def get_sequences(self, locations, width=200):
# need to ensure that most locations on the forward
# and reverse strands are mappable
seqs = [utils.makestr(self.genome[loc[0]][int(loc[1])-width/2:int(loc[1])+width/2]) if loc[3]=='+' \
else utils.reverse_complement(utils.makestr(self.genome[loc[0]][int(loc[2])-width/2+1:int(loc[2])+width/2+1])) \
for loc in locations]
return seqs
def get_sequences(self, locations, width=200):
# need to ensure that most locations on the forward
# and reverse strands are mappable
seqs = [utils.makestr(self.genome[loc[0]][int(loc[1])-width/2:int(loc[1])+width/2]) if loc[3]=='+' \
else utils.reverse_complement(utils.makestr(self.genome[loc[0]][int(loc[2])-width/2+1:int(loc[2])+width/2+1])) \
for loc in locations]
return seqs
def getnull(self, locations, sample='', width=200):
left = self.k/2
right = self.k/2-1
if sample=='':
cutrate = self.cutrate
else:
cutrate = self.cutrate[sample]
strand = np.array([1 if loc[3]=='+' else 0 for loc in locations])
# removed a +1 for the - strand
sequences = np.array([utils.makestr(self.genome[loc[0]][int(loc[1])-width/2-left:int(loc[1])+width/2+right]) if loc[3]=='+' \
else utils.makestr(self.genome[loc[0]][int(loc[2])-width/2-left:int(loc[2])+width/2+right]) \
for loc in locations])
null = sequence_null.getnull(sequences, strand, cutrate, width, self.k)
null[null==0] = 1e-8
null = null/utils.insum(null,[1])
return null
def _make_cutrate(self, data):
cutrate = dict([(utils.makestr(key),[val[0]/val[2],val[1]/val[2]]) for key,val in data.iteritems()])
fwdtotal = np.sum([val[0] for val in data.itervalues()])
revtotal = np.sum([val[1] for val in data.itervalues()])
total = np.sum([val[2] for val in data.itervalues()])
cutrate['mean'] = [fwdtotal/total, revtotal/total]
return cutrate
def getnull(self, locations, sample='', width=200):
left = self.k / 2
right = self.k / 2 - 1
if sample == '':
cutrate = self.cutrate
else:
cutrate = self.cutrate[sample]
strand = np.array([1 if loc[3] == '+' else 0 for loc in locations])
# removed a +1 for the - strand
sequences = np.array([utils.makestr(self.genome[loc[0]][int(loc[1])-width/2-left:int(loc[1])+width/2+right]) if loc[3]=='+' \
else utils.makestr(self.genome[loc[0]][int(loc[2])-width/2-left:int(loc[2])+width/2+right]) \
for loc in locations])
null = sequence_null.getnull(sequences, strand, cutrate, width, self.k)
null[null == 0] = 1e-8
null = null / utils.insum(null, [1])
return null
def _make_cutrate(self, data):
cutrate = dict([(utils.makestr(key),
[val[0] / val[2], val[1] / val[2]])
for key, val in data.iteritems()])
fwdtotal = np.sum([val[0] for val in data.itervalues()])
revtotal = np.sum([val[1] for val in data.itervalues()])
total = np.sum([val[2] for val in data.itervalues()])
cutrate['mean'] = [fwdtotal / total, revtotal / total]
return cutrate
