/usr/lib/python2.7/dist-packages/cogent/align/align.py is in python-cogent 1.9-9.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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 68 69 70 71 72 73 74 75 76 77 | #!/usr/bin/env python
import numpy
Float = numpy.core.numerictypes.sctype2char(float)
from cogent.align import pairwise, indel_model, pycompare
from cogent.evolve.likelihood_tree import makeLikelihoodTreeLeaf
__author__ = "Peter Maxwell"
__copyright__ = "Copyright 2007-2016, The Cogent Project"
__credits__ = ["Peter Maxwell", "Gavin Huttley"]
__license__ = "GPL"
__version__ = "1.9"
__maintainer__ = "Peter Maxwell"
__email__ = "pm67nz@gmail.com"
__status__ = "Production"
def dotplot(seq1, seq2, window, threshold, min_gap_length=0, band=None, **kw):
#warnings.warn("cogent.align.align.dotplot moved to cogent.align.compare.dotplot",
# DeprecationWarning)
return pycompare.dotplot(seq1, seq2, window, threshold, min_gap_length,
band, **kw)
def make_dna_scoring_dict(match, transition, transversion):
DNA = {}
for a in 'ATCG':
ar = a in 'AG'
for b in 'ATCG':
br = b in 'AG'
if a == b:
score = match
elif ar == br:
score = transition
else:
score = transversion
DNA[a,b] = score
return DNA
def _align_pairwise(s1, s2, mprobs, psub, TM, local, return_alignment=True, return_score=False, **kw):
"""Generic alignment with any substitution model and indel model"""
[p1, p2] = [makeLikelihoodTreeLeaf(seq) for seq in [s1, s2]]
[p1, p2] = [pairwise.AlignableSeq(leaf) for leaf in [p1, p2]]
pair = pairwise.Pair(p1, p2)
EP = pair.makeSimpleEmissionProbs(mprobs, [psub])
hmm = EP.makePairHMM(TM)
vpath = hmm.getViterbiPath(local=local, **kw)
score = vpath.getScore()
if return_alignment:
alignment = vpath.getAlignment()
if return_score:
return (alignment, score)
else:
return alignment
else:
return score
def classic_align_pairwise(s1, s2, Sd, d, e, local, return_score=False, **kw):
"""Alignment specified by gap costs and a score matrix"""
TM = indel_model.ClassicGapScores(d, e)
a1 = s1.MolType.Alphabet
a2 = s2.MolType.Alphabet
S = numpy.zeros([len(a1), len(a2)], Float)
for (i,m1) in enumerate(a1):
for (j,m2) in enumerate(a2):
S[i, j] = Sd[m1, m2]
psub = numpy.exp(S)
mprobs = numpy.ones(len(psub), Float) / len(psub)
return _align_pairwise(s1, s2, mprobs, psub, TM, local, return_score=return_score, **kw)
# these can't do codon sequences
# they could be replaced with something more sophisticated, like the HMM
# may not give same answers as algorithm
def local_pairwise(s1, s2, S, d, e, return_score=False):
return classic_align_pairwise(s1, s2, S, d, e, True, return_score=return_score)
def global_pairwise(s1, s2, S, d, e, return_score=False):
return classic_align_pairwise(s1, s2, S, d, e, False, return_score=return_score)
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