annotate SAINT_preprocessing_mq_pep.py @ 12:3e1b66d58f94 draft

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author bornea
date Tue, 12 Apr 2016 13:24:36 -0400
parents 0fed3fc380c7
children bd71998aec8d
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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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34 cmd = (r"Rscript "+ str(ins_path) +"pre_process_protein_name_set.R " + str(mq_file) +
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35 " " + str(names_path))
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36 os.system(cmd)
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37
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38 infile = "./tukeys_output.txt"
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39 # The MaxQuant "Samples Report" output.
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40 prey = sys.argv[2]
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41 # Y or N boolean from Galaxy.
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42 fasta_db = sys.argv[3]
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43 if fasta_db == "None":
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44 fasta_db = str(ins_path) + "SwissProt_HUMAN_2014_08.fasta"
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45 make_bait = sys.argv[6]
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46 bait_bool = sys.argv[9]
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47
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48 def bait_create(baits, infile):
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49 # Takes the Bait specified by the user and makes them into a Bait file and includes a
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50 # check to make sure they are using valid baits.
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51 baits = make_bait.split()
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52 i = 0
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53 bait_file_tmp = open("bait.txt", "w")
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54 order = []
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55 bait_cache = []
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56 while i < len(baits):
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57 if baits[i+2] == "true":
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58 T_C = "C"
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59 else:
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60 T_C = "T"
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61 bait_line = baits[i] + "\t" + baits[i+1] + "\t" + T_C + "\n"
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62 read_infile = open(infile, "r")
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63 for input_line in read_infile :
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64 input_line = input_line.replace("\"", "")
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65 input_line = input_line.replace(r"Intensity.", "")
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66 # R coerces "-" into "." changes them back and remove Intensity from the Bait names.
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67 input_line = input_line.replace(r".", r"-")
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68 temp = input_line.split()
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69 if "mapped_protein" in str(temp):
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70 if baits[i] in temp:
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71 number_bait = temp.index(str(baits[i]))
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72 number_bait = number_bait - 9
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73 bait_cache.append((number_bait, str(bait_line)))
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74 # Locates the Bait names in the column names and then sets the Baits in the
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75 # correct order in the cache thus the - 9 because the baits start at the 9th
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76 # column.
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77 else:
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78 print "Error: bad bait " + str(baits[i])
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79 sys.exit()
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80 else:
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81 pass
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82 i = i + 3
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83 # Writes cache to Bait file.
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84 bait_cache.sort()
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85 for line in bait_cache:
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86 bait_file_tmp.write(line[1])
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87
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88 bait_file_tmp.close()
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89
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90
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91 if bait_bool == 'false':
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92 bait_create(make_bait, infile)
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93 baitfile = "bait.txt"
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94 else:
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95 bait_temp_file = open(sys.argv[10], 'r')
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96 bait_cache = bait_temp_file.readlines()
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97 bait_file_tmp = open("bait.txt", "wr")
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98 for line in bait_cache:
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99 bait_file_tmp.write(line)
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100 bait_file_tmp.close()
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101 baitfile = "bait.txt"
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102
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103
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104 class ReturnValue1(object):
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105 def __init__(self, sequence, gene):
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106 self.seqlength = sequence
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107 self.genename = gene
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108 class ReturnValue2(object):
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109 def __init__(self, getdata, getproteins, getheader):
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110 self.data = getdata
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111 self.proteins = getproteins
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112 self.header = getheader
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113
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114
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115 def main(MaxQuant_input, make_bait):
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116 #bait_check(baitfile, MaxQuant_input)
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117 make_inter(MaxQuant_input)
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118 if prey == 'true':
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119 make_prey(MaxQuant_input)
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120 no_error_inter(MaxQuant_input)
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121 os.rename('prey.txt', sys.argv[5])
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122 elif prey == 'false':
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123 if os.path.isfile('error proteins.txt') == True:
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124 no_error_inter(MaxQuant_input)
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125 pass
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126 elif prey != 'true' or 'false':
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127 sys.exit("Invalid Prey Argument: Y or N")
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128 os.rename('inter.txt', sys.argv[4])
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129 os.rename("bait.txt", sys.argv[7])
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130
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131
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132 def get_info(uniprot_accession_in):
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133 # Get aa lengths and gene name.
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134 error = open('error proteins.txt', 'a+')
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135 data = open(fasta_db, 'r')
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136 data_lines = data.readlines()
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137 db_len = len(data_lines)
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138 seqlength = 0
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139 count = 0
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140 for data_line in data_lines:
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141 if ">sp" in data_line:
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142 if uniprot_accession_in == data_line.split("|")[1]:
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143 match = count + 1
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144 if 'GN=' in data_line:
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145 lst = data_line.split('GN=')
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146 lst2 = lst[1].split(' ')
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147 genename = lst2[0]
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148 if 'GN=' not in data_line:
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149 genename = 'NA'
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150 while ">sp" not in data_lines[match]:
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151 if match <= db_len:
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152 seqlength = seqlength + len(data_lines[match].strip())
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153 match = match + 1
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154 else:
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155 break
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156 return ReturnValue1(seqlength, genename)
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157 count = count + 1
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158
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159
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160 if seqlength == 0:
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161 error.write(uniprot_accession_in + '\t' + "Uniprot not in Fasta" + '\n')
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162 error.close
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163 seqlength = 'NA'
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164 genename = 'NA'
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165 return ReturnValue1(seqlength, genename)
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166
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167
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168 def readtab(infile):
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169 with open(infile, 'r') as input_file:
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170 # Read in tab-delim text file.
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171 output = []
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172 for input_line in input_file:
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173 input_line = input_line.strip()
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174 temp = input_line.split('\t')
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175 output.append(temp)
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176 return output
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177
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178
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179 def read_MaxQuant(MaxQuant_input):
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180 # Get data, proteins and header from MaxQuant output.
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181 dupes = readtab(MaxQuant_input)
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182 header_start = 0
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183 header = dupes[header_start]
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184 for var_MQ in header:
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185 var_MQ = var_MQ.replace(r"\"", "")
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186 var_MQ = var_MQ.replace(r"Intensity.", r"")
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187 var_MQ = var_MQ.replace(r".", r"-")
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188 data = dupes[header_start+1:len(dupes)]
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189 # Cut off blank line and END OF FILE.
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190 proteins = []
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191 for protein in data:
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192 proteins.append(protein[0])
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193 return ReturnValue2(data, proteins, header)
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194
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195
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196 def make_inter(MaxQuant_input):
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197 bait = readtab(baitfile)
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198 data = read_MaxQuant(MaxQuant_input).data
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199 header = read_MaxQuant(MaxQuant_input).header
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200 proteins = read_MaxQuant(MaxQuant_input).proteins
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201 bait_index = []
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202 for bait_item in bait:
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203 bait_index.append(header.index("mapped_protein") + 1)
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204 # Find just the baits defined in bait file.
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205 with open('inter.txt', 'w') as y:
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206 a = 0; l = 0
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207 for bb in bait:
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208 for lst in data:
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209 y.write(header[bait_index[l]] + '\t' + bb[1] + '\t' + proteins[a] + '\t'
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210 + lst[bait_index[l]] + '\n')
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211 a += 1
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212 if a == len(proteins):
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213 a = 0; l += 1
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214
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215
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216 def make_prey(MaxQuant_input):
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217 proteins = read_MaxQuant(MaxQuant_input).proteins
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bornea
parents:
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218 output_file = open("prey.txt", 'w')
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bornea
parents:
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219 for a in proteins:
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bornea
parents:
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220 a = a.replace("\n", "")
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bornea
parents:
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221 # Remove \n for input into function.
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bornea
parents:
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222 a = a.replace("\r", "")
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bornea
parents:
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223 # Ditto for \r.
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bornea
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224 seq = get_info(a).seqlength
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bornea
parents:
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225 GN = get_info(a).genename
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bornea
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226 if seq != 'NA':
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bornea
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227 output_file.write(a+"\t"+str(seq)+ "\t" + str(GN) + "\n")
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bornea
parents:
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228 output_file.close()
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bornea
parents:
diff changeset
229
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bornea
parents:
diff changeset
230
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bornea
parents:
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231 def no_error_inter(MaxQuant_input):
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bornea
parents:
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232 # Remake inter file without protein errors from Uniprot.
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bornea
parents:
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233 err = readtab("error proteins.txt")
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bornea
parents:
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234 bait = readtab(baitfile)
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bornea
parents:
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235 data = read_MaxQuant(MaxQuant_input).data
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bornea
parents:
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236 header = read_MaxQuant(MaxQuant_input).header
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bornea
parents:
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237 header = [MQ_var.replace(r"\"", "") for MQ_var in header]
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bornea
parents:
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238 header = [MQ_var.replace(r"Intensity.", r"") for MQ_var in header]
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bornea
parents:
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239 header = [MQ_var.replace(r".", r"-") for MQ_var in header]
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bornea
parents:
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240 bait_index = []
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bornea
parents:
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241 for bait_item in bait:
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bornea
parents:
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242 bait_index.append(header.index(bait_item[0]))
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bornea
parents:
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243 proteins = read_MaxQuant(MaxQuant_input).proteins
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bornea
parents:
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244 errors = []
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bornea
parents:
diff changeset
245 for e in err:
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bornea
parents:
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246 errors.append(e[0])
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bornea
parents:
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247 with open('inter.txt', 'w') as input_file:
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bornea
parents:
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248 l = 0; a = 0
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bornea
parents:
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249 for bb in bait:
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bornea
parents:
diff changeset
250 for lst in data:
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bornea
parents:
diff changeset
251 if proteins[a] not in errors:
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bornea
parents:
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252 input_file.write(header[bait_index[l]] + '\t' + bb[1] + '\t' + proteins[a] + '\t'
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bornea
parents:
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253 + lst[bait_index[l]] + '\n')
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bornea
parents:
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254 a += 1
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bornea
parents:
diff changeset
255 if a == len(proteins):
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bornea
parents:
diff changeset
256 l += 1; a = 0
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bornea
parents:
diff changeset
257
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bornea
parents:
diff changeset
258
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bornea
parents:
diff changeset
259 def bait_check(bait, MaxQuant_input):
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bornea
parents:
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260 # Check that bait names share header titles.
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bornea
parents:
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261 bait_in = readtab(bait)
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bornea
parents:
diff changeset
262 header = read_MaxQuant(MaxQuant_input).header
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bornea
parents:
diff changeset
263 for bait in bait_in:
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bornea
parents:
diff changeset
264 if bait[0] not in header:
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bornea
parents:
diff changeset
265 sys.exit("Bait must share header titles with MaxQuant output")
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bornea
parents:
diff changeset
266
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bornea
parents:
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267 if __name__ == '__main__':
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bornea
parents:
diff changeset
268 main(infile, make_bait)