def preprocess_hic(
clr: cooler.Cooler,
min_contacts: Optional[int] = None,
region: Optional[str] = None,
) -> sp.csr_matrix:
"""
Given an input cooler object, returns the preprocessed Hi-C matrix.
Preprocessing involves (in that order): subsetting region, subsampling
contacts, normalisation, detrending (obs / exp). Balancing weights must
be pre-computer in the referenced cool file. Region must be in UCSC format.
"""
# Load raw matrix and subset region if requested
mat = clr.matrix(sparse=True, balance=False)
bins = clr.bins()
if region is None:
mat = mat[:]
bins = bins[:]
else:
mat = mat.fetch(region)
bins = bins.fetch(region)
try:
biases = bins["weight"].values
except KeyError as err:
sys.stderr.write("Error: Input cooler must be balanced.\n")
raise err
# get to same coverage if requested and matrix is not empty
if mat.sum() and (min_contacts is not None):
mat = cup.subsample_contacts(mat, min_contacts).tocoo()
valid = cup.get_detectable_bins(mat, n_mads=5)
# balance region with weights precomputed on the whole matrix
mat.data = mat.data * biases[mat.row] * biases[mat.col]
# Detrend for P(s)
mat = cup.detrend(mat.tocsr(), smooth=False, detectable_bins=valid[0])
# Replace NaNs by 0s
mat.data = np.nan_to_num(mat.data)
mat.eliminate_zeros()
return mat
def test_subsample_contacts_count(n_contacts):
"""Test sampling raw contact counts"""
sampled = preproc.subsample_contacts(mat.tocoo(), n_contacts)
assert np.isclose(sampled.data.sum(), n_contacts, rtol=0.1)
def test_subsample_contacts_prop(prop):
"""Test sampling proportions of contacts"""
sampled = preproc.subsample_contacts(mat.tocoo(),
int(prop * mat.data.sum()))
assert np.isclose(sampled.data.sum(), mat.data.sum() * prop, rtol=0.1)
def test_subsample_contacts_exceed(self, n_contacts):
"""Oversampling should result in value errors"""
with self.assertRaises(ValueError):
preproc.subsample_contacts(mat, n_contacts)