1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
|
#!/usr/bin/env python
"""clustal_run.py
Example code to show how to create a clustalw command line, run clustalw
and parse the results into an object that can be dealt with easily."""
# standard library
from __future__ import print_function
import sys
import subprocess
# biopython
from Bio.Alphabet import Gapped, IUPAC
from Bio.Align.Applications import ClustalwCommandline
from Bio import AlignIO
from Bio.Align import AlignInfo
from Bio.SubsMat import FreqTable
# create the command line to run clustalw
# this assumes you've got clustalw somewhere on your path, otherwise
# you need to pass the full path of the executable to this via cmd="..."
cline = ClustalwCommandline(infile='opuntia.fasta', outfile='test.aln')
# actually perform the alignment
return_code = subprocess.call(str(cline), shell=(sys.platform != "win32"))
assert return_code == 0, "Calling ClustalW failed"
# Parse the output
alignment = AlignIO.read("test.aln", "clustal",
alphabet=Gapped(IUPAC.unambiguous_dna))
print(alignment)
print('first description: %s' % alignment[0].description)
print('first sequence: %s' % alignment[0].seq)
# get the length of the alignment
print('length %i' % alignment.get_alignment_length())
print(alignment)
# print out interesting information about the alignment
summary_align = AlignInfo.SummaryInfo(alignment)
consensus = summary_align.dumb_consensus()
print('consensus %s' % consensus)
my_pssm = summary_align.pos_specific_score_matrix(consensus,
chars_to_ignore=['N'])
print(my_pssm)
expect_freq = {
'A': .3,
'G': .2,
'T': .3,
'C': .2}
freq_table_info = FreqTable.FreqTable(expect_freq, FreqTable.FREQ,
IUPAC.unambiguous_dna)
info_content = summary_align.information_content(5, 30,
chars_to_ignore=['N'],
e_freq_table=freq_table_info)
print("relative info content: %f" % info_content)
|
