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comparison codon_usage.py @ 0:5b61f1b564b3 draft

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author fabio
date Tue, 11 Dec 2018 12:27:52 -0500
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-1:000000000000 0:5b61f1b564b3
1 #!/home/gianmarco/galaxy-python/python
2
3 import Bio
4 from Bio import SeqIO
5 from Bio.Data import CodonTable
6 import re
7 import sys
8 import os
9 import pandas as pd
10
11 def read_input(data = "example.fna"):
12
13 seqs = ""
14 with open(data, "rU") as handle:
15 for record in SeqIO.parse(handle, "fasta"):
16 seqs = seqs + str(record.seq)
17
18 return seqs
19
20 def codon_usage(seqs, codonTable):
21
22 codon_usage = {}
23 tmp = [x for x in re.split(r'(\w{3})', seqs) if x != ""]
24
25 b_cod_table = CodonTable.unambiguous_dna_by_name[codonTable].forward_table
26
27
28 for cod in CodonTable.unambiguous_dna_by_name[codonTable].stop_codons:
29 b_cod_table[cod] = "_Stop"
30
31 for cod in CodonTable.unambiguous_dna_by_name[codonTable].start_codons:
32 b_cod_table[cod + " Start"] = b_cod_table[cod]
33 b_cod_table.pop(cod)
34
35 aas = set(b_cod_table.values())
36
37
38 for aa in aas:
39 codon_usage[aa] = {}
40 for codon in b_cod_table.keys():
41 if b_cod_table[codon] == aa:
42 codon_usage[aa][codon] = tmp.count(codon.split(" ")[0])
43
44
45 tups = {(outerKey, innerKey): values for outerKey, innerDict in codon_usage.iteritems() for innerKey, values in innerDict.iteritems()}
46
47 #aas_ = set(tups.keys())
48
49 #stops_ = {el for el in aas_ if el[0] == "Stop"}
50 #aas_ = list(aas_.difference(stops_))
51 #stops_ = list(stops_)
52 #aas_.sort()
53 #stops_.sort()
54
55 codon_usage_ = pd.DataFrame(pd.Series(tups), columns = ["Count"])
56 codon_usage_.index = codon_usage_.index.set_names(["AA", "Codon"])
57 #codon_usage_.index.reindex(pd.MultiIndex.from_tuples([aas_, stops_], names=('AA', 'Codon')), level=[0,1])
58
59
60 codon_usage_['Proportion'] = codon_usage_.groupby(level=0).transform(lambda x: (x / x.sum()).round(2))
61
62 return {"Dictionary": codon_usage, "Tuples": tups, "Table": codon_usage_}
63
64
65
66 if __name__ == '__main__':
67
68
69 seqs = read_input(data=sys.argv[1])
70 out = codon_usage(seqs,"Bacterial")
71
72
73 with open(sys.argv[2], "w") as outf:
74 out["Table"].to_csv(outf, sep="\t")
75 #sys.stdout.write(out['Table'])