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1 import sys
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2 import os
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3 from time import sleep
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4
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5 files = sys.argv[1] # read in a string of file names seperated by ", "
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6 # e.g. "Default_Protein_Report.txt, Default_Protein_Report_2.txt"
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7 #bait = sys.argv[2] # SAINT formatted bait file
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8 # still need a way to match files to bait identifiers
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9 # or they can just be required to be put in the order of the bait file
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10 quant_type = sys.argv[3] # what metric to use for quantification
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11 # "#Validated Peptides", "#Peptides", "#Unique", "#Validated PSMs", "#PSMs"
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12 db = sys.argv[4] # fasta database used in SearchGUI and PeptideShaker
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13 prey = sys.argv[5]
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14 tool_path = sys.argv[7]
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15 if db == "None":
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16 db = str(tool_path) + "/SwissProt_HUMAN_2015_12.fasta"
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17 make_bait = sys.argv[6]
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18 bait_bool = sys.argv[8]
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19
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20 def bait_create(baits, infile):
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21 # Verifies the Baits are valid in the Scaffold file and writes the Bait.txt.
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22 baits = make_bait.split()
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23 i = 0
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24 bait_file_tmp = open("bait.txt", "w")
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25 order = []
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26 bait_cache = []
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27 while i < len(baits):
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28 if baits[i+2] == "true":
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29 T_C = "C"
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30 else:
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31 T_C = "T"
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32 bait_line = baits[i] + "\t" + baits[i+1] + "\t" + T_C + "\n"
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33 bait_cache.append(str(bait_line))
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34 i = i + 3
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35
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36 for cache_line in bait_cache:
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37 bait_file_tmp.write(cache_line)
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38
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39 bait_file_tmp.close()
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40
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41 if bait_bool == 'false':
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42 bait_create(make_bait, infile)
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43 bait = "bait.txt"
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44 else:
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45 bait_temp_file = open(sys.argv[9], 'r')
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46 bait_cache = bait_temp_file.readlines()
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47 bait_file_tmp = open("bait.txt", "wr")
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48 for cache_line in bait_cache:
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49 bait_file_tmp.write(cache_line)
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50 bait_file_tmp.close()
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51 bait = "bait.txt"
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52
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53 class ReturnValue1(object):
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54 def __init__(self, sequence, gene):
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55 self.seqlength = sequence
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56 self.genename = gene
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57
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58 def read_tab(infile):
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59 with open(infile,'r') as x:
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60 output = []
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61 for line in x:
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62 line = line.strip()
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63 temp = line.split('\t')
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64 output.append(temp)
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65 return output
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66 def printProgress (iteration, total, prefix = '', suffix = '', decimals = 1, barLength = 100):
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67 """
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68 Call in a loop to create terminal progress bar
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69 @params:
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70 iteration - Required : current iteration (Int)
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71 total - Required : total iterations (Int)
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72 prefix - Optional : prefix string (Str)
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73 suffix - Optional : suffix string (Str)
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74 decimals - Optional : positive number of decimals in percent complete (Int)
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75 barLength - Optional : character length of bar (Int)
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76 """
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77 formatStr = "{0:." + str(decimals) + "f}"
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78 percents = formatStr.format(100 * (iteration / float(total)))
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79 filledLength = int(round(barLength * iteration / float(total)))
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80 bar = '=' * filledLength + '-' * (barLength - filledLength)
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81 sys.stdout.write('\r%s |%s| %s%s %s' % (prefix, bar, percents, '%', suffix)),
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82 sys.stdout.flush()
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83 if iteration == total:
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84 sys.stdout.write('\n')
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85 sys.stdout.flush()
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86 def get_info(uniprot_accession_in,fasta_db):
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87 # Get aminoacid lengths and gene name.
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88 error = open('error proteins.txt', 'a+')
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89 data = open(fasta_db, 'r')
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90 data_lines = data.readlines()
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91 db_len = len(data_lines)
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92 seqlength = 0
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93 count = 0
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58
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94 last_line = data_lines[-1]
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56
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95 for data_line in data_lines:
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96 if ">sp" in data_line:
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97 namer = data_line.split("|")[2]
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98 if uniprot_accession_in == data_line.split("|")[1]:
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99 match = count + 1
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100 if 'GN=' in data_line:
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101 lst = data_line.split('GN=')
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102 lst2 = lst[1].split(' ')
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103 genename = lst2[0]
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104 if 'GN=' not in data_line:
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105 genename = 'NA'
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106 while ">sp" not in data_lines[match]:
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107 if match <= db_len:
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108 seqlength = seqlength + len(data_lines[match].strip())
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58
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109 if data_lines[match] == last_line:
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110 break
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56
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111 match = match + 1
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112 else:
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113 break
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114 return ReturnValue1(seqlength, genename)
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115 if uniprot_accession_in == namer.split(" ")[0]:
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116 match = count + 1
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117 # Ensures consistent spacing throughout.
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118 if 'GN=' in data_line:
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119 lst = data_line.split('GN=')
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120 lst2 = lst[1].split(' ')
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121 genename = lst2[0]
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122 if 'GN=' not in data_line:
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123 genename = 'NA'
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124 while ">sp" not in data_lines[match]:
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125 if match <= db_len:
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126 seqlength = seqlength + len(data_lines[match].strip())
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58
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127 if data_lines[match] == last_line:
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128 break
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56
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129 match = match + 1
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130 else:
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131 break
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132 return ReturnValue1(seqlength, genename)
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133 count = count + 1
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134 if seqlength == 0:
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135 error.write(uniprot_accession_in + '\t' + "Uniprot not in Fasta" + '\n')
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136 error.close
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137 seqlength = 'NA'
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138 genename = 'NA'
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139 return ReturnValue1(seqlength, genename)
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140 def concatenate_files(file_list_string, bait_file):
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141 file_list = file_list_string.split(",")
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142 bait = read_tab(bait_file)
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143 master_table = []
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144 header_check = 0
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145 file_cnt = 0
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146 table_cnt = 0
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147 for i in file_list:
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148 table = read_tab(i)
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149 for j in table:
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150 if table_cnt == 0:
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151 if header_check == 0:
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152 header_check +=1
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153 j.append("Replicate")
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154 j.append("Bait_Grouping")
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155 master_table.append(j)
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156 if table_cnt > 0:
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157 j.append(bait[file_cnt][0])
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158 j.append(bait[file_cnt][1])
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159 master_table.append(j)
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160 table_cnt +=1
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161 file_cnt+=1
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162 table_cnt = 0
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163 if len(master_table[0]) < len(master_table[1]):
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164 master_table[0] = ["#"] + master_table[0]
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165 with open("merged_PeptideShaker.txt","w") as x:
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166 for i in master_table:
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167 x.write("\t".join(i))
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168 x.write("\n")
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169 return master_table
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170 def make_inter(master_table,quant_type):
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171 if len(master_table[0]) < len(master_table[1]):
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172 master_table[0] = ["#"] + master_table[0]
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173 replicate_index = master_table[0].index("Replicate")
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174 grouping_index = master_table[0].index("Bait_Grouping")
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175 accession_index = master_table[0].index("Main Accession")
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176 quant_type = quant_type.replace("_", " ")
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177 quant_type = r"#" + quant_type
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178 Quant_index = master_table[0].index(quant_type)
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179 inter_file = ""
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180 for i in master_table[1:]:
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181 line = []
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182 line.append(i[replicate_index])
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183 line.append(i[grouping_index])
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184 line.append(i[accession_index])
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185 line.append(i[Quant_index])
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186 inter_file = inter_file + "\t".join(line) + "\n"
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187 with open("inter.txt","w") as x:
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188 x.write(inter_file)
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189
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190 def make_prey(concat_table,fasta_db):
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191 input_data = concat_table
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192 if len(input_data[0]) < len(input_data[1]):
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193 input_data[0] = ["#"] + input_data[0]
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194 accession_index = input_data[0].index("Main Accession")
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195 proteins = []
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196 for i in input_data[1:]:
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197 proteins.append(i[accession_index])
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198 output_file = open("prey.txt", 'w')
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199 start = 0
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200 end = len(proteins)
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201
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202 # Initial call to print 0% progress
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203 printProgress(start, end, prefix = 'Progress:', suffix = 'Complete', barLength = 50)
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204
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205 for protein in proteins:
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206 seq = get_info(protein,fasta_db).seqlength
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207 GN = get_info(protein,fasta_db).genename
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208 if seq != 'NA':
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209 output_file.write(protein + "\t" + str(seq) + "\t" + str(GN) + "\n")
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210 start+=1
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211 printProgress(start, end, prefix = 'Progress:', suffix = 'Complete', barLength = 50)
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212 output_file.close()
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213 data = concatenate_files(files,bait)
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214 make_inter(data, quant_type)
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215 if prey == "true":
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216 make_prey(data,db)
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217
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218 os.rename("bait.txt", sys.argv[2])
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219 os.rename("inter.txt", sys.argv[10])
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220 if str(prey) != "None":
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221 os.rename("prey.txt", sys.argv[11]) |
