def _biasVplotHelper(arg):
"""function to make vplot for a particular set of bed regions
"""
(chunks, params) = arg
mat = np.zeros((params.upper - params.lower, 2 * params.flank + 1))
for chunk in chunks:
try:
chunk.center()
biastrack = InsertionBiasTrack(
chunk.chrom,
chunk.start - params.flank - 1 - (params.upper / 2),
chunk.end + params.flank + params.upper / 2 + 1)
if params.bg is not None:
biastrack.read_track(params.bg, empty=0)
else:
biastrack.computeBias(params.fasta, params.chrs, params.pwm)
biasmat = BiasMat2D(chunk.chrom, chunk.start - params.flank - 1,
chunk.end + params.flank, params.lower,
params.upper)
biasmat.makeBiasMat(biastrack)
biasmat.normByInsertDist(params.fragmentsizes)
add = biasmat.get(start=chunk.start - params.flank,
end=chunk.end + params.flank,
flip=(chunk.strand == "-"))
if params.scale:
mat += add / np.sum(add)
else:
mat += add
except Exception as e:
print('Caught exception when processing:\n' + chunk.asBed() + "\n")
traceback.print_exc()
print()
raise e
return mat
def makeBiasMat(self):
self.bias_mat = BiasMat2D(self.chrom, self.start - self.params.flank,
self.end + self.params.flank, 0, self.params.upper)
if self.params.fasta is not None:
bias_track = InsertionBiasTrack(self.chrom, self.start - self.params.window - self.params.upper/2,
self.end + self.params.window + self.params.upper/2 + 1, log = True)
bias_track.computeBias(self.params.fasta, self.params.chrs, self.params.pwm)
self.bias_mat.makeBiasMat(bias_track)
def getBias(self):
"""get bias"""
self.bias = InsertionBiasTrack(self.chrom,
self.start,
self.end,
log=True)
if self.params.fasta is not None:
self.bias.computeBias(self.params.fasta, self.params.chrs,
self.params.pwm)
def setUp(self):
"""setup Test_BiasMat class with construction of a biasmat"""
bed_list = ChunkList.read('example/example.bed')
self.chunk = bed_list[0]
self.biastrack = InsertionBiasTrack(self.chunk.chrom, self.chunk.start,
self.chunk.end)
self.biastrack.read_track('example/example.Scores.bedgraph.gz')
self.biasmat = BiasMat2D(self.chunk.chrom, self.chunk.start + 100,
self.chunk.end - 100, 100, 200)
self.biasmat.makeBiasMat(self.biastrack)
def setUp(self):
""" set up class for testing variance calculation for background signal
"""
bed_list = ChunkList.read('example/example.bed')
chunk = bed_list[0]
vmat = V.VMat.open('example/example.VMat')
biastrack = InsertionBiasTrack(chunk.chrom, chunk.start, chunk.end)
biastrack.read_track('example/example.Scores.bedgraph.gz')
biasmat = BiasMat2D(chunk.chrom,chunk.start+200,chunk.end-200,100,250)
biasmat.makeBiasMat(biastrack)
self.signaldist = Nuc.SignalDistribution(chunk.start+300,vmat,biasmat,35)
def _biasHelper(arg):
"""Helper function to multiprocess computation of bias tracks"""
(chunk, params) = arg
try:
bias = InsertionBiasTrack(chunk.chrom, chunk.start, chunk.end)
bias.computeBias(params.fasta, params.chrs, params.pwm)
except Exception as e:
print(('Caught exception when processing:\n' + chunk.asBed() + "\n"))
traceback.print_exc()
print()
raise e
return bias
def makeBiasMat(self):
self.bias_mat = BiasMat2D(self.chrom, self.start - self.params.window,
self.end + self.params.window, 0, self.params.upper)
bias_track = InsertionBiasTrack(self.chrom, self.start - self.params.window - self.params.upper/2,
self.end + self.params.window + self.params.upper/2 + 1, log = True)
if self.params.fasta is not None:
bias_track.computeBias(self.params.fasta, self.params.chrs, self.params.pwm)
self.bias_mat.makeBiasMat(bias_track)
self.bias_mat_prenorm = BiasMat2D(self.chrom, self.start - self.params.window,
self.end + self.params.window, 0, self.params.upper)
self.bias_mat_prenorm.mat = copy(self.bias_mat.mat)
self.bias_mat.normByInsertDist(self.params.fragmentsizes)
