Generalize REMc analysis
This commit is contained in:
@@ -1,71 +0,0 @@
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#!/usr/bin/env python
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# This code is to concatenate the batch GO Term Finder results (.tsv) generated from batch GTF perl code(Chris Johnson, U of Tulsa) into a list table
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import sys, os, string, glob
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# return the file list
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def list_all_files(Path):
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list_all_files = []
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list_all_files = glob.glob(Path +'/*.txt.tsv')
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return list_all_files
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# Main function
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try:
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data_file_Path = sys.argv[1]
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output_file_Path = sys.argv[2]
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except:
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print ('Usage: python Concatenate_GTF_results.py /datasetPath /outputFilePath_and_Name')
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print ('Data file not found, error in given directory')
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sys.exit(1)
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# Open the output file
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try:
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output = open(output_file_Path, 'w')
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except OSError:
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print ('output file error')
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# get all the GTF result files in given directory
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File_list = []
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File_list = list_all_files(data_file_Path)
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File_list.sort()
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i = 0
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for file in File_list:
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#parse the file names given in absolute path
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file_name = file.strip().split('/')[-1]
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file_name = file_name.rstrip('.txt.tsv')
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# function to read tsv files from a given directory
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#open the file
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data = open(file,'r')
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#reading the label line
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labelLine = data.readline()
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label = labelLine.strip().split('\t')
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#write the label
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#updates2010July26: update following label writing code
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if i == 0:
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# output.write('cluster origin')
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for element in label:
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output.write(element)
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output.write('\t')
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i = i + 1
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#updates2010July26 End
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#switch to the next line
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output.write('\n')
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#read the GO terms
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GOTermLines = data.readlines()
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for GOTerm in GOTermLines:
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GOTerm = GOTerm.strip().strip('\t')
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if GOTerm != '':
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#updates2010July26: remove the code to write the first column 'REMc cluster ID'
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#output.write(file_name)
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#output.write('\t')
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##updates2010July26 update end
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output.write(GOTerm + '\n')
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#output.write('\n')
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output.close()
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@@ -1,55 +0,0 @@
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#!/usr/bin/perl
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use strict;
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use warnings;
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use diagnostics;
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use File::Map qw(map_file);
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my $infile = shift;
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my $input;
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map_file $input, $infile;
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{
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local $_ = $input;
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(my $f = $infile) =~ s/(.*\/)?(.*)(\.[^\.]*){2}/$2/;
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my %orfgene = (/(Y\w+)\s+(\w+)\n/g);
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my @indices = (/\Q-- \E(\d+) of \d+\Q --\E/g);
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my @ids = (/GOID\s+GO:(\d+)/g);
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my @terms = (/TERM\s+(.*?)\n/g);
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my @pvalues = (/\nCORRECTED P-VALUE\s+(\d.*?)\n/g);
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my @clusterf = (/NUM_ANNOTATIONS\s+(\d+ of \d+)/g);
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my @bgfreq = (/, vs (\d+ of \d+) in the genome/g);
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my @orfs = (/The genes annotated to this node are:\n(.*?)\n/g);
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s/, /:/g for @orfs;
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my @genes;
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for my $orf (@orfs) {
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my @otmp = split /:/, $orf;
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my @gtmp = map { $orfgene{$_} } @otmp;
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push @genes, (join ':', @gtmp);
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}
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&header();
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for my $i (0 .. (@ids - 1)) {
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&report($f, $ids[$i], $terms[$i], $pvalues[$i], $clusterf[$i], $bgfreq[$i], $orfs[$i], $genes[$i]);
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}
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}
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sub header {
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print "REMc ID\tGO_term ID\tGO-term\tCluster frequency\tBackground frequency\tP-value\tORFs\tGenes\n";
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}
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sub report {
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my ($f, $id, $term, $p, $cfreq, $bgfreq, $orfs, $genes) = @_;
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$cfreq =~ /(\d+) of (\d+)/;
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$cfreq = sprintf "%d out of %d genes, %.1f%%", $1, $2, (100*$1/$2);
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$bgfreq =~ /(\d+) of (\d+)/;
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$bgfreq = sprintf "%d out of %d genes, %.1f%%", $1, $2, (100*$1/$2);
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print "$f\t$id\t$term\t$cfreq\t$bgfreq\t$p\t$orfs\t$genes\n";
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}
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File diff suppressed because one or more lines are too long
@@ -1,264 +0,0 @@
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#JoinInteractExps3dev.R
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#User prompt for std Value
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cat("Enter a Standard Deviation value to filter data to be used by REMc ?\n")
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inp <- readLines(file("stdin"), n = 1L)
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cat(paste("Standard Deviation Value is", inp, "\n"))
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inp<- as.numeric(inp)
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#set std deviation multiplier default if no user entry
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if(is.double(inp) & !is.na(inp)){
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std= inp
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}else{std= 2}
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#The input files should be entered in order from the greatest number of rows(Orfs) to least.
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#Args <- commandArgs(TRUE)
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#if(length(Args)==0){
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# std=0
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#}else{
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# std=Args[1]
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#}
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print(paste("SD=",std))
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#Wstudy= getwd()
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#dir.create("../JoinFiles") #(paste0(Wstudy,"/JoinFiles"))
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#outDir <- "../JoinFiles" #paste0(Wstudy,"/JoinFiles")
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#dir.create("../REMc") #(paste0(Wstudy,"/JoinFiles"))
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outDir <- "./" #../REMc" #paste0(Wstudy,"/JoinFiles")
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print(outDir)
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#Args= 'asdf'
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#Args[1]= "../Exp1/ZScores/ZScores_Interaction.csv" #paste0(Wstudy,"/Exp1/ZScores/ZScores_Interaction.csv")
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#Args[2]= "../Exp2/ZScores/ZScores_Interaction.csv" #paste0(Wstudy,"/Exp2/ZScores/ZScores_Interaction.csv")
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#Args[3]= "../Exp3/ZScores/ZScores_Interaction.csv" #paste0(Wstudy,"/Exp1/ZScores/ZScores_Interaction.csv")
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#Args[4]= "../Exp4/ZScores/ZScores_Interaction.csv" #paste0(Wstudy,"/Exp2/ZScores/ZScores_Interaction.csv")
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#Args[3]= "../Exp3/ZScores/ZScores_Interaction.csv" #paste0(Wstudy,"/Exp3/ZScores/ZScores_Interaction.csv")
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inputFile= 'asdf'
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if (file.exists('../Exp1/ZScores/ZScores_Interaction.csv')){
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inputFile <- '../Exp1/ZScores/ZScores_Interaction.csv'
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}
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if (file.exists('../Exp2/ZScores/ZScores_Interaction.csv')){
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inputFile[2] <- '../Exp2/ZScores/ZScores_Interaction.csv'
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}
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if (file.exists('../Exp3/ZScores/ZScores_Interaction.csv')){
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inputFile[3] <- '../Exp3/ZScores/ZScores_Interaction.csv'
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}
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if (file.exists('../Exp4/ZScores/ZScores_Interaction.csv')){
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inputFile[4] <- '../Exp4/ZScores/ZScores_Interaction.csv'
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}
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#Args= inputFile
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#outDir <- ArgsJoin[1] #Output Directory
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print(length(inputFile)) #display the number of arguments on terminal
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#open required library for the join function (libraries must already be install on R)
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library(plyr)
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library(sos)
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library(dplyr)
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#read in the files for your experiment and
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#join the two files at a time as a function of how many inputFile, list the larger file first ? in this example X2 has the larger number of genes.
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#if X1 has a larger number of genes, switch the order of X1 and X2
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if(length(inputFile)==2) {
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X1 <- read.csv(file= inputFile[1],stringsAsFactors = FALSE)
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X2 <- read.csv(file= inputFile[2],stringsAsFactors = FALSE)
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X <- join(X1,X2,by="OrfRep")
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OBH=X[,order(colnames(X))] #OrderByHeader
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headSel= select(OBH, contains('OrfRep'), matches('Gene'), contains('Z_lm_K'), contains('Z_Shift_K'),contains('Z_lm_L'), contains('Z_Shift_L'))
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headSel= select(headSel, -'Gene.1') #remove 'Gene.1 column
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headSel2 = select(OBH, contains('OrfRep'), matches('Gene')) #Frame for interleaving Z_lm with Shift colums
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headSel2 = select(headSel2, -'Gene.1') #remove 'Gene.1 column #Frame for interleaving Z_lm with Shift colums
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}else if(length(inputFile)==3){
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X1 <- read.csv(file= inputFile[1],stringsAsFactors = FALSE) #exp1File,stringsAsFactors = FALSE)
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X2 <- read.csv(file= inputFile[2],stringsAsFactors = FALSE) #exp2File,stringsAsFactors = FALSE)
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X3 <- read.csv(file= inputFile[3],stringsAsFactors = FALSE) #exp3File,stringsAsFactors = FALSE)
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X <- join(X1,X2,by="OrfRep")
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X <- join(X,X3,by="OrfRep")
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OBH=X[,order(colnames(X))] #OrderByHeader
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headSel= select(OBH, contains('OrfRep'), matches('Gene'), contains('Z_lm_K'), contains('Z_Shift_K'),contains('Z_lm_L'), contains('Z_Shift_L'))
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headSel= select(headSel, -'Gene.1',-'Gene.2')
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headSel2 = select(OBH, contains('OrfRep'), matches('Gene'))
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headSel2 = select(headSel2, -'Gene.1',-'Gene.2')
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}else if(length(inputFile)==4){
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X1 <- read.csv(file= inputFile[1],stringsAsFactors = FALSE) #exp1File,stringsAsFactors = FALSE)
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X2 <- read.csv(file= inputFile[2],stringsAsFactors = FALSE) #exp2File,stringsAsFactors = FALSE)
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X3 <- read.csv(file= inputFile[3],stringsAsFactors = FALSE) #exp3File,stringsAsFactors = FALSE)
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X4 <- read.csv(file= inputFile[4],stringsAsFactors = FALSE) #exp4File,stringsAsFactors = FALSE)
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X <- join(X1,X2,by="OrfRep")
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X <- join(X,X3,by="OrfRep")
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X <- join(X,X4,by="OrfRep")
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OBH=X[,order(colnames(X))] #OrderByHeader
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headSel= select(OBH, contains('OrfRep'), matches('Gene'), contains('Z_lm_K'), contains('Z_Shift_K'),contains('Z_lm_L'), contains('Z_Shift_L'))
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headSel= select(headSel, -'Gene.1',-'Gene.2',-'Gene.3')
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headSel2 = select(OBH, contains('OrfRep'), matches('Gene'))
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headSel2 = select(headSel2, -'Gene.1',-'Gene.2',-'Gene.3')
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}
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#headSel$contains('Z_Shift') %>% replace_na(0.001)
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headers<-colnames(headSel)
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i=0
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for(i in 1:length(headers)){
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if(grepl("Shift",headers[i])) {
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headSel[headers[i]][is.na(headSel[headers[i]])] = 0.001
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}
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if(grepl("Z_lm_",headers[i])) {
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headSel[headers[i]][is.na(headSel[headers[i]])] = 0.0001
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}
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}
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#2SD option code to exclude Z_lm values less than 2 standard Deviations
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#+++++++++++++
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REMcRdy= select(headSel, contains('OrfRep'), matches('Gene'), contains('Z_lm_'))
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shiftOnly= select(headSel, contains('OrfRep'), matches('Gene'), contains('Z_Shift'))
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#Code to replace the numeric (.1 .2 .3) headers with experiment names from StudyInfo.txt
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Labels <- read.csv(file= "../Code/StudyInfo.csv",stringsAsFactors = FALSE,sep= ",")
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#Using Text search grepl to relabel headers+++++++++++++++++++++++++++++++++++++++++
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REMcRdyHdr= colnames(REMcRdy)
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REMcRdyLabels= 'asdf'
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shftHdr= colnames(shiftOnly)
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shiftLabels='asdf'
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shiftLabels[1:2]<-shftHdr[1:2]
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REMcRdyLabels[1:2]<-REMcRdyHdr[1:2]
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for(i in 3:(length(shftHdr))){
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if(i==3){
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shiftLabels[3]<-paste0(Labels[1,2],".",shftHdr[3])
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REMcRdyLabels[3]<-paste0(Labels[1,2],".",REMcRdyHdr[3]) }
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if(i==5){
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shiftLabels[5]<-paste0(Labels[1,2],".",shftHdr[5])
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REMcRdyLabels[5]<-paste0(Labels[1,2],".",REMcRdyHdr[5])
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}
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if(i==7){
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shiftLabels[7]<-paste0(Labels[1,2],".",shftHdr[7])
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REMcRdyLabels[7]<-paste0(Labels[1,2],".",REMcRdyHdr[7])
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}
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if(grepl(".1",shftHdr[i],fixed=true)){
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shiftLabels[i]<-paste0(Labels[2,2],".",shftHdr[i])
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REMcRdyLabels[i]<-paste0(Labels[2,2],".",REMcRdyHdr[i])}
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if (grepl(".2",shftHdr[i],fixed=true)){
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shiftLabels[i]<-paste0(Labels[3,2],".",shftHdr[i])
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REMcRdyLabels[i]<-paste0(Labels[3,2],".",REMcRdyHdr[i])}
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if(grepl(".3",shftHdr[i],fixed=true)){
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shiftLabels[i]<-paste0(Labels[4,2],".",shftHdr[i])
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REMcRdyLabels[i]<-paste0(Labels[4,2],".",REMcRdyHdr[i])}
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}
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for(i in 3:(length(REMcRdyLabels))){
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j=as.integer(i)
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REMcRdyLabels[j]<- gsub("[.]", "_", REMcRdyLabels[j])
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shiftLabels[j]<- gsub("[.]", "_", shiftLabels[j])
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}
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colnames(shiftOnly)<- shiftLabels
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colnames(REMcRdy)<- REMcRdyLabels
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#+++++++++++++++++++++++
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combI= headSel2 #Starting Template orf, Genename columns
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#headersRemc<-colnames(REMcRdy)
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#Reoder columns to produce an interleaved set of Z_lm and Shift data for all the cpps.
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for(i in 3:length(colnames(REMcRdy))){
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combI=cbind.data.frame(combI, shiftOnly[i])
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combI=cbind.data.frame(combI, REMcRdy[i])
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}
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#+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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Vec1= NA
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Vec2= NA
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Vec3= NA
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Vec4= NA
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Vec5= NA
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Vec6= NA
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Vec7= NA
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Vec8= NA
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if(length(REMcRdy)== 6){
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Vec1= abs(REMcRdy[,3])>=std
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Vec2= abs(REMcRdy[,4])>=std
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Vec3= abs(REMcRdy[,5])>=std
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Vec4= abs(REMcRdy[,6])>=std
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bolVec= Vec1 | Vec2 |Vec3 |Vec4
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REMcRdyGT2= REMcRdy[bolVec,1:2]
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REMcRdyGT2[ ,3:6]= REMcRdy[bolVec,3:6]
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shiftOnlyGT2= shiftOnly[bolVec,1:2]
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shiftOnlyGT2[ ,3:6]= shiftOnly[bolVec,3:6]
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}
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if(length(REMcRdy)== 8){
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Vec1= abs(REMcRdy[,3])>=std
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Vec2= abs(REMcRdy[,4])>=std
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Vec3= abs(REMcRdy[,5])>=std
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Vec4= abs(REMcRdy[,6])>=std
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Vec5= abs(REMcRdy[,7])>=std
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Vec6= abs(REMcRdy[,8])>=std
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bolVec= Vec1 | Vec2 |Vec3 | Vec4 |Vec5 |Vec6
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REMcRdyGT2= REMcRdy[bolVec,1:2]
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REMcRdyGT2[ ,3:8]= REMcRdy[bolVec,3:8]
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shiftOnlyGT2= shiftOnly[bolVec,1:2]
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shiftOnlyGT2[ ,3:8]= shiftOnly[bolVec,3:8]
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}
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if(length(REMcRdy)== 10){
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Vec1= abs(REMcRdy[,3])>=std
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Vec2= abs(REMcRdy[,4])>=std
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Vec3= abs(REMcRdy[,5])>=std
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Vec4= abs(REMcRdy[,6])>=std
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Vec5= abs(REMcRdy[,7])>=std
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Vec6= abs(REMcRdy[,8])>=std
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Vec7= abs(REMcRdy[,9])>=std
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Vec8= abs(REMcRdy[,10])>=std
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bolVec= Vec1 | Vec2 |Vec3 |Vec4|Vec5|Vec6|Vec7|Vec8
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REMcRdyGT2= REMcRdy[bolVec,1:2]
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REMcRdyGT2[ ,3:10]= REMcRdy[bolVec,3:10]
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shiftOnlyGT2= shiftOnly[bolVec,1:2]
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shiftOnlyGT2[ ,3:10]= shiftOnly[bolVec,3:10]
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}
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if(std!=0){
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REMcRdy= REMcRdyGT2 #[,2:length(REMcRdyGT2)]
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shiftOnly= shiftOnlyGT2 #[,2:length(shiftOnlyGT2)]
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}
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if(std==0){
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REMcRdy= REMcRdy #[,2:length(REMcRdy)]
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shiftOnly= shiftOnly #[,2:length(shiftOnly)]
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}
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#R places hidden "" around the header names. The following
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# is intended to remove those quote so that the "" donot blow up the Java REMc.
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#Use ,quote=F in the write.csv statement to fix R output file.
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print(paste("SD=",std))
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print(getwd())
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#write.csv(combI,file = file.path(outDir,"CombinedKLzscores.csv"),row.names = FALSE)
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write.csv(REMcRdy,file = file.path(outDir,"REMcRdy_lm_only.csv"),row.names = FALSE, quote=F)
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write.csv(shiftOnly,file = file.path(outDir,"Shift_only.csv"),row.names = FALSE, quote=F)
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#LabelStd <- read.table(file= "./Parameters.csv",stringsAsFactors = FALSE,sep= ",")
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pwd=getwd()
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print(getwd)
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LabelStd<- read.csv(file= "../Code/StudyInfo.csv",stringsAsFactors = FALSE)
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print(std)
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LabelStd[,4]= as.numeric(std)
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write.csv(LabelStd,file="../Code/Parameters.csv",row.names = FALSE)
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write.csv(LabelStd,file="../Code/StudyInfo.csv",row.names = FALSE)
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cat(paste("Standard Deviation Value was set as", std, "\n"))
|
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|
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