def _obs_exp_lieberman(pSubmatrix, pLengthChromosome, pChromosomeCount):
obs_exp_matrix_ = obs_exp_matrix_lieberman(pSubmatrix, pLengthChromosome,
pChromosomeCount)
obs_exp_matrix_ = convertNansToZeros(csr_matrix(obs_exp_matrix_))
obs_exp_matrix_ = convertInfsToZeros(csr_matrix(obs_exp_matrix_)).todense()
return obs_exp_matrix_
def _obs_exp_lieberman(pSubmatrix, pLengthChromosome, pChromosomeCount):
obs_exp_matrix_ = obs_exp_matrix_lieberman(pSubmatrix, pLengthChromosome, pChromosomeCount)
obs_exp_matrix_ = convertNansToZeros(csr_matrix(obs_exp_matrix_))
obs_exp_matrix_ = convertInfsToZeros(csr_matrix(obs_exp_matrix_))
# if len(obs_exp_matrix_.data) == 0:
# return np.array()
return obs_exp_matrix_ # .todense()
def main(args=None):
args = parse_arguments().parse_args(args)
if int(args.numberOfEigenvectors) != len(args.outputFileName):
log.error("Number of output file names and number of eigenvectors"
" does not match. Please"
"provide the name of each file.\nFiles: {}\nNumber of "
"eigenvectors: {}".format(args.outputFileName,
args.numberOfEigenvectors))
exit(1)
ma = hm.hiCMatrix(args.matrix)
ma.maskBins(ma.nan_bins)
if args.ignoreMaskedBins:
# ma.maskBins(ma.nan_bins)
new_intervals = enlarge_bins(ma.cut_intervals)
ma.setCutIntervals(new_intervals)
if args.chromosomes:
ma.keepOnlyTheseChr(args.chromosomes)
vecs_list = []
chrom_list = []
start_list = []
end_list = []
# PCA is computed per chromosome
length_chromosome = 0
chromosome_count = len(ma.getChrNames())
if args.pearsonMatrix:
transf_matrix_pearson = lil_matrix(ma.matrix.shape)
if args.obsexpMatrix:
transf_matrix_obsexp = lil_matrix(ma.matrix.shape)
for chrname in ma.getChrNames():
chr_range = ma.getChrBinRange(chrname)
length_chromosome += chr_range[1] - chr_range[0]
if args.extraTrack and (args.extraTrack.endswith('.bw') or args.extraTrack.endswith('.bigwig')):
bwTrack = pyBigWig.open(args.extraTrack, 'r')
for chrname in ma.getChrNames():
chr_range = ma.getChrBinRange(chrname)
submatrix = ma.matrix[chr_range[0]:chr_range[1],
chr_range[0]:chr_range[1]]
if args.method == 'lieberman':
obs_exp_matrix_ = obs_exp_matrix_lieberman(submatrix,
length_chromosome,
chromosome_count)
else:
obs_exp_matrix_ = obs_exp_matrix_non_zero(submatrix, args.ligation_factor)
obs_exp_matrix_ = csr_matrix(obs_exp_matrix_).todense()
if args.obsexpMatrix:
transf_matrix_obsexp[chr_range[0]:chr_range[1], chr_range[0]:chr_range[1]] = lil_matrix(obs_exp_matrix_)
pearson_correlation_matrix = np.corrcoef(obs_exp_matrix_)
pearson_correlation_matrix = convertNansToZeros(csr_matrix(pearson_correlation_matrix)).todense()
pearson_correlation_matrix = convertInfsToZeros(csr_matrix(pearson_correlation_matrix)).todense()
if args.pearsonMatrix:
transf_matrix_pearson[chr_range[0]:chr_range[1], chr_range[0]:chr_range[1]] = lil_matrix(pearson_correlation_matrix)
corrmatrix = np.cov(pearson_correlation_matrix)
corrmatrix = pearson_correlation_matrix
corrmatrix = convertNansToZeros(csr_matrix(corrmatrix)).todense()
corrmatrix = convertInfsToZeros(csr_matrix(corrmatrix)).todense()
evals, eigs = linalg.eig(corrmatrix)
k = args.numberOfEigenvectors
chrom, start, end, _ = zip(*ma.cut_intervals[chr_range[0]:chr_range[1]])
chrom_list += chrom
start_list += start
end_list += end
if args.extraTrack and (args.extraTrack.endswith('.bw') or args.extraTrack.endswith('.bigwig')):
assert(len(end) == len(start))
correlateEigenvectorWithHistonMarkTrack(eigs[:, :k].transpose(),
bwTrack, chrname, start,
end, args.extraTrack,
args.histonMarkType)
vecs_list += eigs[:, :k].tolist()
if args.pearsonMatrix:
file_type = 'cool'
if args.pearsonMatrix.endswith('.h5'):
file_type = 'h5'
matrixFileHandlerOutput = MatrixFileHandler(pFileType=file_type)
matrixFileHandlerOutput.set_matrix_variables(transf_matrix_pearson.tocsr(),
ma.cut_intervals,
ma.nan_bins,
ma.correction_factors,
ma.distance_counts)
matrixFileHandlerOutput.save(args.pearsonMatrix, pSymmetric=True,
pApplyCorrection=False)
if args.obsexpMatrix:
file_type = 'cool'
if args.obsexpMatrix.endswith('.h5'):
file_type = 'h5'
matrixFileHandlerOutput = MatrixFileHandler(pFileType=file_type)
matrixFileHandlerOutput.set_matrix_variables(transf_matrix_obsexp.tocsr(),
ma.cut_intervals,
ma.nan_bins,
ma.correction_factors,
ma.distance_counts)
matrixFileHandlerOutput.save(args.obsexpMatrix, pSymmetric=True,
pApplyCorrection=False)
if args.extraTrack and not args.extraTrack.endswith('.bw') and not args.extraTrack.endswith('.bigwig'):
vecs_list = correlateEigenvectorWithGeneTrack(ma, vecs_list, args.extraTrack)
if args.format == 'bedgraph':
for idx, outfile in enumerate(args.outputFileName):
assert(len(vecs_list) == len(chrom_list))
with open(outfile, 'w') as fh:
for i, value in enumerate(vecs_list):
if len(value) == args.numberOfEigenvectors:
if isinstance(value[idx], np.complex):
value[idx] = value[idx].real
fh.write("{}\t{}\t{}\t{:.12f}\n".format(toString(chrom_list[i]), start_list[i], end_list[i], value[idx]))
elif args.format == 'bigwig':
if not pyBigWig.numpy == 1:
log.error("ERROR: Your version of pyBigWig is not supporting "
"numpy: {}".format(pyBigWig.__file__))
exit(1)
old_chrom = chrom_list[0]
header = []
for i, _chrom in enumerate(chrom_list):
if old_chrom != _chrom:
header.append((toString(old_chrom), end_list[i - 1]))
old_chrom = _chrom
header.append((toString(chrom_list[-1]), end_list[-1]))
for idx, outfile in enumerate(args.outputFileName):
log.debug("bigwig: len(vecs_list) {}".format(len(vecs_list)))
log.debug("bigwig: len(chrom_list) {}".format(len(chrom_list)))
assert(len(vecs_list) == len(chrom_list))
_chrom_list = []
_start_list = []
_end_list = []
values = []
bw = pyBigWig.open(outfile, 'w')
# set big wig header
bw.addHeader(header)
# create entry lists
for i, value in enumerate(vecs_list):
# it can happen that some 'value' is having less dimensions than it should
if len(value) == args.numberOfEigenvectors:
if isinstance(value[idx], np.complex):
value[idx] = value[idx].real
values.append(value[idx])
_chrom_list.append(toString(chrom_list[i]))
_start_list.append(start_list[i])
_end_list.append(end_list[i])
# write entries
bw.addEntries(_chrom_list, _start_list, ends=_end_list,
values=values)
bw.close()
else:
log.error("Output format not known: {}".format(args.format))
exit(1)
def open_and_store_matrix(pMatrixName, pMatricesList, pIndex, pXDimension,
pChromosomes, pNorm, pExtraTrack, pHistonMarkType,
pBinarization, pQueue):
compartments_matrix = None
for i, matrix in enumerate(pMatricesList):
ma = hm.hiCMatrix(pMatrixName + '::' + matrix)
# WARNING
# DO NOT APPLY BIN MASKING, WILL LEAD TO DIFFERENT SIZES OF THE CHROMOSOMES
# THIS IS CAUSING A FAIL OF THE COMPUTATION
# ma.maskBins(ma.nan_bins)
k = 1
if pChromosomes:
ma.keepOnlyTheseChr(pChromosomes)
vecs_list = []
chrom_list = []
start_list = []
end_list = []
# PCA is computed per chromosome
length_chromosome = 0
chromosome_count = len(ma.getChrNames())
for chrname in ma.getChrNames():
chr_range = ma.getChrBinRange(chrname)
length_chromosome += chr_range[1] - chr_range[0]
if pExtraTrack and (pExtraTrack.endswith('.bw')
or pExtraTrack.endswith('.bigwig')):
bwTrack = pyBigWig.open(pExtraTrack, 'r')
for chrname in ma.getChrNames():
chr_range = ma.getChrBinRange(chrname)
submatrix = ma.matrix[chr_range[0]:chr_range[1],
chr_range[0]:chr_range[1]]
if pNorm:
obs_exp_matrix_ = obs_exp_matrix_norm(submatrix)
else:
obs_exp_matrix_ = obs_exp_matrix_lieberman(
submatrix, length_chromosome, chromosome_count)
obs_exp_matrix_ = convertNansToZeros(
csr_matrix(obs_exp_matrix_)).todense()
obs_exp_matrix_ = convertInfsToZeros(
csr_matrix(obs_exp_matrix_)).todense()
pearson_correlation_matrix = np.corrcoef(obs_exp_matrix_)
pearson_correlation_matrix = convertNansToZeros(
csr_matrix(pearson_correlation_matrix)).todense()
pearson_correlation_matrix = convertInfsToZeros(
csr_matrix(pearson_correlation_matrix)).todense()
corrmatrix = np.cov(pearson_correlation_matrix)
corrmatrix = convertNansToZeros(csr_matrix(corrmatrix)).todense()
corrmatrix = convertInfsToZeros(csr_matrix(corrmatrix)).todense()
evals, eigs = linalg.eig(corrmatrix)
chrom, start, end, _ = zip(
*ma.cut_intervals[chr_range[0]:chr_range[1]])
chrom_list += chrom
start_list += start
end_list += end
if pExtraTrack and (pExtraTrack.endswith('.bw')
or pExtraTrack.endswith('.bigwig')):
assert (len(end) == len(start))
correlateEigenvectorWithHistonMarkTrack(
eigs[:, :k].transpose(), bwTrack, chrname, start, end,
pExtraTrack, pHistonMarkType)
vecs_list += eigs[:, :k].tolist()
if compartments_matrix is None:
compartments_matrix = np.zeros(
[pXDimension, len(np.array(vecs_list).flatten())],
dtype=np.float)
eigenvector = np.real(np.array(vecs_list).flatten())
mask = np.isnan(eigenvector)
if len(mask) > 0:
eigenvector[mask] = 0
mask = np.isinf(eigenvector)
if len(mask) > 0:
eigenvector[mask] = 0
if pBinarization:
mask = eigenvector <= 0
eigenvector[mask] = -1
mask = eigenvector > 0
eigenvector[mask] = 1
compartments_matrix[pIndex + i, :] = eigenvector
pQueue.put(compartments_matrix)
return
