def chunks_containing_region(self):
breakpoints = BedTool(paths.reference + self.params.breakpointsfile)
blocks = SnpPartition(self.refpanel, breakpoints, remove_mhc=True)
self.A = SnpSubset(self.refpanel,
GenomicSubset(self.params.region).bedtool)
return [
int(i / self.chunk_size(blocks.ranges()))
for i in blocks.indices_containing(self.A.irs)
]
def mult_by_R_ldblocks(V, refpanel, refpanel_indices=None):
breakpoints = BedTool(paths.reference + 'pickrell_breakpoints.hg19.eur.bed')
blocks = SnpPartition(refpanel, breakpoints, remove_mhc=True)
if refpanel_indices is not None:
Vwithzeros = np.zeros((refpanel.M, V.shape[1]))
Vwithzeros[refpanel_indices] = V
else:
Vwithzeros = V
result = np.zeros(Vwithzeros.shape)
for r in blocks.ranges():
print('\tXTXV', r[0], r[1], 'of', refpanel.M)
X = refpanel.get_standardized_genotypes(r)
result[r[0]:r[1],:] = X.T.dot(X.dot(Vwithzeros[r[0]:r[1],:]))
if refpanel_indices is not None:
return result[refpanel_indices] / refpanel.N
else:
return result / refpanel.N
def mult_by_R_ldblocks(V, refpanel, refpanel_indices=None):
breakpoints = BedTool(paths.reference +
'pickrell_breakpoints.hg19.eur.bed')
blocks = SnpPartition(refpanel, breakpoints, remove_mhc=True)
if refpanel_indices is not None:
Vwithzeros = np.zeros((refpanel.M, V.shape[1]))
Vwithzeros[refpanel_indices] = V
else:
Vwithzeros = V
result = np.zeros(Vwithzeros.shape)
for r in blocks.ranges():
print('\tXTXV', r[0], r[1], 'of', refpanel.M)
X = refpanel.get_standardized_genotypes(r)
result[r[0]:r[1], :] = X.T.dot(X.dot(Vwithzeros[r[0]:r[1], :]))
if refpanel_indices is not None:
return result[refpanel_indices] / refpanel.N
else:
return result / refpanel.N
def compute_covariance(self):
breakpoints = BedTool(paths.reference + self.params.breakpointsfile)
blocks = SnpPartition(self.refpanel, breakpoints, remove_mhc=True)
myranges = self.ranges_in_chunk(blocks.ranges())
print('working on', len(myranges), 'ld blocks')
return BlockDiag.ld_matrix_blocks(self.refpanel, myranges)
def compute_covariance(self):
breakpoints = BedTool(paths.reference + self.params.breakpointsfile)
blocks = SnpPartition(self.refpanel, breakpoints, remove_mhc=True)
myranges = self.ranges_in_chunk(blocks.ranges())
print('working on', len(myranges), 'ld blocks')
return BlockDiag.ld_matrix_blocks(self.refpanel, myranges)
def chunks_containing_region(self):
breakpoints = BedTool(paths.reference + self.params.breakpointsfile)
blocks = SnpPartition(self.refpanel, breakpoints, remove_mhc=True)
self.A = SnpSubset(self.refpanel, GenomicSubset(self.params.region).bedtool)
return [int(i / self.chunk_size(blocks.ranges()))
for i in blocks.indices_containing(self.A.irs)]