def setUp(self):
self.linear_graph = Graph({i: Block(5)
for i in range(1, 4)},
{i: [i + 1]
for i in range(1, 3)})
self.scores = DensePileup.from_intervals(
self.linear_graph, [Interval(0, 5, [i]) for i in range(1, 4)])
self.graph = Graph({i: Block(5)
for i in range(1, 4)}, {
1: [3],
2: [3],
3: [4]
})
def test_find_max_path_through_subgraph_multiple_paths(self):
graph = Graph({
1: Block(10),
2: Block(10),
3: Block(10),
4: Block(10)
}, {
1: [2, 3],
2: [4],
3: [4]
})
peak = ConnectedAreas(graph, {
2: [0, 10],
3: [0, 10],
1: [5, 10],
4: [0, 3]
})
binary_peak = BinaryContinousAreas.from_old_areas(peak)
qvalues = DensePileup.from_intervals(
graph,
[
Interval(7, 2, [1, 3, 4]) # Giving higher qvalue
# through this path
])
print(qvalues)
scored_peak = ScoredPeak.from_peak_and_pileup(binary_peak, qvalues)
print(scored_peak)
max_path = scored_peak.get_max_path()
self.assertEqual(max_path, Interval(5, 3, [1, 3, 4]))
def simple_test():
graph = Graph({
1: Block(10),
2: Block(1),
3: Block(1),
4: Block(10)
}, {
1: [2, 3],
2: [4],
3: [4]
})
graph.convert_to_numpy_backend()
sequence_graph = SequenceGraph.create_empty_from_ob_graph(graph)
sequence_graph.set_sequence(1, "GGGTTTATAC")
sequence_graph.set_sequence(2, "A")
sequence_graph.set_sequence(3, "C")
sequence_graph.set_sequence(4, "GTACATTGTA")
linear_ref = Interval(0, 10, [1, 2, 3], graph)
linear_ref = linear_ref.to_numpy_indexed_interval()
critical_nodes = set([4])
finder = MinimizerFinder(graph,
sequence_graph,
critical_nodes,
linear_ref,
k=3,
w=3)
minimizers = finder.find_minimizers()
assert minimizers.has_minimizer(2, 0)
assert minimizers.has_minimizer(3, 0)
assert minimizers.has_minimizer(4, 4)
def test_create_from_nongraphpeakcollection(self):
graph = Graph({
1: Block(10),
2: Block(10),
3: Block(10)
}, {
1: [2],
2: [3]
})
graph.convert_to_numpy_backend()
linear_path = Interval(0, 10, [1, 2, 3], graph)
linear_path = linear_path.to_numpy_indexed_interval()
nongraph_peaks = NonGraphPeakCollection([
NonGraphPeak("chr1", 3, 10, 5),
NonGraphPeak("chr1", 13, 15, 7),
])
peaks = PeakCollection.create_from_nongraph_peak_collection(
graph, nongraph_peaks, linear_path, None)
self.assertEqual(peaks.intervals[0], Interval(3, 10, [1]))
self.assertEqual(peaks.intervals[1], Interval(3, 5, [2]))
peaks = PeakCollection.create_from_nongraph_peak_collection(
graph, nongraph_peaks, linear_path, LinearRegion("chr1", 3, 20))
self.assertEqual(peaks.intervals[0], Interval(0, 7, [1]))
self.assertEqual(peaks.intervals[1], Interval(0, 2, [2]))
def test_three_nodes_in(self):
graph = Graph({i: Block(5)
for i in range(1, 5)}, {
1: [4],
2: [4],
3: [4]
})
intervals = [
Interval(2, 5, [1]),
Interval(2, 5, [2]),
Interval(2, 5, [3]),
Interval(0, 3, [4])
]
pileup = DensePileup.from_intervals(graph, intervals)
subgraphs = SubgraphCollectionPartiallyOrderedGraph.create_from_pileup(
graph, pileup)
print(subgraphs)
correct1 = BinaryContinousAreas(graph)
correct1.add_start(-1, 3)
correct1.add_start(-2, 3)
correct1.add_start(-3, 3)
correct1.add_start(4, 3)
self.assertTrue(correct1 in subgraphs)
def test_find_max_path_on_start_and_end_node(self):
graph = Graph({
1: Block(10),
2: Block(10),
3: Block(10),
4: Block(10)
}, {
1: [2, 3],
2: [4],
3: [4]
})
peak = ConnectedAreas(graph, {
2: [0, 10],
4: [0, 10],
})
binary_peak = BinaryContinousAreas.from_old_areas(peak)
qvalues = DensePileup.from_intervals(graph,
[Interval(7, 2, [1, 2, 4])])
scored_peak = ScoredPeak.from_peak_and_pileup(binary_peak, qvalues)
max_path = scored_peak.get_max_path()
self.assertEqual(max_path, Interval(0, 10, [2, 4]))
def test_simple3(self):
graph = Graph({i: Block(5)
for i in range(1, 6)}, {
1: [3],
2: [3],
3: [4, 5]
})
scores = DensePileup.from_intervals(
graph, [Interval(0, 5, [i]) for i in range(1, 6)])
intervals = [
Interval(0, 5, [1]),
Interval(0, 5, [3]),
Interval(0, 5, [4]),
Interval(0, 3, [5])
]
pileup = DensePileup.from_intervals(graph, intervals)
subgraphs = SubgraphCollectionPartiallyOrderedGraph.create_from_pileup(
graph, pileup)
scored_peaks = (ScoredPeak.from_peak_and_pileup(peak, scores)
for peak in subgraphs)
max_paths = [peak.get_max_path() for peak in scored_peaks]
self.assertTrue(
Interval(0, 5, [1, 3, 4]) in max_paths
or Interval(0, 3, [1, 3, 5]) in max_paths)
def set_graph(self):
self.graph = Graph({
1: Block(5),
2: Block(5),
3: Block(5)
}, {
1: [2],
2: [3]
})
def setUp(self):
self.graph = Graph({i: Block(3)
for i in range(1, 7)},
{i: [i + 1]
for i in range(1, 6)})
self.peaks = PeakCollection([
Peak(3, 3, [1, 2, 3, 4], self.graph),
Peak(3, 3, [5, 6], self.graph)
])
def set_graph(self):
self.graph = Graph({
1: Block(5),
2: Block(5),
3: Block(5),
4: Block(5)
}, {
1: [2, 3],
2: [4],
3: [4]
})
def setUp(self):
self.graph = Graph({i: Block(10)
for i in range(1, 4)},
{i: [i + 1]
for i in range(1, 3)})
self.index = GraphIndex({
1: [(2, 10), (3, 20)],
2: [(3, 10)],
3: [],
-1: [],
-2: [(-1, 10)],
-3: [(-2, 10), (-1, 20)]
})
self.extender = GraphExtender(self.index)
def setUp(self):
self.complex_graph = Graph(
{i: Block(3) for i in range(1, 13)},
{
1: [2, 3],
2: [7, 8],
3: [4, 5],
4: [6],
5: [6],
6: [10],
7: [9],
8: [9],
9: [10],
10: [12]
})
self.complex_graph.convert_to_numpy_backend()
def test_find_max_path_through_subgraph_two_node_graph(self):
graph = Graph({1: Block(10), 2: Block(10)}, {1: [2]})
peak = ConnectedAreas(graph, {2: [0, 4], 1: [5, 10]})
binary_peak = BinaryContinousAreas.from_old_areas(peak)
qvalues = DensePileup.from_base_value(graph, 10)
print("q values")
print(qvalues)
print(qvalues.data._values)
scored_peak = ScoredPeak.from_peak_and_pileup(binary_peak, qvalues)
print(scored_peak)
max_path = scored_peak.get_max_path()
self.assertEqual(max_path, Interval(5, 4, [1, 2]))
def test_reverse():
graph = Graph({
1: Block(10),
2: Block(5),
3: Block(10),
4: Block(5)
}, {
1: [2, 3],
2: [4],
3: [4]
})
graph.convert_to_numpy_backend()
linear_path = NumpyIndexedInterval.from_interval(
Interval(0, 10, [1, 2, 4], graph))
alignments = [Interval(4, 5, [-3, -1], graph)]
projected = project_alignments(alignments, linear_path)
projected = list(projected)
assert projected[0] == (5, 16, "-")
def test_many_nodes():
nodes = {i: Block(1) for i in range(2, 10)}
nodes[1] = Block(10)
nodes[10] = Block(10)
graph = Graph(
nodes, {
1: [2, 3],
2: [4],
3: [4],
4: [5, 6],
5: [7],
6: [7],
7: [8, 9],
8: [10],
9: [10]
})
graph.convert_to_numpy_backend()
sequence_graph = SequenceGraph.create_empty_from_ob_graph(graph)
sequence_graph.set_sequence(1, "ACTGACTGAC")
sequence_graph.set_sequence(10, "ACTGACTGAC")
sequence_graph.set_sequence(2, "A")
sequence_graph.set_sequence(3, "C")
sequence_graph.set_sequence(4, "A")
sequence_graph.set_sequence(5, "G")
sequence_graph.set_sequence(6, "C")
sequence_graph.set_sequence(7, "T")
sequence_graph.set_sequence(8, "A")
sequence_graph.set_sequence(9, "A")
linear_ref = Interval(0, 10, [1, 2, 4, 6, 7, 8, 10], graph)
linear_ref = linear_ref.to_numpy_indexed_interval()
critical_nodes = {1, 4, 7, 10}
finder = MinimizerFinder(graph,
sequence_graph,
critical_nodes,
linear_ref,
k=3,
w=3)
minimizers = finder.find_minimizers()
print(len(minimizers.minimizers))
def test_simple():
graph = Graph({
1: Block(10),
2: Block(5),
3: Block(10),
4: Block(5)
}, {
1: [2, 3],
2: [4],
3: [4]
})
graph.convert_to_numpy_backend()
linear_path = NumpyIndexedInterval.from_interval(
Interval(0, 10, [1, 2, 4], graph))
alignments = [Interval(5, 5, [1, 3], graph), Interval(5, 5, [3, 4], graph)]
projected = project_alignments(alignments, linear_path)
projected = list(projected)
assert projected[0] == (5, 15, "+")
assert projected[1] == (15, 25, "+")
def setUp(self):
self.graph = Graph({i: Block(10)
for i in range(1, 5)}, {
1: [2, 3],
2: [4],
3: [4]
})
self.index = GraphIndex({
1: [(2, 10), (3, 10), (4, 20)],
2: [(4, 10)],
3: [(4, 10)],
4: [],
-1: [],
-2: [(-1, 10)],
-3: [(-1, 10)],
-4: [(-2, 10), (-3, 10), (-1, 20)]
})
self.extender = GraphExtender(self.index)
def setUp(self):
self.simple_graph = Graph({i: Block(3)
for i in range(1, 9)}, {
1: [2, 3],
2: [4],
3: [4],
4: [5],
5: [6, 7],
6: [8],
7: [8]
})
print(self.simple_graph.get_first_blocks())
print(self.simple_graph.reverse_adj_list)
self.simple_snarls = \
{
20: SimpleSnarl(1, 4, 20),
21: SimpleSnarl(5, 8, 21),
22: SimpleSnarl(4, 5, 22)
}
def test_find_max_path_through_subgraph_with_illegal_paths(self):
graph = Graph(
{
1: Block(10),
2: Block(10),
3: Block(10),
4: Block(10)
},
{
1: [2, 3],
2: [4],
-4: [-3] # Making 3=>4 not allowed path
})
peak = ConnectedAreas(graph, {
2: [0, 10],
3: [0, 10],
1: [5, 10],
4: [0, 8]
})
binary_peak = BinaryContinousAreas.from_old_areas(peak)
qvalues = DensePileup.from_intervals(
graph,
[
Interval(0, 10, [3]), # Higher value on 3 than 2
Interval(0, 10, [3]),
Interval(0, 10, [4]), # Highest value if ending on 4
Interval(0, 10, [4]),
Interval(0, 10, [1]), # Highest value if inncluding 1
Interval(0, 10, [1]), # Highest value if inncluding 1
Interval(0, 10, [1, 2, 4])
])
scored_peak = ScoredPeak.from_peak_and_pileup(binary_peak, qvalues)
max_path = scored_peak.get_max_path()
print(max_path)
self.assertEqual(max_path, Interval(5, 8, [1, 2, 4]))
def test_many_nodes():
nodes = {i: Block(1) for i in range(2, 10)}
nodes[1] = Block(10)
nodes[10] = Block(10)
graph = Graph(
nodes, {
1: [2, 3],
2: [4],
3: [4],
4: [5, 6],
5: [7],
6: [7],
7: [8, 9],
8: [10],
9: [10]
})
graph.convert_to_numpy_backend()
sequence_graph = SequenceGraph.create_empty_from_ob_graph(graph)
sequence_graph.set_sequence(1, "ACTGACTGAC")
sequence_graph.set_sequence(10, "ACTGACTGAC")
sequence_graph.set_sequence(2, "A")
sequence_graph.set_sequence(3, "C")
sequence_graph.set_sequence(4, "A")
sequence_graph.set_sequence(5, "G")
sequence_graph.set_sequence(6, "C")
sequence_graph.set_sequence(7, "T")
sequence_graph.set_sequence(8, "T")
sequence_graph.set_sequence(9, "A")
linear_ref_nodes = {1, 2, 4, 6, 7, 8, 10}
read_sequence = "ACTGACCAGTAACTGAC"
start_node = 1
start_offset = 4
aligner = LocalGraphAligner(graph, sequence_graph, read_sequence,
linear_ref_nodes, start_node, start_offset)
alignment, score = aligner.align()
assert alignment == [1, 3, 4, 5, 7, 9, 10]
def test_simple(self):
graph = Graph(
{i: Block(3) for i in range(1, 5)},
{
1: [2, 3],
2: [4],
3: [4]
}
)
graph.convert_to_numpy_backend()
intervals = IntervalCollection([
Interval(0, 3, [1, 3])
])
haplotyper = HaploTyper(graph, intervals)
haplotyper.build()
max_interval = haplotyper.get_maximum_interval_through_graph()
self.assertEqual(
max_interval,
Interval(0, 3, [1, 3, 4])
)
def _create_data(self):
node_offset = 1
for chrom_number, chromosome in enumerate(self.chromosomes):
graph = Graph(
{i + node_offset: Block(10)
for i in range(0, 3)},
{i + node_offset: [i + 1 + node_offset]
for i in range(0, 2)})
linear_map = LinearMap.from_graph(graph)
linear_map_file_name = "linear_map_%s.npz" % chromosome
linear_map.to_file(linear_map_file_name)
self.linear_maps.append(linear_map_file_name)
self.sequence_retrievers.append(
SequenceRetriever(
{i + node_offset: "A" * 10
for i in range(0, 3)}))
self._create_reads(chrom_number, chromosome, graph)
node_offset += 3
graph.convert_to_numpy_backend()
SequenceGraph.create_empty_from_ob_graph(graph).to_file(
chromosome + ".nobg.sequences")
graph.to_file(chromosome + ".nobg")
def test_convert_to_approx_linear_peaks(self):
graph = Graph({i: Block(3)
for i in range(1, 10)}, {
1: [2],
2: [3],
3: [4],
4: [5],
5: [6],
6: [7, 8],
7: [9],
9: [9]
})
graph.convert_to_numpy_backend()
linear_interval = Interval(0, 3, [2, 4, 8, 9], graph)
linear_interval = linear_interval.to_numpy_indexed_interval()
peaks = PeakCollection([Peak(2, 2, [2, 3, 4]), Peak(1, 1, [3, 4, 5])])
linear_peaks = peaks.to_approx_linear_peaks(linear_interval, "chr4")
linear_peaks = linear_peaks.peaks
print(linear_peaks)
self.assertEqual(linear_peaks[0], NonGraphPeak("chr4", 2, 5))
self.assertEqual(linear_peaks[1], NonGraphPeak("chr4", 3, 3))
import pytest
import unittest
import numpy as np
from offsetbasedgraph import GraphWithReversals as Graph,\
Block, DirectedInterval as Interval
if pytest.__version__ < "3.0.0":
pytest.skip()
graph = Graph({i: Block(10) for i in range(1, 4)}, {1: [2], 2: [3]})
@pytest.mark.skip("Legacy")
class TestDensePileup(unittest.TestCase):
def test_init(self):
DensePileup(graph)
def test_from_starts_and_ends(self):
starts = {1: [3, 5]}
ends = {1: [7, 9]}
pileup = DensePileup.from_starts_and_ends(graph, starts, ends)
indexes, values = pileup.data.get_sparse_indexes_and_values(1)
self.assertTrue(np.all(values == [0, 1, 2, 1, 0]))
self.assertTrue(np.all(indexes == [0, 3, 5, 7, 9, 10]))
starts = {1: [0, 3]}
ends = {1: [5, 10]}
pileup = DensePileup.from_starts_and_ends(graph, starts, ends)
indexes, values = pileup.data.get_sparse_indexes_and_values(1)
def test_hierarchical(self):
graph = Graph({i: Block(3)
for i in range(1, 13)}, {
11: [1],
1: [2, 3],
2: [7, 8],
3: [4, 5],
4: [6],
5: [6],
6: [10],
7: [9],
8: [9],
9: [10],
10: [12]
})
subsnarl1 = SimpleSnarl(3, 6, 21, parent=20)
subsnarl2 = SimpleSnarl(2, 9, 22, parent=20)
parent_snarl = SimpleSnarl(1, 10, 20, children=[subsnarl1, subsnarl2])
snarls = {20: parent_snarl, 21: subsnarl1, 22: subsnarl2}
builder = SnarlGraphBuilder(graph, snarls, id_counter=13)
snarlgraph = builder.build_snarl_graphs()
print("Snarlgraph")
print(snarlgraph)
correct_snarl_graph = SnarlGraph(
{
11:
Block(3),
12:
Block(3),
1:
Block(3),
10:
Block(3),
20:
SnarlGraph(
{
3:
Block(3),
21:
SnarlGraph({
4: Block(3),
5: Block(3)
}, {
3: [4, 5],
4: [6],
5: [6]
},
start_node=3,
end_node=6),
22:
SnarlGraph({
7: Block(3),
8: Block(3)
}, {
2: [7, 8],
7: [9],
8: [9]
},
start_node=2,
end_node=9),
2:
Block(3),
6:
Block(3),
9:
Block(3),
}, {
3: [21],
2: [22],
21: [6],
22: [9],
1: [2, 3],
6: [10],
9: [10]
},
start_node=1,
end_node=10)
},
{
11: [1],
1: [20],
20: [10],
10: [12],
13: [11], # Dummy
12: [14], # Dummy
},
start_node=13,
end_node=14)
print("Snarlgraph")
print(snarlgraph)
self.assertEqual(correct_snarl_graph, snarlgraph)
import pytest
# from graph_peak_caller.densepileup import DensePileupData, DensePileup
from offsetbasedgraph import GraphWithReversals as Graph, Block,\
DirectedInterval as Interval
import unittest
import numpy as np
# from graph_peak_caller.dagholecleaner import DagHoleCleaner
if pytest.__version__ < "3.0.0":
pytest.skip()
graph = Graph({i: Block(10) for i in range(1, 4)}, {1: [2], 2: [3]})
split_graph = Graph({
1: Block(10),
2: Block(10),
3: Block(10),
4: Block(10),
}, {
1: [2, 3],
2: [4],
3: [4]
})
@pytest.mark.skip("Legacy")
class TestDagHoleCleanerGetLeftSideOfHoles(unittest.TestCase):
def test_simple(self):
pileup = DensePileup.from_intervals(graph, [Interval(0, 3, [1])])
cleaner = DagHoleCleaner(pileup, 3)
left_holes = cleaner.get_left_side_of_holes()
def setUp(self):
self.graph = Graph({i: Block(3) for i in range(1, 3)}, {1: [2]})