_type(listfile, inc_file, exc_file)
-  if(type == "SC") {
-    df <- merge_files_sc(listfile, preyfile, crapome)
-  }
-  if(type == "MQ") {
-    df <- merge_files_mq(listfile, preyfile, crapome)
-  }
-  bubble_NSAF(df,color)
-  bubble_SAINT(df,color)
-  bubble_zoom_SAINT(df, color, label, cutoff)
-  bubble_zoom_NSAF(df, color, label, cutoff)
-  write.table(df,"output.txt",sep="\t",quote=FALSE, row.names=FALSE)
-}
-
-list_type <- function(df, inc_file, exc_file) {
-  Saint <- read.delim(df, stringsAsFactors=FALSE)
-  if (inc_file != "None") {
-    if (exc_file == "None"){
-      inc_prots <- read.delim(inc_file, sep='\t', header=FALSE, stringsAsFactors=FALSE)
-      filtered_df = subset(Saint, Saint$Prey == inc_prots[,1])
-    }
-    else {
-      inc_prots <- read.delim(inc_file, sep='\t', header=FALSE, stringsAsFactors=FALSE)
-      exc_prots <- read.delim(exc_file, sep='\t', header=FALSE, stringsAsFactors=FALSE)
-      filtered_df = subset(Saint, Saint$Prey == inc_prots[,1])
-      filtered_df = subset(filtered_df, filtered_df$Prey != exc_prots[,1])
-    }
-  }
-  else if (exc_file != "None") {
-    exc_prots <- read.delim(exc_file, sep='\t', header=FALSE, stringsAsFactors=FALSE)
-    filtered_df = subset(Saint, Saint$Prey != exc_prots[,1])
-  }
-  else {
-    filtered_df = Saint
-  }
-  return(filtered_df)
-  
-}
-###################################################################################################
-# Merge input files and caculate Crapome(%) and NSAF for each protein for each bait
-###################################################################################################
-merge_files_mq <- function(SAINT, 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)
-  DF$SpecSum <- log2(DF$SpecSum)
-  
-  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 <- 100 - (as.integer(DF$NumExp) / as.integer(DF$TotalExp) * 100) #calculate crapome %
-  }
-  DF$SAF <- DF$AvgSpec / DF$Length
-  DF2 = DF %>% group_by(Bait) %>% mutate(NSAF = SAF/sum(SAF))
-  DF$NSAF = DF2$NSAF
-  return(DF)
-}
-
-merge_files_sc <- function(SAINT, prey_DF, crapome=FALSE) {
-  #SAINT <- read.table(SAINT_DF, sep='\t', header=TRUE)
-  prey <- read.table(prey_DF, sep='\t', header=FALSE); colnames(prey) <- c("Prey", "Length", "PreyGene")
-  DF <- merge(SAINT,prey)
-  
-  if(crapome!=FALSE) {
-    crapome <- read.table(crapome, sep='\t', header=TRUE)
-    colnames(crapome) <- c("Prey", "Symbol", "Num.of.Exp", "Ave.SC", "Max.SC")
-    DF1 <- merge(DF, crapome); as.character(DF1$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$CrapomePCT <- 100 - (as.integer(DF$NumExp) / as.integer(DF$TotalExp) * 100) #calculate crapome %
-  }
-  DF$SAF <- DF$AvgSpec / DF$Length
-  DF2 = DF %>% group_by(Bait) %>% mutate(NSAF = SAF/sum(SAF))
-  DF$NSAF = DF2$NSAF
-  return(DF)
-}
-###################################################################################################
-# Plot all proteins for each bait by x=ln(NSAF), y=Log2(FoldChange)
-###################################################################################################
-bubble_NSAF <- function(data, color) {
-    if(color=="crapome") {
-      a <- subset(data, CrapomePCT <80, select = c(NSAF,SpecSum, CrapomePCT, FoldChange, SaintScore, Bait))
-      b <- subset(data, CrapomePCT>=80, select = c(NSAF,SpecSum, CrapomePCT, FoldChange, SaintScore, Bait))
-      p <- qplot(x=log(NSAF), y=log2(FoldChange), data=a, colour=I("tan"),size=SpecSum) + scale_size(range=c(1,10)) + 
-        geom_point(aes(x=log(NSAF),y=log2(FoldChange), size=SpecSum), colour="black", shape=21, data=a)
-      if(length(levels(a$Bait) > 1)) {p <- p + facet_wrap(~Bait, scales="free_y")} # multiple graphs if multiple baits
-      p <- p + geom_point(aes(x=log(NSAF),y=log2(FoldChange), size=SpecSum, color=CrapomePCT), data=b) + 
-        scale_colour_gradient(limits=c(80, 100), low="tan", high="red") + 
-        labs(colour="CRAPome Probability \nof Specific Interaction (%)", x="ln(NSAF)") + 
-        geom_point(aes(x=log(NSAF),y=log2(FoldChange), size=SpecSum), colour="black", shape=21, data=b)
-      return(ggsave(p, width=8,height=4,filename = "bubble_NSAF.png"))
-    }
-   if(color != "crapome") {
-      p <- qplot(x=log(NSAF), y=log2(FoldChange), data=data, colour=I(color),size=SpecSum) + scale_size(range=c(1,10)) + 
-        geom_point(aes(x=log(NSAF),y=log2(FoldChange), size=SpecSum), colour="black", shape=21, data=data) + # add bubble outlines
-          labs(x="ln(NSAF)")
-        if(length(levels(data$Bait) > 1)) {p <- p + facet_wrap(~Bait, scales="free_y")}
-      return(ggsave(p, width=8,height=4,filename = "bubble_NSAF.png"))
-    }
-  }
-###################################################################################################
-# Plot all proteins for each bait by x=Saintscore, y=Log2(FoldChange)
-###################################################################################################
-bubble_SAINT <- function(data, color) {
-    if(color=="crapome") {
-      a <- subset(data, CrapomePCT <80, select = c(NSAF,SpecSum, CrapomePCT, FoldChange, SaintScore, Bait)) #filter on CRAPome
-      b <- subset(data, CrapomePCT >=80, select = c(NSAF,SpecSum, CrapomePCT, FoldChange, SaintScore, Bait))
-      p <- qplot(x=SaintScore, y=log2(FoldChange), data=a, colour=I("tan"),size=SpecSum) + 
-        scale_size(range=c(1,10)) + geom_point(aes(x=SaintScore,y=log2(FoldChange), size=SpecSum), colour="black", shape=21, data=a)
-      if(length(levels(a$Bait) > 1)) {p <- p + facet_wrap(~Bait, scales="free_y")}
-      p <- p + geom_point(aes(x=SaintScore,y=log2(FoldChange), size=SpecSum, color=CrapomePCT), data=b) + 
-        scale_colour_gradient(limits=c(80, 100), low="tan", high="red") + 
-        labs(colour="CRAPome Probability \nof Specific Interaction (%)") +
-        geom_point(aes(x=SaintScore,y=log2(FoldChange), size=SpecSum), colour="black", shape=21, data=b)
-      return(ggsave(p, width=8,height=4,filename = "bubble_SAINT.png"))
-    }
-    if(color != "crapome") {
-      p <- qplot(x=SaintScore, y=log2(FoldChange), data=data, colour=I(color),size=SpecSum) +
-        scale_size(range=c(1,10)) + geom_point(aes(x=SaintScore,y=log2(FoldChange), size=SpecSum), colour="black", shape=21, data=data)
-      if(length(levels(data$Bait) > 1)) {p <- p + facet_wrap(~Bait, scales="free_y")}
-      return(ggsave(p, width=8,height=4,filename = "bubble_SAINT.png"))
-    }
-  }
-###################################################################################################
-# Filter proteins on Saintscore cutoff and plot for each bait x=Saintscore, y=Log2(FoldChange)
-###################################################################################################
-bubble_zoom_SAINT <- function(data, color, label=FALSE, cutoff=0.8) {
-  if(color=="crapome") {
-    a <- subset(data, CrapomePCT <80 & SaintScore>=cutoff, select = c(NSAF,SpecSum, CrapomePCT, FoldChange, SaintScore, Bait, PreyGene))
-    b <- subset(data, CrapomePCT >=80 & SaintScore >=cutoff, select = c(NSAF,SpecSum, CrapomePCT, FoldChange, SaintScore, Bait, PreyGene))
-    p <- qplot(x=SaintScore, y=log2(FoldChange), data=a, colour=I("tan"),size=SpecSum) + 
-      scale_size(range=c(1,10)) + ggtitle("Filtered on SAINT score")+geom_point(aes(x=SaintScore,y=log2(FoldChange), size=SpecSum), colour="black", shape=21, data=a)
-    if(label==TRUE & length(a$NSAF!=0)) {
-      p <- p + geom_text(data=a, aes(label=PreyGene, size=10, vjust=0, hjust=0),colour="black")
-    }
-    if(length(levels(a$Bait) > 1)) {p <- p + facet_wrap(~Bait, scales="free_y")}
-    p <- p + geom_point(aes(x=SaintScore,y=log2(FoldChange), size=SpecSum, color=CrapomePCT), data=b) + 
-      scale_colour_gradient(limits=c(80, 100), low="tan", high="red") + 
-      labs(colour="CRAPome Probability \nof Specific Interaction (%)") + 
-      geom_point(aes(x=SaintScore,y=log2(FoldChange), size=SpecSum), colour="black", shape=21, data=b)
-    if(label==TRUE & length(b$NSAF!=0)) {
-      p <- p + geom_text(data=b, aes(label=PreyGene, size=10, vjust=0, hjust=0),colour="black", show_guide=FALSE)
-    }
-    return(ggsave(p, width=8,height=4,filename = "bubble_zoom_SAINT.png"))
-  }
-  if(color != "crapome") {
-    a <- subset(data, SaintScore>=cutoff, select = c(NSAF,SpecSum, FoldChange, SaintScore, Bait, PreyGene))
-    p <- qplot(x=SaintScore, y=log2(FoldChange), data=a, colour=I(color),size=SpecSum) +
-      scale_size(range=c(1,10)) + ggtitle("Filtered on SAINT score") + 
-      geom_point(aes(x=SaintScore,y=log2(FoldChange), size=SpecSum), colour="black", shape=21, data=a)
-    if(label==TRUE & length(a$NSAF!=0)) {
-      p <- p + geom_text(data=a, aes(label=PreyGene, size=10, vjust=0, hjust=0),colour="black", show_guide=FALSE)
-    }
-    if(length(levels(data$Bait) > 1)) {p <- p + facet_wrap(~Bait, scales="free_y")}
-    return(ggsave(p, width=8,height=4,filename = "bubble_zoom_SAINT.png"))
-  }
-}
-###################################################################################################
-# Filter proteins on Saintscore cutoff and plot for each bait x=log(NSAF), y=Log2(FoldChange)
-###################################################################################################
-bubble_zoom_NSAF <- function(data, color, label=FALSE, cutoff=0.8) {
-  if(color=="crapome") {
-    a <- subset(data, CrapomePCT <80 & SaintScore>=cutoff, select = c(NSAF,SpecSum, CrapomePCT, FoldChange, SaintScore, Bait, PreyGene))
-    b <- subset(data, CrapomePCT >=80 & SaintScore >=cutoff, select = c(NSAF,SpecSum, CrapomePCT, FoldChange, SaintScore, Bait, PreyGene))
-    p <- qplot(x=log(NSAF), y=log2(FoldChange), data=a, colour=I("tan"),size=SpecSum) + 
-      scale_size(range=c(1,10)) + ggtitle("Filtered on SAINT score") + 
-      geom_point(aes(x=log(NSAF),y=log2(FoldChange), size=SpecSum), colour="black", shape=21, data=a)
-    if(label==TRUE & length(a$NSAF!=0)) {
-      p <- p + geom_text(data=a, aes(label=PreyGene, size=10, vjust=0, hjust=0),colour="black")
-    }
-    if(length(levels(a$Bait) > 1)) {p <- p + facet_wrap(~Bait, scales="free_y")}
-    p <- p + geom_point(aes(x=log(NSAF),y=log2(FoldChange), size=SpecSum, color=CrapomePCT), data=b) + 
-      scale_colour_gradient(limits=c(80, 100), low="tan", high="red") + 
-      labs(colour="CRAPome Probability \nof Specific Interaction (%)", x="ln(NSAF)") + 
-      geom_point(aes(x=log(NSAF),y=log2(FoldChange), size=SpecSum), colour="black", shape=21, data=b)
-    if(label==TRUE & length(b$NSAF!=0)) {
-      p <- p + geom_text(data=b, aes(label=PreyGene, size=10, vjust=0, hjust=0),colour="black", show_guide=FALSE)
-    }
-    return(ggsave(p, width=8,height=4,filename = "bubble_zoom_NSAF.png"))
-  }
-  if(color != "crapome") {
-    a <- subset(data, SaintScore>=cutoff, select = c(NSAF,SpecSum, FoldChange, SaintScore, Bait, PreyGene))
-    p <- qplot(x=log(NSAF), y=log2(FoldChange), data=a, colour=I(color), size=SpecSum) +
-      scale_size(range=c(1,10)) + ggtitle("Filtered on SAINT score") + 
-      geom_point(aes(x=log(NSAF),y=log2(FoldChange), size=SpecSum), colour="black", shape=21, data=a) + 
-      labs(x="ln(NSAF)")
-    if(label==TRUE & length(a$NSAF!=0)) {
-      p <- p + geom_text(data=a, aes(label=PreyGene, size=10, vjust=0, hjust=0),colour="black", show_guide=FALSE)
-    }
-    if(length(levels(data$Bait) > 1)) {p <- p + facet_wrap(~Bait, scales="free_y")}
-    return(ggsave(p, width=8,height=4,filename = "bubble_zoom_NSAF.png"))
-  }
-}
-###################################################################################################
-# Check Saintscore cutoff and stop program if not between 0 and 1
-###################################################################################################
-cutoff_check <- function(cutoff){
-  if( any(cutoff < 0 | cutoff > 1) ) stop('SAINT score cutoff not between 0 and 1. Please correct and try again')
-}
-
-args <- commandArgs(trailingOnly = TRUE)
-main(args[1],args[2],args[3],args[4],args[5],args[6],args[7],args[8],args[9])
-
-#main("test_list.txt", "preytest.txt", crapome="craptest.txt", color="crapome", label=TRUE)
-#main("Crizo_list.txt", "prey_cr.txt", crapome = "crizo_crap.txt", color="crapome", label=TRUE, cutoff=0.7)
-#main("test_list.txt", "preytest.txt", crapome=FALSE, color="magenta", label=FALSE, cutoff=1.1)
\ No newline at end of file