def re_annotate(self, from_edges=False, window=FULL_EXTEND):
"""create a position specific scoring matrix for the surrounding regions,
see how far you can go while keeping conservation, using a maximum
likelihood method. Can either annotate from feature (by default) or
from edges"""
if len(self.lst) < 2:
return
# unzip
if from_edges:
[befores, afters] = zip(*[e.around_IS(window) for e in self.lst])
else:
[befores, afters] = zip(*[e.around_gene(window) for e in self.lst])
# make them the same length
minlength_before = min([len(b) for b in befores])
minlength_after = min([len(a) for a in afters])
befores = [b[:minlength_before] for b in befores]
afters = [a[:minlength_after] for a in afters]
verbose = False
individual = True
before_lens = EdgeFinder.find_left_edges([str(s) for s in befores],
individual, verbose)
after_lens = EdgeFinder.find_left_edges([str(s) for s in afters],
individual, verbose)
for e, before_len, after_len in zip(self.lst, before_lens, after_lens):
if from_edges:
start = e.start
end = e.end
else:
start = e.feature.location._start.position
end = e.feature.location._end.position
if e.direction == 1:
newstart = start - before_len
newend = end + after_len
else:
newstart = start - after_len
newend = end + before_len
e.change(newstart=newstart, newend=newend)
