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1 #!/home/gianmarco/galaxy-python/python
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2
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3 import Bio
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4 from Bio import SeqIO
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5 from Bio.Data import CodonTable
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6 import re
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7 import sys
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8 import os
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9 import pandas as pd
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10
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11 def read_input(data = "example.fna"):
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12
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13 seqs = ""
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14 with open(data, "rU") as handle:
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15 for record in SeqIO.parse(handle, "fasta"):
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16 seqs = seqs + str(record.seq)
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17
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18 return seqs
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19
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20 def codon_usage(seqs, codonTable):
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21
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22 codon_usage = {}
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23 tmp = [x for x in re.split(r'(\w{3})', seqs) if x != ""]
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24
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25 b_cod_table = CodonTable.unambiguous_dna_by_name[codonTable].forward_table
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26
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27
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28 for cod in CodonTable.unambiguous_dna_by_name[codonTable].stop_codons:
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29 b_cod_table[cod] = "_Stop"
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30
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31 for cod in CodonTable.unambiguous_dna_by_name[codonTable].start_codons:
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32 b_cod_table[cod + " Start"] = b_cod_table[cod]
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33 b_cod_table.pop(cod)
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34
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35 aas = set(b_cod_table.values())
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36
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37
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38 for aa in aas:
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39 codon_usage[aa] = {}
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40 for codon in b_cod_table.keys():
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41 if b_cod_table[codon] == aa:
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42 codon_usage[aa][codon] = tmp.count(codon.split(" ")[0])
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43
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44
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45 tups = {(outerKey, innerKey): values for outerKey, innerDict in codon_usage.iteritems() for innerKey, values in innerDict.iteritems()}
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46
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47 #aas_ = set(tups.keys())
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48
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49 #stops_ = {el for el in aas_ if el[0] == "Stop"}
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50 #aas_ = list(aas_.difference(stops_))
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51 #stops_ = list(stops_)
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52 #aas_.sort()
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53 #stops_.sort()
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54
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55 codon_usage_ = pd.DataFrame(pd.Series(tups), columns = ["Count"])
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56 codon_usage_.index = codon_usage_.index.set_names(["AA", "Codon"])
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57 #codon_usage_.index.reindex(pd.MultiIndex.from_tuples([aas_, stops_], names=('AA', 'Codon')), level=[0,1])
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58
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59
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60 codon_usage_['Proportion'] = codon_usage_.groupby(level=0).transform(lambda x: (x / x.sum()).round(2))
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61
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62 return {"Dictionary": codon_usage, "Tuples": tups, "Table": codon_usage_}
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63
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64
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65
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66 if __name__ == '__main__':
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67
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68
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69 seqs = read_input(data=sys.argv[1])
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70 out = codon_usage(seqs,"Bacterial")
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71
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72
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73 with open(sys.argv[2], "w") as outf:
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74 out["Table"].to_csv(outf, sep="\t")
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75 #sys.stdout.write(out['Table']) |
