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1 #!/usr/bin/env python
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2
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3 __author__= "Gianmarco Piccinno"
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4 __version__ = "1.0.0"
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5
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6 from syngenic import *
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7 from functions import *
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8 from Bio import *
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9 import argparse as ap
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10
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11 if __name__ == '__main__':
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12
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13 parser = ap.ArgumentParser(description="", formatter_class=ap.RawTextHelpFormatter)
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14
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15 parser.add_argument(
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16 '-i', '--input_plasmid', help='Input plasmid', required=True)
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17 parser.add_argument(
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18 '-l', '--plasmid_format', help='Format of the plasmid: {fasta, genbank}', required=True)
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19 parser.add_argument(
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20 '-p', '--input_patterns', help='Input patterns separated by new_line', required=True)
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21 parser.add_argument(
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22 '-g', '--input_genome', help='Input annotated genome', required=True)
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23 parser.add_argument(
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24 '-q', '--genome_format', help='Format of the annotated genome: {fasta, gbk}', required=True)
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25 parser.add_argument(
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26 '-c', '--codon_table', help='Codon table to be used {Bacterial}', required=True)
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27 parser.add_argument(
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28 '-m', '--max_row', help='Max row length when print', required=False)
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29 parser.add_argument(
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30 '-d', '--demonstration', help='Use demonstration simplication', required=False)
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31 parser.add_argument(
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32 '-f', '--n_plasmids', help='Use demonstration simplication', required=False)
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33 parser.add_argument(
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34 '-o', '--output_folder', help='Folder for writing the output file', required=True)
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35 args = vars(parser.parse_args())
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36
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37 """
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38
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39 python codon_switch_v2.py
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40 -i ./pEPSA5_annotated.gb
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41 -l genbank
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42 -p ./patterns.txt
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43 -g S_aureus_JE2.gbf
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44 -q gbk -c Bacterial
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45 -o ./output
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46
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47 python codon_switch_v2.py -i ./pEPSA5_annotated.gb -l genbank -p ./patterns.txt -g S_aureus_JE2.gbf -q genbank -c Bacterial -o ./output
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48
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49 """
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50
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51
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52 pl = SeqIO.read(
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53 open(args['input_plasmid'], "r"), args['plasmid_format'])
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54
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55 if args['demonstration'] == "demonstration":
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56 pl = pl[0:3000]
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57 pats = read_patterns(args['input_patterns'])
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58
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59
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60 #############################################################
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61 #
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62 #############################################################
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63
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64 #pl = fake_from_real(path = "./data/pEPSA5_annotated.gb", id_ = "Trial", name = "Fake_plasmid")
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65 print(type(pl))
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66 print(pl); print(pl.seq); print(pl.features)
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67
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68 #for feat in pl.features:
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69 # print(str(feat.extract(pl)))
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70 # print(str(pl[feat.location.start:feat.location.end]))
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71 # print("\n")
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72
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73
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74 n_pl = plasmid(pl)
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75 print(n_pl); print(len(n_pl))
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76 print(n_pl.features)
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77
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78
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79 patts, n_patts = all_patterns(input_ = pats)
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80
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81
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82 f_patts = n_pl.findpatterns(n_patts, patts)
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83 print(f_patts)
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84 print(pl.seq)
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85 print(len(pl.seq))
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86
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87
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88 n_poss = punctuate_targets(f_patts, n_pl)
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89 print(n_poss)
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90
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91 print_seq(n_pl.seq)
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92
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93 synonims_tables = synonims_(table_name=args['codon_table'])
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94
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95 synonims_tables
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96
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97 plasmids = generalization(n_poss, n_pl, synonims_tables)
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98
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99 print(len(plasmids))
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100
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101 #plasmids
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102
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103 #if len(plasmids) > 5000000:
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104 #redo generalization without considering internal bases
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105 #in target sites that are not in CDS
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106 #this means considering only the outer bases of the target
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107 # plasmids = generalization(n_poss, n_pl, synonims_tables,
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108 # reduced = True)
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109
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110 #########################################################
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111 # Read plasmid and compute codon usage
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112 #########################################################
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113
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114 genome = annotated_genome(read_annotated_genome(
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115 data=args['input_genome'], type_=args['genome_format']))
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116
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117 out_genome = genome.codon_usage(args['codon_table'])
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118 print(out_genome.keys())
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119 print(out_genome["Table"])
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120
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121 print(out_genome["Table"].loc["GCA"]["Proportion"])
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122 print(type(out_genome["Table"].loc["GCA"]["Proportion"]))
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123
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124
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125 #########################################################
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126 # Evaluate the plasmid
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127 #########################################################
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128
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129 useful_plasmids = evaluate_plasmids(plasmids = plasmids,
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130 original_plasmid = n_pl,
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131 codon_usage_table = out_genome["Table"],
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132 n_patts = n_patts,
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133 f_patts = patts)
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134
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135 dat_plasmids = rank_plasmids(original_useful_plasmids = useful_plasmids)
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136
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137 def_pls = dat_plasmids.index[:int(args['n_plasmids'])]
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138
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139 for to_save in def_pls:
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140 #print(to_save)
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141 #print(useful_plasmids[to_save])
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142 with open(to_save+".fa", "w") as handle:
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143 handle.write(">"+to_save+"\n")
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144 handle.write(useful_plasmids[to_save]["sequence"])
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145
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146
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147
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148 if args['max_row'] != None:
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149 tmp_max_row = int(args['max_row'])
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150 else:
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151 tmp_max_row = 27
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152
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153 print_color_seq(original = n_pl,
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154 others = def_pls,
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155 annotation_information = useful_plasmids,
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156 tot = useful_plasmids,
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157 ind_range = None,
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158 patterns = n_poss,
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159 f_patterns = f_patts,
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160 patts = patts,
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161 max_row = tmp_max_row)
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162
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163
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164 print_to_pdf(original = n_pl,
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165 others = def_pls,
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166 annotation_information = useful_plasmids,
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167 tot = useful_plasmids,
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168 ind_range = None,
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169 patterns = n_poss,
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170 f_patterns = f_patts,
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171 patts = patts,
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172 max_row = tmp_max_row)
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