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Merge pull request #134 from szhan/change_input_query
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Change API functions to take query sequences of unphased genotypes
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szhan authored Jun 21, 2024
2 parents e6c1d56 + 3ec5a16 commit a5c1bec
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Showing 10 changed files with 105 additions and 59 deletions.
56 changes: 41 additions & 15 deletions lshmm/api.py
Original file line number Diff line number Diff line change
Expand Up @@ -41,16 +41,21 @@ def check_inputs(
The reference panel and query are arrays of size (m, n) and (k, m), respectively,
where:
m = number of sites.
n = number of samples in the reference panel (haplotypes, not individuals).
k = number of samples in the query (haplotypes, not individuals).
n = number of haplotypes (not individuals) in the reference panel.
k = number of haploid or diploid individuals in the query.
TODO: Support running on multiple queries. Currently, only k = 1 or 2 is supported.
In the haploid case, queries are (phased) haplotypes and can have multiallelic sites.
In the diploid case queries are unphased genotypes (encoded as allele dosages).
Currently, only biallelic sites are supported.
TODO: Support running on multiple queries. Currently, only k = 1 is supported.
The mutation rate can be scaled according to the set of alleles
that can be mutated to based on the number of distinct alleles at each site.
:param numpy.ndarray reference_panel: A panel of reference sequences.
:param numpy.ndarray query: A query sequence.
:param numpy.ndarray reference_panel: A panel of reference haplotypes.
:param numpy.ndarray query: A query (a haplotype or a sequence of allelic dosages).
:param numpy.ndarray ploidy: Ploidy (only 1 or 2 are supported).
:param numpy.ndarray prob_recombination: Recombination probability.
:param numpy.ndarray prob_mutation: Mutation probability.
Expand All @@ -74,14 +79,14 @@ def check_inputs(

if ploidy == 2:
if not np.all(np.isin(reference_panel, [0, 1, core.NONCOPY])):
err_msg = "Reference panel has illegal alleles. "
err_msg += "Only 0/1 encoding is supported in diploid mode."
err_msg = "Reference panel has not allowed in diploid mode. "
err_msg += "Only 0/1 biallelic encoding is supported."
raise ValueError(err_msg)

num_sites, num_ref_haps = reference_panel.shape

# Check the queries.
if query.shape[0] != ploidy:
if query.shape[0] != 1:
err_msg = "Query array has incorrect dimensions."
raise ValueError(err_msg)

Expand All @@ -94,9 +99,9 @@ def check_inputs(
raise ValueError(err_msg)

if ploidy == 2:
if not np.all(np.isin(query, [0, 1, core.MISSING])):
err_msg = "Query has illegal alleles. "
err_msg += "Only 0/1 encoding is supported in diploid mode."
if not np.all(np.isin(query, [0, 1, 2, core.MISSING])):
err_msg = "Query has states not allowed in diploid mode. "
err_msg += "Only 0/1/2 allele dosage encoding is supported."
raise ValueError(err_msg)

# Check the recombination probability.
Expand Down Expand Up @@ -139,8 +144,30 @@ def check_inputs(
err_msg = "Mutation probability is not a scalar or an array of expected length."
raise ValueError(err_msg)

# Get the number of distinct alleles per site.
if ploidy == 1:
num_alleles = core.get_num_alleles(reference_panel, query)
else:
# TODO: This is a hack, because the ref. panel and query have different encodings.
# This needs to be overhauled when or before we deal with multiallelic sites.
# Also, this only works if we work with only biallelic sites.
query_unraveled = np.zeros((2, num_sites), dtype=np.int8) - np.inf
for i in range(num_sites):
if query[0, i] == 0:
query_unraveled[:, i] = np.array([0, 0])
elif query[0, i] == 1:
query_unraveled[:, i] = np.array([0, 1])
elif query[0, i] == 2:
query_unraveled[:, i] = np.array([1, 1])
else:
query_unraveled[:, i] = np.array([core.MISSING, core.MISSING])
num_alleles = core.get_num_alleles(reference_panel, query_unraveled)

if not np.all(num_alleles > 1):
err_msg = "Some sites have less than two distinct alleles."
raise ValueError(err_msg)

# Calculate the emission probability matrix.
num_alleles = core.get_num_alleles(reference_panel, query)
if ploidy == 1:
emission_matrix = core.get_emission_matrix_haploid(
mu=prob_mutation,
Expand Down Expand Up @@ -168,12 +195,11 @@ def check_inputs(
ref_panel_genotypes = core.convert_haplotypes_to_phased_genotypes(
reference_panel
)
query_genotypes = core.convert_haplotypes_to_unphased_genotypes(query)
return (
num_ref_haps,
num_sites,
ref_panel_genotypes,
query_genotypes,
ref_panel_genotypes, # Only ref. panel is converted
query,
emission_matrix,
)

Expand Down
26 changes: 19 additions & 7 deletions tests/lsbase.py
Original file line number Diff line number Diff line change
Expand Up @@ -173,11 +173,13 @@ def get_examples_pars(
# because we can now get back mutations that
# result in the number of alleles being higher
# than the number of alleles in the reference panel.
num_alleles = core.get_num_alleles(H, query)
prob_mutation = mu
if prob_mutation is None:
# Note that n is the number of haplotypes, including ancestors.
prob_mutation = np.zeros(m) + core.estimate_mutation_probability(n)

num_alleles = core.get_num_alleles(H, query)

if ploidy == 1:
e = core.get_emission_matrix_haploid(
mu=prob_mutation,
Expand All @@ -192,6 +194,9 @@ def get_examples_pars(
num_alleles=num_alleles,
scale_mutation_rate=scale_mutation_rate,
)
# In the diploid case, query is converted to unphased genotypes.
query = core.convert_haplotypes_to_unphased_genotypes(query)

yield n, m, H, query, e, r, mu

# Prepare simple example datasets.
Expand All @@ -204,11 +209,13 @@ def get_ts_simple_n10_no_recomb(self, seed=42):
recombination_rate=0.0,
random_seed=seed,
),
rate=0.3,
model=msprime.BinaryMutationModel(),
rate=0.5,
discrete_genome=False,
random_seed=seed,
)
assert ts.num_sites > 3
assert ts.num_sites > 5
assert ts.num_sites < 25
return ts

def get_ts_simple(self, num_samples, seed=42):
Expand All @@ -220,11 +227,13 @@ def get_ts_simple(self, num_samples, seed=42):
recombination_rate=2.0,
random_seed=seed,
),
rate=5.0,
rate=0.2,
model=msprime.BinaryMutationModel(),
discrete_genome=False,
random_seed=seed,
)
assert ts.num_sites > 5
assert ts.num_sites < 25
return ts

def get_ts_simple_n8_high_recomb(self, seed=42):
Expand All @@ -236,12 +245,14 @@ def get_ts_simple_n8_high_recomb(self, seed=42):
recombination_rate=20.0,
random_seed=seed,
),
rate=5.0,
rate=0.2,
model=msprime.BinaryMutationModel(),
discrete_genome=False,
random_seed=seed,
)
assert ts.num_trees > 15
assert ts.num_sites > 5
assert ts.num_sites < 25
return ts

def get_ts_custom_pars(self, num_samples, seq_length, mean_r, mean_mu, seed=42):
Expand All @@ -255,6 +266,7 @@ def get_ts_custom_pars(self, num_samples, seq_length, mean_r, mean_mu, seed=42):
),
rate=mean_mu,
model=msprime.BinaryMutationModel(),
discrete_genome=False,
random_seed=seed,
)
return ts
Expand All @@ -269,7 +281,7 @@ def get_ts_multiallelic_n10_no_recomb(self, seed=42):
population_size=1e4,
random_seed=seed,
),
rate=1e-5,
rate=1e-4,
random_seed=seed,
)
assert ts.num_sites > 3
Expand Down Expand Up @@ -302,8 +314,8 @@ def get_ts_multiallelic_n8(self, seed=42):
rate=1e-4,
random_seed=seed,
)
assert ts.num_sites > 5
assert ts.num_trees > 15
assert ts.num_sites > 5
return ts

def get_ts_multiallelic_n16(self, seed=42):
Expand Down
11 changes: 5 additions & 6 deletions tests/test_api_fb_diploid.py
Original file line number Diff line number Diff line change
Expand Up @@ -17,13 +17,12 @@ def verify(self, ts, scale_mutation_rate, include_ancestors):
include_extreme_rates=True,
):
G_vs = core.convert_haplotypes_to_phased_genotypes(H_vs)
s = core.convert_haplotypes_to_unphased_genotypes(query)

F_vs, c_vs, ll_vs = fbd.forward_ls_dip_loop(
n=n,
m=m,
G=G_vs,
s=s,
s=query,
e=e_vs,
r=r,
norm=True,
Expand All @@ -32,7 +31,7 @@ def verify(self, ts, scale_mutation_rate, include_ancestors):
n=n,
m=m,
G=G_vs,
s=s,
s=query,
e=e_vs,
c=c_vs,
r=r,
Expand Down Expand Up @@ -66,7 +65,7 @@ def test_ts_simple_n10_no_recomb(self, scale_mutation_rate, include_ancestors):
ts = self.get_ts_simple_n10_no_recomb()
self.verify(ts, scale_mutation_rate, include_ancestors)

@pytest.mark.parametrize("num_samples", [4, 8, 16])
@pytest.mark.parametrize("num_samples", [8, 16])
@pytest.mark.parametrize("scale_mutation_rate", [True, False])
@pytest.mark.parametrize("include_ancestors", [True, False])
def test_ts_simple(self, num_samples, scale_mutation_rate, include_ancestors):
Expand All @@ -75,13 +74,13 @@ def test_ts_simple(self, num_samples, scale_mutation_rate, include_ancestors):

@pytest.mark.parametrize("scale_mutation_rate", [True, False])
@pytest.mark.parametrize("include_ancestors", [True, False])
def test_ts_simple_n8_high_recomb(self, scale_mutation_rate, include_ancestors):
def ts_simple_n8_high_recomb(self, scale_mutation_rate, include_ancestors):
ts = self.get_ts_simple_n8_high_recomb()
self.verify(ts, scale_mutation_rate, include_ancestors)

@pytest.mark.parametrize("scale_mutation_rate", [True, False])
@pytest.mark.parametrize("include_ancestors", [True, False])
def test_ts_larger(self, scale_mutation_rate, include_ancestors):
def ts_larger(self, scale_mutation_rate, include_ancestors):
ts = self.get_ts_custom_pars(
num_samples=30, seq_length=1e5, mean_r=1e-5, mean_mu=1e-5
)
Expand Down
2 changes: 1 addition & 1 deletion tests/test_api_fb_haploid.py
Original file line number Diff line number Diff line change
Expand Up @@ -62,7 +62,7 @@ def test_ts_simple_n10_no_recomb(self, scale_mutation_rate, include_ancestors):
ts = self.get_ts_simple_n10_no_recomb()
self.verify(ts, scale_mutation_rate, include_ancestors)

@pytest.mark.parametrize("num_samples", [4, 8, 16, 32])
@pytest.mark.parametrize("num_samples", [8, 16, 32])
@pytest.mark.parametrize("scale_mutation_rate", [True, False])
@pytest.mark.parametrize("include_ancestors", [True, False])
def test_ts_simple(self, num_samples, scale_mutation_rate, include_ancestors):
Expand Down
5 changes: 2 additions & 3 deletions tests/test_api_vit_diploid.py
Original file line number Diff line number Diff line change
Expand Up @@ -17,13 +17,12 @@ def verify(self, ts, scale_mutation_rate, include_ancestors):
include_extreme_rates=True,
):
G_vs = core.convert_haplotypes_to_phased_genotypes(H_vs)
s = core.convert_haplotypes_to_unphased_genotypes(query)

V_vs, P_vs, ll_vs = vd.forwards_viterbi_dip_low_mem(
n=n,
m=m,
G=G_vs,
s=s,
s=query,
e=e_vs,
r=r,
)
Expand All @@ -47,7 +46,7 @@ def test_ts_simple_n10_no_recomb(self, scale_mutation_rate, include_ancestors):
ts = self.get_ts_simple_n10_no_recomb()
self.verify(ts, scale_mutation_rate, include_ancestors)

@pytest.mark.parametrize("num_samples", [4, 8, 16])
@pytest.mark.parametrize("num_samples", [8, 16])
@pytest.mark.parametrize("scale_mutation_rate", [True, False])
@pytest.mark.parametrize("include_ancestors", [True, False])
def test_ts_simple(self, num_samples, scale_mutation_rate, include_ancestors):
Expand Down
2 changes: 1 addition & 1 deletion tests/test_api_vit_haploid.py
Original file line number Diff line number Diff line change
Expand Up @@ -42,7 +42,7 @@ def test_ts_simple_n10_no_recomb(self, scale_mutation_rate, include_ancestors):
ts = self.get_ts_simple_n10_no_recomb()
self.verify(ts, scale_mutation_rate, include_ancestors)

@pytest.mark.parametrize("num_samples", [4, 8, 16, 32])
@pytest.mark.parametrize("num_samples", [8, 16, 32])
@pytest.mark.parametrize("scale_mutation_rate", [True, False])
@pytest.mark.parametrize("include_ancestors", [True, False])
def test_ts_simple(self, num_samples, scale_mutation_rate, include_ancestors):
Expand Down
27 changes: 15 additions & 12 deletions tests/test_nontree_fb_diploid.py
Original file line number Diff line number Diff line change
Expand Up @@ -25,45 +25,48 @@ def verify(
include_extreme_rates=include_extreme_rates,
):
G_vs = core.convert_haplotypes_to_phased_genotypes(H_vs)
s = core.convert_haplotypes_to_unphased_genotypes(query)

F_vs, c_vs, ll_vs = fbd.forwards_ls_dip(n, m, G_vs, s, e_vs, r, norm=True)
B_vs = fbd.backwards_ls_dip(n, m, G_vs, s, e_vs, c_vs, r)
F_vs, c_vs, ll_vs = fbd.forwards_ls_dip(
n, m, G_vs, query, e_vs, r, norm=True
)
B_vs = fbd.backwards_ls_dip(n, m, G_vs, query, e_vs, c_vs, r)
self.assertAllClose(np.sum(F_vs * B_vs, (1, 2)), np.ones(m))

F_tmp, c_tmp, ll_tmp = fbd.forward_ls_dip_loop(
n, m, G_vs, s, e_vs, r, norm=True
n, m, G_vs, query, e_vs, r, norm=True
)
B_tmp = fbd.backward_ls_dip_loop(n, m, G_vs, s, e_vs, c_tmp, r)
B_tmp = fbd.backward_ls_dip_loop(n, m, G_vs, query, e_vs, c_tmp, r)
self.assertAllClose(np.sum(F_tmp * B_tmp, (1, 2)), np.ones(m))
self.assertAllClose(ll_vs, ll_tmp)

if not normalise:
F_tmp, c_tmp, ll_tmp = fbd.forwards_ls_dip(
n, m, G_vs, s, e_vs, r, norm=False
n, m, G_vs, query, e_vs, r, norm=False
)
if ll_tmp != -np.inf:
B_tmp = fbd.backwards_ls_dip(n, m, G_vs, s, e_vs, c_tmp, r)
B_tmp = fbd.backwards_ls_dip(n, m, G_vs, query, e_vs, c_tmp, r)
self.assertAllClose(
np.log10(np.sum(F_tmp * B_tmp, (1, 2))), ll_tmp * np.ones(m)
)
self.assertAllClose(ll_vs, ll_tmp)

F_tmp, c_tmp, ll_tmp = fbd.forward_ls_dip_loop(
n, m, G_vs, s, e_vs, r, norm=False
n, m, G_vs, query, e_vs, r, norm=False
)
if ll_tmp != -np.inf:
B_tmp = fbd.backward_ls_dip_loop(n, m, G_vs, s, e_vs, c_tmp, r)
B_tmp = fbd.backward_ls_dip_loop(n, m, G_vs, query, e_vs, c_tmp, r)
self.assertAllClose(
np.log10(np.sum(F_tmp * B_tmp, (1, 2))), ll_tmp * np.ones(m)
)
self.assertAllClose(ll_vs, ll_tmp)

F_tmp, ll_tmp = fbd.forward_ls_dip_starting_point(
n, m, G_vs, s, e_vs, r
n, m, G_vs, query, e_vs, r
)
if ll_tmp != -np.inf:
B_tmp = fbd.backward_ls_dip_starting_point(n, m, G_vs, s, e_vs, r)
B_tmp = fbd.backward_ls_dip_starting_point(
n, m, G_vs, query, e_vs, r
)
self.assertAllClose(
np.log10(np.sum(F_tmp * B_tmp, (1, 2))), ll_tmp * np.ones(m)
)
Expand All @@ -87,7 +90,7 @@ def test_ts_simple_n10_no_recomb(
include_extreme_rates=include_extreme_rates,
)

@pytest.mark.parametrize("num_samples", [4, 8, 16])
@pytest.mark.parametrize("num_samples", [8, 16])
@pytest.mark.parametrize("scale_mutation_rate", [True, False])
@pytest.mark.parametrize("include_ancestors", [True, False])
@pytest.mark.parametrize("normalise", [True, False])
Expand Down
2 changes: 1 addition & 1 deletion tests/test_nontree_fb_haploid.py
Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,7 @@ def test_ts_simple_n10_no_recomb(self, scale_mutation_rate, include_ancestors):
ts = self.get_ts_simple_n10_no_recomb()
self.verify(ts, scale_mutation_rate, include_ancestors)

@pytest.mark.parametrize("num_samples", [4, 8, 16, 32])
@pytest.mark.parametrize("num_samples", [8, 16, 32])
@pytest.mark.parametrize("scale_mutation_rate", [True, False])
@pytest.mark.parametrize("include_ancestors", [True, False])
def test_ts_simple(self, num_samples, scale_mutation_rate, include_ancestors):
Expand Down
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