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1 #######################################################################################
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2 # Python-code: SAINT pre-processing from MaxQuant "Samples Report" output
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3 # Author: Brent Kuenzi
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4 #######################################################################################
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5 # This program reads in a raw MaxQuant "Samples Report" output and a user generated
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6 # bait file and autoformats it into prey and interaction files for SAINTexpress
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7 # analysis
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8 #######################################################################################
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9 # Copyright (C) Brent Kuenzi.
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10 # Permission is granted to copy, distribute and/or modify this document
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11 # under the terms of the GNU Free Documentation License, Version 1.3
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12 # or any later version published by the Free Software Foundation;
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13 # with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts.
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14 # A copy of the license is included in the section entitled "GNU
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15 # Free Documentation License".
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16 #######################################################################################
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17 ## REQUIRED INPUT ##
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18
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19 # 1) infile: MaxQuant "Samples Report" output
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20 # 2) baitfile: SAINT formatted bait file generated in Galaxy
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21 # 3) fasta_db: fasta database for use (defaults to SwissProt_HUMAN_2014_08.fasta)
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22 # 4) prey: Y or N for generating a prey file
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23 # 5) make_bait: String of bait names, assignment, and test or control boolean
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24 #######################################################################################
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25
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26
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27 import sys
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28 import os
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29
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30
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31 mq_file = sys.argv[1]
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32 ins_path = sys.argv[8]
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33 names_path = str(ins_path) + r"uniprot_names.txt"
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29
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34 fasta_db = sys.argv[3]
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35
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36 # Uses faster names list for filtering when default db used.
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37 if fasta_db == "None":
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38 cmd = (r"Rscript "+ str(ins_path) +"pre_process_protein_name_set.R " + str(mq_file) +
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39 " " + str(names_path))
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40 os.system(cmd)
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41 else:
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42 cmd = (r"Rscript "+ str(ins_path) +"pre_process_protein_name_set.R " + str(mq_file) +
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31
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43 " " + str(fasta_db))
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29
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44 os.system(cmd)
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6
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45
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31
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46
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6
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47 infile = "./tukeys_output.txt"
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48 # The MaxQuant "Samples Report" output.
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49 prey = sys.argv[2]
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50 # Y or N boolean from Galaxy.
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51 if fasta_db == "None":
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52 fasta_db = str(ins_path) + "SwissProt_HUMAN_2014_08.fasta"
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53 make_bait = sys.argv[6]
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54 bait_bool = sys.argv[9]
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55
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56 def bait_create(baits, infile):
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57 # Takes the Bait specified by the user and makes them into a Bait file and includes a
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58 # check to make sure they are using valid baits.
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59 baits = make_bait.split()
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60 i = 0
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61 bait_file_tmp = open("bait.txt", "w")
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62 order = []
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63 bait_cache = []
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64 while i < len(baits):
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65 if baits[i+2] == "true":
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66 T_C = "C"
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67 else:
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68 T_C = "T"
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69 bait_line = baits[i] + "\t" + baits[i+1] + "\t" + T_C + "\n"
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70 read_infile = open(infile, "r")
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71 for input_line in read_infile :
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72 input_line = input_line.replace("\"", "")
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73 input_line = input_line.replace(r"Intensity.", "")
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74 # R coerces "-" into "." changes them back and remove Intensity from the Bait names.
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75 input_line = input_line.replace(r".", r"-")
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76 temp = input_line.split()
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77 if "mapped_protein" in str(temp):
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78 if baits[i] in temp:
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79 number_bait = temp.index(str(baits[i]))
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80 number_bait = number_bait - 9
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81 bait_cache.append((number_bait, str(bait_line)))
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82 # Locates the Bait names in the column names and then sets the Baits in the
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83 # correct order in the cache thus the - 9 because the baits start at the 9th
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84 # column.
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85 else:
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86 print "Error: bad bait " + str(baits[i])
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87 sys.exit()
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88 else:
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89 pass
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90 i = i + 3
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91 # Writes cache to Bait file.
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92 bait_cache.sort()
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93 for line in bait_cache:
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94 bait_file_tmp.write(line[1])
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95
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96 bait_file_tmp.close()
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97
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98
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99 if bait_bool == 'false':
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100 bait_create(make_bait, infile)
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101 baitfile = "bait.txt"
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102 else:
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103 bait_temp_file = open(sys.argv[10], 'r')
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104 bait_cache = bait_temp_file.readlines()
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105 bait_file_tmp = open("bait.txt", "wr")
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106 for line in bait_cache:
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107 bait_file_tmp.write(line)
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108 bait_file_tmp.close()
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109 baitfile = "bait.txt"
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110
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111
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112 class ReturnValue1(object):
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113 def __init__(self, sequence, gene):
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114 self.seqlength = sequence
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115 self.genename = gene
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116 class ReturnValue2(object):
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117 def __init__(self, getdata, getproteins, getheader):
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118 self.data = getdata
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119 self.proteins = getproteins
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120 self.header = getheader
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121
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122
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123 def main(MaxQuant_input, make_bait):
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124 #bait_check(baitfile, MaxQuant_input)
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125 make_inter(MaxQuant_input)
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126 if prey == 'true':
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127 make_prey(MaxQuant_input)
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128 no_error_inter(MaxQuant_input)
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129 os.rename('prey.txt', sys.argv[5])
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130 elif prey == 'false':
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131 if os.path.isfile('./error_proteins.txt') == True:
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132 no_error_inter(MaxQuant_input)
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133 pass
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134 elif prey != 'true' or 'false':
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135 sys.exit("Invalid Prey Argument: Y or N")
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136 os.rename('inter.txt', sys.argv[4])
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137 os.rename("bait.txt", sys.argv[7])
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138
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139
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140 def get_info(uniprot_accession_in):
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141 # Get aa lengths and gene name.
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142 error = open('./error_proteins.txt', 'a+')
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143 data = open(fasta_db, 'r')
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144 data_lines = data.readlines()
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145 db_len = len(data_lines)
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146 seqlength = 0
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147 count = 0
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54
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148 last_line = data_lines[-1]
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149 for data_line in data_lines:
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150 if ">sp" in data_line:
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151 if uniprot_accession_in == data_line.split("|")[1]:
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152 match = count + 1
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153 if 'GN=' in data_line:
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154 lst = data_line.split('GN=')
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155 lst2 = lst[1].split(' ')
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156 genename = lst2[0]
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157 if 'GN=' not in data_line:
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158 genename = 'NA'
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159 while ">sp" not in data_lines[match]:
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160 if match <= db_len:
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161 seqlength = seqlength + len(data_lines[match].strip())
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54
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162 if data_lines[match] == last_line:
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163 break
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164 match = match + 1
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165 else:
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166 break
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167 return ReturnValue1(seqlength, genename)
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168 count = count + 1
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169
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170
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171 if seqlength == 0:
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172 error.write(uniprot_accession_in + '\t' + "Uniprot not in Fasta" + '\n')
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173 error.close
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174 seqlength = 'NA'
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175 genename = 'NA'
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176 return ReturnValue1(seqlength, genename)
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177
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178
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179 def readtab(infile):
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180 with open(infile, 'r') as input_file:
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181 # Read in tab-delim text file.
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182 output = []
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183 for input_line in input_file:
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184 input_line = input_line.strip()
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185 temp = input_line.split('\t')
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186 output.append(temp)
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187 return output
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188
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189
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190 def read_MaxQuant(MaxQuant_input):
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191 # Get data, proteins and header from MaxQuant output.
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192 dupes = readtab(MaxQuant_input)
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193 header_start = 0
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194 header = dupes[header_start]
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195 for var_MQ in header:
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196 var_MQ = var_MQ.replace(r"\"", "")
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197 var_MQ = var_MQ.replace(r"Intensity.", r"")
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198 var_MQ = var_MQ.replace(r".", r"-")
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199 data = dupes[header_start+1:len(dupes)]
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200 # Cut off blank line and END OF FILE.
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201 proteins = []
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202 for protein in data:
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203 proteins.append(protein[0])
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204 return ReturnValue2(data, proteins, header)
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205
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206
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207 def make_inter(MaxQuant_input):
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208 bait = readtab(baitfile)
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209 data = read_MaxQuant(MaxQuant_input).data
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210 header = read_MaxQuant(MaxQuant_input).header
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211 proteins = read_MaxQuant(MaxQuant_input).proteins
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212 bait_index = []
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213 for bait_item in bait:
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214 bait_index.append(header.index("mapped_protein") + 1)
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215 # Find just the baits defined in bait file.
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216 with open('inter.txt', 'w') as y:
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217 a = 0; l = 0
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218 for bb in bait:
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219 for lst in data:
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220 y.write(header[bait_index[l]] + '\t' + bb[1] + '\t' + proteins[a] + '\t'
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221 + lst[bait_index[l]] + '\n')
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222 a += 1
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223 if a == len(proteins):
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224 a = 0; l += 1
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225
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226
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227 def make_prey(MaxQuant_input):
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228 proteins = read_MaxQuant(MaxQuant_input).proteins
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229 output_file = open("prey.txt", 'w')
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230 for a in proteins:
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231 a = a.replace("\n", "")
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232 # Remove \n for input into function.
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233 a = a.replace("\r", "")
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234 # Ditto for \r.
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235 seq = get_info(a).seqlength
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236 GN = get_info(a).genename
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237 if seq != 'NA':
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34
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238 if GN != 'NA':
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239 output_file.write(a+"\t"+str(seq)+ "\t" + str(GN) + "\n")
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240 output_file.close()
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241
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242
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243 def no_error_inter(MaxQuant_input):
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244 # Remake inter file without protein errors from Uniprot.
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245 err = readtab("./error_proteins.txt")
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246 bait = readtab(baitfile)
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247 data = read_MaxQuant(MaxQuant_input).data
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248 header = read_MaxQuant(MaxQuant_input).header
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249 header = [MQ_var.replace(r"\"", "") for MQ_var in header]
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250 header = [MQ_var.replace(r"Intensity.", r"") for MQ_var in header]
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251 header = [MQ_var.replace(r".", r"-") for MQ_var in header]
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252 bait_index = []
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253 for bait_item in bait:
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254 bait_index.append(header.index(bait_item[0]))
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255 proteins = read_MaxQuant(MaxQuant_input).proteins
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256 errors = []
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257 valid_prots = []
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258 for e in err:
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259 errors.append(e[0])
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260 for a in proteins:
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261 a = a.replace("\n", "")
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262 # Remove \n for input into function.
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263 a = a.replace("\r", "")
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264 # Ditto for \r.
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265 seq = get_info(a).seqlength
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266 GN = get_info(a).genename
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267 if seq != 'NA':
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268 if GN != 'NA':
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269 valid_prots.append(a)
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270 with open('inter.txt', 'w') as input_file:
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271 l = 0; a = 0
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272 for bb in bait:
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273 for lst in data:
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274 if lst[0] in valid_prots:
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275 input_file.write(header[bait_index[l]] + '\t' + bb[1] + '\t' + lst[0] + '\t' + lst[bait_index[l]] + '\n')
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276 a += 1
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277 if a == len(proteins):
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278 l += 1; a = 0
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279
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280
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281 def bait_check(bait, MaxQuant_input):
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282 # Check that bait names share header titles.
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283 bait_in = readtab(bait)
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284 header = read_MaxQuant(MaxQuant_input).header
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285 for bait in bait_in:
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286 if bait[0] not in header:
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287 sys.exit("Bait must share header titles with MaxQuant output")
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288
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289 if __name__ == '__main__':
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290 main(infile, make_bait)
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