changeset 22:503f1c1bac0c draft

Deleted selected files

--- a/Bubblebeam_For_SAINT_wrapper.py	Fri Nov 20 12:04:24 2015 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,49 +0,0 @@
-import os 
-import sys
-import time
-
-
-list_file = sys.argv[1]
-prey_file = sys.argv[2]
-crapome = sys.argv[3]
-color = sys.argv[4]
-label = sys.argv[5]
-cutoff = sys.argv[6]
-mq_sc = sys.argv[7]
-inc_file = sys.argv[8]
-exc_file = sys.argv[9]
-output_file_name = sys.argv[10]
-bub_zoom_NSAF = sys.argv[11]
-bub_zoom_SAINT =sys.argv[12]
-bub_SAINT = sys.argv[13]
-bub_NSAF = sys.argv[14]
-ins_path =sys.argv[15]
-
-if crapome == "None":
-	crapome = "FALSE"
-
-
-if label == "false":
-	label = "FALSE"
-elif label == "true":
-	label = "TRUE" 
-
-cmd = r"Rscript "+ str(ins_path) + r"/bubbles_v9_NSAF_natural_log.R " + str(list_file) + r" " + str(prey_file) + r" " + str(crapome) + r" " + str(color) + r" " + str(label) + r" " + str(cutoff) + r" " + str(mq_sc) + r" " + str(inc_file) + r" " + str(exc_file)
-os.system(cmd)
-time.sleep(3)
-
-open('./output.txt')
-os.rename('output.txt', str(output_file_name))
-
-open('./bubble_zoom_NSAF.png')
-os.rename('bubble_zoom_NSAF.png', str(bub_zoom_NSAF))
-
-open('./bubble_zoom_SAINT.png')
-os.rename('bubble_zoom_SAINT.png', str(bub_zoom_SAINT))
-
-open('./bubble_SAINT.png')
-os.rename('bubble_SAINT.png', str(bub_SAINT))
-
-open('./bubble_NSAF.png')
-os.rename('bubble_NSAF.png', str(bub_NSAF))
-

--- a/Bubblebeam_For_SAINT_wrapper.xml	Fri Nov 20 12:04:24 2015 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,132 +0,0 @@
-<tool id="Bubblebeam_For_SAINT" name="Bubblebeam For SAINT">
-  <description></description>
-  <command interpreter="python">Bubblebeam_For_SAINT_wrapper.py $list_file $prey_file $crapome $color $label $cutoff $type $inc_file $exc_file $outfile $NSAF_zoom $SAINT_zoom $SAINT $NSAF \$INSTALL_RUN_PATH/</command>
-  <requirements>
-    <requirement type="set_environment">INSTALL_RUN_PATH</requirement>
-    <requirement type="package" version="3.2.1">package_r_3_2_1</requirement>
-  </requirements>
-  <inputs>
-    <param type="select" name="type" label="MaxQuant or Scaffold">
-      <option value="MQ">MaxQuant</option>
-      <option value="SC">Scaffold</option> 
-    </param>
-    <param format="txt" name="list_file" type="data" label="List File"/>
-    <param format="txt" name="prey_file" type="data" label="Prey File"/>
-    <param format="txt" name="crapome" type="data" label="Crapome File" optional="true"/>
-    <param name="color" type="select" label="Color">
-        <option value="crapome">Crapome</option>
-        <option value="red">Red</option>
-        <option value="blue">Blue</option>
-    </param>
-    <param type="boolean" name="label" checked="true" label="Use Labels"/>
-    <param type="float" name="cutoff" label="SAINT Score Cutoff" help="Select a value between 0 and 1 written like 0.8." value="0.8"/>
-    <param format="txt" name="inc_file" type="data" label="List of Uniprot IDs to Include" optional="true"/>
-    <param format="txt" name="exc_file" type="data" label="List of Uniprot IDs to Include" optional="true"/>
-  </inputs>
-  <outputs>
-    <data format="txt" name="outfile" label="Outfile"/>    
-    <data format="png" name="NSAF_zoom" label="Zoom NSAF" />
-    <data format="png" name="SAINT_zoom" label="Zoom SAINT" />
-    <data format="png" name="NSAF" label="NSAF" />
-    <data format="png" name="SAINT" label="SAINT" />
-  </outputs>
-  <stdio>
-    <regex match="error"
-	   source="stdout"
-           level="fatal"
-           description="Unknown error"/>
-  </stdio> 
-
-  <tests>
-    <test>
-      <param name="input" value="fa_gc_content_input.fa"/>
-      <output name="out_file1" file="fa_gc_content_output.txt"/>
-    </test>
-  </tests>
-  <help>
-Post-processing:
-Once SAINTexpress has been run, APOSTL is able to read the resulting "list.txt" file. Fromhere APOSTL does a number of things:
-
-APOSTL calculates NSAF values for each prey based on the average spectra observed for each bait
-
-OPTIONAL: APOSTL calculates the probability of a specific interaction based on prey revalence in the CRAPome 
-
-Bubble graphs are generated for each bait where:
-
-- x axis is the natural log of the NSAF values
-
-- y axis is the observed log2 fold change (as compared to control)
-
-- bubble radius is proportional to the average observed spectra
-
-OPTIONAL: bubble color corresponds to the CRAPome probability of a specific interaction in which an 80% cutoff is applied where prey with less than 80% are colored tan
-
-APOSTL queries ConsensusPathDB for protein-protein interactions within your data and then formats the resulting network for simple cytoscape import using the "import network from file" option.
-
-INPUTS:
-
-List File: 
-
-- SAINTexpress generated "list.txt" file
-
-Prey File:
-
-- SAINT pre-processing generated "prey.txt" file used to run SAINTexpress
-
-Crapome File:
-
-- raw output from Crapome Workflow 1 query (http://www.crapome.org)
-
-Color:
-
-- Specify the color of the bubbles within the graph.
-
-- If "crapome" is chosen and 'crapome' file is specified, bubbles will be color based on crapome specificity
-
-Use labels:
-
-- Adds gene name labels to bubbles within the "zoomed in" graphs
-SAINT Score Cutoff:
-
-- Choose Saintscore cutoff (between 0-1) to be used for filtering the "zoomed in" graphs (default = 0.8)
-
-- Also used for filtering during the generation of the cytoscape network
-
-Species:
-
-- Human, mouse, or yeast
-
-Interaction Confidence:
-
-- Interaction confidence value (0-1) used to filter the interactions with the ConsensusPathDB database
-
-- Suggestions:
-
-* low: 0
-
-* medium: 0.5
-
-* high: 0.7
-
-* very high: 0.9
-
-OUTPUTS:
-
-Bubble Graphs:
-
-- Unfiltered Data:
-
-* NSAF v. Log2(FoldChange)
-
-* SAINTscore v. Log2(FoldChange)
-
-- Filtered by SAINT Score
-
-* NSAF v. Log2(FoldChange)
-
-* SAINTscore v. Log2(FoldChange)  
-
-Output.txt
-- SAINTexpress "list.txt" output with additional columns that were used during the analysis
-  </help>
-</tool>

--- a/bubbles_v9_NSAF_natural_log.R	Fri Nov 20 12:04:24 2015 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,252 +0,0 @@
-rm(list=ls())
-###################################################################################################
-# R-code: Multi-bubble graph generation from SAINTexpress output
-# Author: Brent Kuenzi
-###################################################################################################
-ins_check_run <- function(){
-  if ('dplyr' %in% rownames(installed.packages())){}
-  else {
-    install.packages('dplyr', repos='http://cran.us.r-project.org')
-  }
-  if ('tidyr' %in% rownames(installed.packages())){}
-  else {
-    install.packages('tidyr', repos='http://cran.us.r-project.org')
-  }
-  if ('ggplot2' %in% rownames(installed.packages())){}
-  else {
-    install.packages('ggplot2', repos='http://cran.us.r-project.org')
-  }
-}
-ins_check_run()
-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)
-      print(inc_prots[,1])
-      print(Saint$Prey)
-      filtered_df = subset(Saint, Saint$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

--- a/tool_dependencies.xml	Fri Nov 20 12:04:24 2015 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,11 +0,0 @@
-<?xml version="1.0"?>
-<tool_dependency>
-	<install version="1.0">
-		<package name="package_r_3_2_1" version="3.2.1">
-			<repository toolshed="toolshed.g2.bx.psu.edu" name="package_r_3_2_1" owner="iuc" changeset_revision="fae49a02a848" prior_installation_required="True"/>
-		</package>
-	</install>
-    <set_environment version="1.0">
-        <environment_variable name="INSTALL_RUN_PATH" action="set_to">$REPOSITORY_INSTALL_DIR</environment_variable>   
-    </set_environment>
-</tool_dependency>
\ No newline at end of file