def test_total_branch_length(self):
recombination_rate = 1e-8
Ne = 5000
sample_size = 5
length = 6e2
ts_full = msprime.simulate(sample_size=sample_size,
Ne=Ne,
length=length,
mutation_rate=1e-8,
recombination_rate=recombination_rate,
random_seed=20,
record_full_arg=True)
tsarg = treeSequence.TreeSeq(ts_full)
tsarg.ts_to_argnode()
argnode = tsarg.arg
true_total_branch_length =\
(ts_full.tables.nodes.time[5] * 600) + (ts_full.tables.nodes.time[5] * 600) + \
(ts_full.tables.nodes.time[6] * 600) + (ts_full.tables.nodes.time[6] * 600) + \
((ts_full.tables.nodes.time[7] - ts_full.tables.nodes.time[6]) * 600) + \
((ts_full.tables.nodes.time[9] - ts_full.tables.nodes.time[8]) * 554) + \
((ts_full.tables.nodes.time[9] - ts_full.tables.nodes.time[3]) * 600) + \
((ts_full.tables.nodes.time[10] - ts_full.tables.nodes.time[9]) * 600) + \
((ts_full.tables.nodes.time[12] - ts_full.tables.nodes.time[10]) * 448) + \
((ts_full.tables.nodes.time[12] - ts_full.tables.nodes.time[11]) * 152) + \
((ts_full.tables.nodes.time[13] - ts_full.tables.nodes.time[5]) * 600) + \
((ts_full.tables.nodes.time[13] - ts_full.tables.nodes.time[7]) * 46) + \
((ts_full.tables.nodes.time[14] - ts_full.tables.nodes.time[13]) * 600) + \
((ts_full.tables.nodes.time[14] - ts_full.tables.nodes.time[12]) * 600)
self.assertTrue(
math.isclose(true_total_branch_length,
argnode.total_branch_length()))
#------ also verify other methdods of arg
self.assertTrue(argnode.__contains__(14))
def test_dump_and_load(self):
recombination_rate = 1e-8
Ne = 5000
sample_size = 25
length = 6e2
ts_full = msprime.simulate(sample_size=sample_size,
Ne=Ne,
length=length,
mutation_rate=1e-8,
recombination_rate=recombination_rate,
random_seed=20,
record_full_arg=True)
tsarg = treeSequence.TreeSeq(ts_full)
tsarg.ts_to_argnode()
argnode = tsarg.arg
argnode.dump(path=os.getcwd(), file_name='pickle_out.arg')
loaded_arg = argbook.ARG().load(path=os.getcwd() + '/pickle_out.arg')
for key in loaded_arg.nodes:
self.assertEqual(argnode[key].index, loaded_arg[key].index)
self.assertEqual(sorted(argnode[key].snps),
sorted(loaded_arg[key].snps))
if loaded_arg[key].left_parent is not None:
self.assertEqual(argnode[key].left_parent.index,
loaded_arg[key].left_parent.index)
self.assertEqual(argnode[key].right_parent.index,
loaded_arg[key].right_parent.index)
self.assertEqual(argnode[key].first_segment.left,
loaded_arg[key].first_segment.left)
self.assertEqual(argnode[key].first_segment.right,
loaded_arg[key].first_segment.right)
self.assertEqual(sorted(argnode[key].first_segment.samples),
sorted(loaded_arg[key].first_segment.samples))
tail_argnode = argnode[key].get_tail()
tail_loaded_arg = loaded_arg[key].get_tail()
self.assertEqual(tail_argnode.left, tail_loaded_arg.left)
self.assertEqual(tail_argnode.right, tail_loaded_arg.right)
self.assertEqual(sorted(tail_argnode.samples),
sorted(tail_loaded_arg.samples))
else:
self.assertEqual(argnode[key].left_parent,
loaded_arg[key].left_parent)
self.assertEqual(argnode[key].right_parent,
loaded_arg[key].right_parent)
self.assertEqual(argnode[key].first_segment, None)
self.assertEqual(loaded_arg[key].first_segment, None)
if loaded_arg[key].left_child is not None:
self.assertEqual(argnode[key].left_child.index,
loaded_arg[key].left_child.index)
self.assertEqual(argnode[key].right_child.index,
loaded_arg[key].right_child.index)
else:
self.assertEqual(argnode[key].left_child,
loaded_arg[key].left_child)
self.assertEqual(argnode[key].right_child,
loaded_arg[key].right_child)
self.assertEqual(argnode[key].breakpoint,
loaded_arg[key].breakpoint)
def test_arg_allele_age(self):
recombination_rate = 1e-8
Ne = 5000
sample_size = 5
length = 6e4
ts_full = msprime.simulate(sample_size=sample_size,
Ne=Ne,
length=length,
mutation_rate=1e-8,
recombination_rate=recombination_rate,
random_seed=20,
record_full_arg=True)
tsarg = treeSequence.TreeSeq(ts_full)
tsarg.ts_to_argnode()
arg = tsarg.arg
allele_age = arg.allele_age()
def test_arg_breakpoints(self):
recombination_rate = 1e-8
Ne = 5000
sample_size = 5
length = 6e4
ts_full = msprime.simulate(sample_size=sample_size,
Ne=Ne,
length=length,
mutation_rate=1e-8,
recombination_rate=recombination_rate,
random_seed=20,
record_full_arg=True)
tsarg = treeSequence.TreeSeq(ts_full)
tsarg.ts_to_argnode()
arg = tsarg.arg
all_recomb_events = arg.breakpoints()
ancestral_recomb_events = arg.breakpoints(only_ancRec=True)
def test_arg_copy_and_equal(self):
recombination_rate = 1e-8
Ne = 5000
sample_size = 5
length = 6e2
ts_full = msprime.simulate(sample_size=sample_size,
Ne=Ne,
length=length,
mutation_rate=1e-8,
recombination_rate=recombination_rate,
random_seed=20,
record_full_arg=True)
tsarg = treeSequence.TreeSeq(ts_full)
tsarg.ts_to_argnode()
arg = tsarg.arg
arg_copy = arg.copy()
self.assertTrue(arg.equal(arg_copy), True)
self.assertFalse(arg == arg_copy, False)
def test_arg_coal_and_rec_nodes(self):
recombination_rate = 1e-8
Ne = 5000
sample_size = 5
length = 6e2
ts_full = msprime.simulate(sample_size=sample_size,
Ne=Ne,
length=length,
mutation_rate=1e-8,
recombination_rate=recombination_rate,
random_seed=20,
record_full_arg=True)
tsarg = treeSequence.TreeSeq(ts_full)
tsarg.ts_to_argnode()
argnode = tsarg.arg
self.assertEqual(set([key for key in argnode.rec.keys()]),
set([7, 8, 10, 11]))
self.assertEqual(set([key for key in argnode.coal.keys()]),
set([5, 6, 9, 13, 12, 14]))
self.assertEqual(argnode.coal.__len__(), 6)
def test_arg_leaves(self):
recombination_rate = 1e-8
Ne = 5000
sample_size = 5
length = 6e2
ts_full = msprime.simulate(sample_size=sample_size,
Ne=Ne,
length=length,
mutation_rate=1e-8,
recombination_rate=recombination_rate,
random_seed=20,
record_full_arg=True)
tsarg = treeSequence.TreeSeq(ts_full)
tsarg.ts_to_argnode()
arg = tsarg.arg
manual_leaves = [i for i in range(sample_size)]
leaves = list(arg.leaves(arg.__getitem__(arg.roots.max_key())))
get_leaves = []
for node in leaves:
get_leaves.append(node.index)
self.assertTrue(sorted(get_leaves) == sorted(manual_leaves), True)
def test_verify_mutation_is_on_the_lowest_possible_node(self):
recombination_rate = 1e-8
Ne = 5000
sample_size = 5
length = 6e5
ts_full = msprime.simulate(sample_size=sample_size,
Ne=Ne,
length=length,
mutation_rate=1e-8,
recombination_rate=recombination_rate,
random_seed=20,
record_full_arg=True)
tsarg = treeSequence.TreeSeq(ts_full)
tsarg.ts_to_argnode()
argnode = tsarg.arg
def verify_mutation_node(node, data):
'''
verify node is the lowest possible position
the mutation can sit on.
'''
for x in node.snps:
# bth children have x
# left_child is not right_child
# for the segment containing x on node, samples == data[x]
if node.left_child is not None:
assert node.left_child.index is not node.right_child.index
assert node.left_child.contains(
x) and node.right_child.contains(x)
node_samples = node.x_segment(x).samples
# assert node samples contain all the derived for snp x.
assert sorted(node_samples) == sorted(data[x])
data = treeSequence.get_arg_genotype(ts_full)
# print(data)
for node in argnode.nodes.values():
verify_mutation_node(node, data)
def test_tree_node_age_and_also_upward_path(self):
#-------- ts_full from msprime:
recombination_rate = 1e-8
Ne = 5000
sample_size = 5
length = 6e2
ts_full = msprime.simulate(sample_size=sample_size,
Ne=Ne,
length=length,
mutation_rate=1e-8,
recombination_rate=recombination_rate,
random_seed=20,
record_full_arg=True)
# print(ts_full.tables.edges)
# print(ts_full.tables.nodes.time)
tsarg = treeSequence.TreeSeq(ts_full)
tsarg.ts_to_argnode()
argnode = tsarg.arg
#-------------- the age of node 2 at position 10 ---- easy
self.assertEqual(argnode[2].tree_node_age(10),
ts_full.tables.nodes[6].time)
# now node 6 undergo recombination, then for x=10, it should give us time[13] -time[6]
self.assertEqual(
argnode[6].tree_node_age(10),
ts_full.tables.nodes[13].time - ts_full.tables.nodes[6].time)
#there is a back rec, which is great for this test x= 10 in node 9 age=time[14] - time[9]
self.assertEqual(
argnode[9].tree_node_age(10),
ts_full.tables.nodes[14].time - ts_full.tables.nodes[9].time)
# edges values
self.assertEqual(
argnode[9].tree_node_age(0),
ts_full.tables.nodes[14].time - ts_full.tables.nodes[9].time)
self.assertEqual(
argnode[9].tree_node_age(447),
ts_full.tables.nodes[14].time - ts_full.tables.nodes[9].time)
def test_log_prior(self):
recombination_rate = 1e-8
Ne = 5000
sample_size = 5
length = 6e2
ts_full = msprime.simulate(sample_size=sample_size,
Ne=Ne,
length=length,
mutation_rate=1e-8,
recombination_rate=recombination_rate,
random_seed=20,
record_full_arg=True)
tsarg = treeSequence.TreeSeq(ts_full)
tsarg.ts_to_argnode()
argnode = tsarg.arg
r = 0.1
k = 5 # number_of_lineages
num_link = 5 * (length - 1)
rate = (k * (k - 1) / (2 * 2 * Ne)) + (num_link * r)
#ca node =5
true_log_prior = 0
true_log_prior -= rate * (ts_full.tables.nodes.time[5] - 0) + math.log(
2 * Ne)
num_link -= 599
k = 4
# ca, node =6
rate = (k * (k - 1) / (2 * 2 * Ne)) + (num_link * r)
true_log_prior -= rate * (ts_full.tables.nodes.time[6] - ts_full.tables.nodes.time[5])+\
math.log(2*Ne)
num_link -= 599
k = 3
#rec nodes 7, 8
rate = (k * (k - 1) / (2 * 2 * Ne)) + (num_link * r)
gap = 1
true_log_prior -= rate * (ts_full.tables.nodes.time[7] -
ts_full.tables.nodes.time[6])
true_log_prior += math.log(r)
num_link -= 1
k = 4
# CA , node = 9
rate = (k * (k - 1) / (2 * 2 * Ne)) + (num_link * r)
true_log_prior -= rate * (ts_full.tables.nodes.time[9] - ts_full.tables.nodes.time[8]) +\
math.log(2*Ne)
num_link -= 553
k = 3
#Rec , nodes = 10, 11
rate = (k * (k - 1) / (2 * 2 * Ne)) + (num_link * r)
gap = 1
true_log_prior -= rate * (ts_full.tables.nodes.time[10] -
ts_full.tables.nodes.time[9])
true_log_prior += math.log(r)
num_link -= 1
k = 4
# CA, node= 12
rate = (k * (k - 1) / (2 * 2 * Ne)) + (num_link * r)
true_log_prior -= rate * (ts_full.tables.nodes.time[12] - ts_full.tables.nodes.time[10]) +\
math.log(2*Ne)
num_link += 1
k = 3
# CA , node = 13
rate = (k * (k - 1) / (2 * 2 * Ne)) + (num_link * r)
true_log_prior -= rate * (ts_full.tables.nodes.time[13] - ts_full.tables.nodes.time[12])+\
math.log(2*Ne)
num_link -= 45
k = 2
# CA, node 14
rate = (k * (k - 1) / (2 * 2 * Ne)) + (num_link * r)
true_log_prior -= rate * (ts_full.tables.nodes.time[14] - ts_full.tables.nodes.time[13])+\
math.log(2*Ne)
num_link -= (599 + 599)
k = 1
#----- compare
self.assertTrue(
math.isclose(true_log_prior,
argnode.log_prior(sample_size, length, r, Ne)))
def test_log_likelihood(self):
recombination_rate = 1e-8
Ne = 5000
sample_size = 5
length = 6e2
ts_full = msprime.simulate(sample_size=sample_size,
Ne=Ne,
length=length,
mutation_rate=1e-8,
recombination_rate=recombination_rate,
random_seed=20,
record_full_arg=True)
tsarg = treeSequence.TreeSeq(ts_full)
tsarg.ts_to_argnode()
argnode = tsarg.arg
data = treeSequence.get_arg_genotype(ts_full)
# put some mutations on some nodes
argnode[6].snps.__setitem__(101, 101)
argnode[6].snps.__setitem__(10, 10)
argnode[3].snps.__setitem__(20, 20)
argnode[9].snps.__setitem__(448, 448)
a = bintrees.AVLTree()
a.update({2: 2, 4: 4})
data[10] = a
a = bintrees.AVLTree()
a.update({2: 2, 4: 4})
data[101] = a
a = bintrees.AVLTree()
a.update({3: 3})
data[20] = a
a = bintrees.AVLTree()
a.update({2: 2, 4: 4, 3: 3})
data[448] = a
#print
nodes_with_mutation = []
for node in argnode.nodes.values():
if node.snps:
nodes_with_mutation.append(node)
# print("node", node.index, node.snps)
total_material = (ts_full.tables.nodes.time[5] * 600) + (ts_full.tables.nodes.time[5] * 600) + \
(ts_full.tables.nodes.time[6] * 600) + (ts_full.tables.nodes.time[6] * 600) + \
((ts_full.tables.nodes.time[7] - ts_full.tables.nodes.time[6]) * 600) + \
((ts_full.tables.nodes.time[9] - ts_full.tables.nodes.time[8]) * 554) + \
((ts_full.tables.nodes.time[9] - ts_full.tables.nodes.time[3]) * 600) + \
((ts_full.tables.nodes.time[10] - ts_full.tables.nodes.time[9]) * 600) + \
((ts_full.tables.nodes.time[12] - ts_full.tables.nodes.time[10]) * 448) + \
((ts_full.tables.nodes.time[12] - ts_full.tables.nodes.time[11]) * 152) + \
((ts_full.tables.nodes.time[13] - ts_full.tables.nodes.time[5]) * 600) + \
((ts_full.tables.nodes.time[13] - ts_full.tables.nodes.time[7]) * 46) + \
((ts_full.tables.nodes.time[14] - ts_full.tables.nodes.time[13]) * 600) + \
((ts_full.tables.nodes.time[14] - ts_full.tables.nodes.time[12]) * 600)
number_of_mutations = 6
m = 6 # number of snps
mu = 0.1
true_log_likelihood = (
number_of_mutations * math.log(total_material * mu) -
total_material * mu)
true_log_likelihood += math.log(
(ts_full.tables.nodes.time[14] - ts_full.tables.nodes.time[3]) /
total_material) #x=20 , node=3
true_log_likelihood += math.log(
(ts_full.tables.nodes.time[14] - ts_full.tables.nodes.time[5]) /
total_material) #x=111 , node=5
true_log_likelihood += math.log(
(ts_full.tables.nodes.time[14] - ts_full.tables.nodes.time[5]) /
total_material) #x=558 , node=5
true_log_likelihood += math.log(
(ts_full.tables.nodes.time[13] - ts_full.tables.nodes.time[6]) /
total_material) #x=10 , node=6
true_log_likelihood += math.log(
(ts_full.tables.nodes.time[9] - ts_full.tables.nodes.time[6]) /
total_material) #x=101 , node=6
true_log_likelihood += math.log(
(ts_full.tables.nodes.time[14] - ts_full.tables.nodes.time[9]) /
total_material) #x=448 , node=9
#----- log likelihood function
self.assertTrue(
math.isclose(true_log_likelihood, argnode.log_likelihood(mu,
data)))
def test_ts_to_argnode(self):
#-------- ts_full from msprime:
recombination_rate = 1e-8
Ne = 5000
sample_size = 5
length = 6e2
ts_full = msprime.simulate(sample_size=sample_size,
Ne=Ne,
length=length,
mutation_rate=1e-8,
recombination_rate=recombination_rate,
random_seed=20,
record_full_arg=True)
tsarg = treeSequence.TreeSeq(ts_full)
tsarg.ts_to_argnode()
argnode = tsarg.arg
##----- ts.edges dict
edges_dict = collections.defaultdict(list)
child_edges_dict = collections.defaultdict(list)
for edge in ts_full.tables.edges:
edges_dict[edge.parent].append(edge)
child_edges_dict[edge.child].append(edge)
# number of nodes
self.assertEqual(
len(edges_dict) + ts_full.sample_size, argnode.__len__())
while edges_dict:
parent = next(iter(edges_dict))
if ts_full.tables.nodes[parent].flags == msprime.NODE_IS_RE_EVENT:
child = edges_dict[parent][0].child
parent2 = parent + 1
#time
self.assertEqual(ts_full.tables.nodes[parent].time,
argnode[parent].time)
self.assertEqual(ts_full.tables.nodes[parent2].time,
argnode[parent2].time)
# find breakpoint
if edges_dict[parent][-1].right == edges_dict[parent2][0].left:
l_break = math.ceil(edges_dict[parent][-1].right)
r_break = None
else:
r_break = math.ceil(edges_dict[parent2][0].left)
l_break = math.ceil(edges_dict[parent][-1].right)
#breakpoints
self.assertEqual(argnode[child].breakpoint, l_break)
#assert left
self.assertEqual(argnode[parent].first_segment.left,
math.ceil(edges_dict[parent][0].left))
self.assertEqual(argnode[parent].get_tail().right,
math.ceil(edges_dict[parent][-1].right))
#parent2
self.assertEqual(argnode[parent2].first_segment.left,
math.ceil(edges_dict[parent2][0].left))
self.assertEqual(argnode[parent2].get_tail().right,
math.ceil(edges_dict[parent2][-1].right))
#child
self.assertEqual(argnode[child].first_segment.left,
math.ceil(edges_dict[parent][0].left))
self.assertEqual(argnode[child].get_tail().right,
math.ceil(edges_dict[parent2][-1].right))
# parent or child
self.assertEqual(argnode[child].left_parent.index, parent)
self.assertEqual(argnode[child].right_parent.index, parent2)
self.assertEqual(argnode[parent].left_child.index,
argnode[parent2].left_child.index)
self.assertEqual(argnode[parent].right_child.index,
argnode[parent2].right_child.index)
del edges_dict[parent]
del edges_dict[parent2]
else: # CA
child0 = edges_dict[parent][0].child
child1 = edges_dict[parent][-1].child
assert child0 != child1
#time
self.assertEqual(ts_full.tables.nodes[parent].time,
argnode[parent].time)
#child0
self.assertEqual(argnode[child0].first_segment.left,
math.ceil(child_edges_dict[child0][0].left))
self.assertEqual(argnode[child0].get_tail().right,
math.ceil(child_edges_dict[child0][-1].right))
#child1
self.assertEqual(argnode[child1].first_segment.left,
math.ceil(child_edges_dict[child1][0].left))
self.assertEqual(argnode[child1].get_tail().right,
math.ceil(child_edges_dict[child1][-1].right))
# left_parent
self.assertEqual(argnode[child0].left_parent.index, parent)
self.assertEqual(argnode[child0].right_parent.index, parent)
self.assertEqual(argnode[child1].left_parent.index, parent)
self.assertEqual(argnode[child1].right_parent.index, parent)
#sibling
self.assertEqual(argnode[child0].sibling().index, child1)
self.assertEqual(argnode[child1].sibling().index, child0)
#-----
self.assertEqual(argnode[parent].left_child.index, child0)
self.assertEqual(argnode[parent].right_child.index, child1)
del edges_dict[parent]
