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"tests for bx.align.epo"
import pdb
import random
import unittest
import numpy as np
from bx.align._epo import (
bed_union,
cumulative_intervals,
)
from bx.align.epo import (
Chain,
EPOitem,
)
class TestBed(unittest.TestCase):
def setUp(self):
self.N = random.randint(1, 1000)
def test_ci(self):
S, D = [], []
for i in range(self.N):
S.append(random.randint(10, 50))
D.append(random.randint(10, 50))
D[-1] = 0
C = cumulative_intervals(np.array(S, dtype=np.int64), np.array(D, dtype=np.int64))
for i in range(self.N):
assert C[i, 1] - C[i, 0] == S[i]
for i in range(1, self.N):
assert C[i, 0] - C[i - 1, 1] == D[i - 1], "[%d] %d != %d" % (i, C[i, 0] - C[i - 1, 1], D[i - 1])
def test_elem_u(self):
# back to back, so should return a single interval
EL = []
th = 0
for i in range(self.N):
size = random.randint(1, 20)
EL.append((th, th + size))
th += size
U = bed_union(np.array(EL, dtype=np.uint64))
assert U[0, 0] == 0 and U[0, 1] == th
# disjoint
EL = []
th = 0
for i in range(self.N):
size = random.randint(1, 20)
EL.append((th, th + size))
th += size + 1
U = bed_union(np.array(EL, dtype=np.uint64))
for i in range(U.shape[0]):
assert (U[i, 0], U[i, 1]) == EL[i]
# random with some empty elements
EL = []
th = 0
for i in range(self.N):
size = random.randint(1, 20)
EL.append((th, th + size))
th += random.randint(1, size + size) # 50% of overlapping
U = bed_union(np.array(EL, dtype=np.uint64))
assert U[0, 1] > U[0, 0]
for i in range(1, U.shape[0]):
assert U[i, 1] > U[i, 0]
assert U[i, 0] > U[i - 1, 1]
cigar_pairs = [
(
"GGACCTGGAGAGATCAG---------------------------GACTTCAACTGTGTG-------------TCTTAGACTGGG--------AGGGTGTTA",
"AGGCCAGGAGAGATCAGGTAAGTCTTAATTTAATAAAGAGATAGGACCTGAACTGTGTCTAACAATAGGTAATATTAGACTGGGGGAGAGAGAAGACTTTC",
),
(
"TTT--------------------------------------------------------------------------------------------------------------------T",
"CTTGTACCAAGGACAGTACTGGCAGCCTAATTGCTAACACTTTGTGGTGGATTGGTCCACTCAATATTTGTTCCCACCTCTTTTCAGTCCAGTTCTATAAAGGACAGAAAGTTGAAAACT",
),
(
"A-------------------------------------------------ACACTGGACACAGCACTAACACGATTACTTA",
"ACATTTCCCACACTCCCTTGCAGCTAGGTTTCTAGATATAATTTAGATTCCA----------------------------A",
),
(
"TTTGGTCCTCTGGA------CGAGCAGCCAGTGCT---------------------------------------------------------------------------AAAAAAAA",
"T---CATTCTAGCAGGTGCTGCAGCAGCAGGTAGCCCTGGAGCCAACAGTTGTGGCTATGATTCTTGATCATCAGATTTGGCTCAAGTGATGTGTTCCTCTAGCATGCACTTGAGATA",
),
(
"G-----------------------C----------------------------------------------------------------------------------------A",
"GGCCTGCACTGCCAGTAATTTTAACAAATTTTTAGGCACTGAATTCCCTGTATTAAATCTGTTTTCCTTAGCGTAAACAGATCTCTGTTAAATGAAACTAAACCCTGACTGATA",
),
("TATT----------------------------------T", "TCCTTCATTTTATTTCTCCCTTAAAATTTTTTTTATTACT"),
(
"TAAAAA--A------A------------------------------------------------------------TTTTTTTTTTT",
"T---AATTATTTTGCAGCAGGTCCTTGATAACATATCATCTATAAATATTTCAGCAAGAATCTCTAAAAGGCAAGAACCTCCTTCTT",
),
("AAACAA---------------------------------------TT---T", "AAACAATACCACTGCATCACTATCAAACCCAAAAAATAACAAAAATTGGGT"),
(
"TCTTAAC---TGCTGAGCCATCCCTCCAGCTCCTGTTTTATTTTTATTATGAAGTAATAATA--ATAG--TAATAATAATGATG",
"TACACTTAATTCTAAAACTTGTTATGAATCATCA----------TTGG--TTTTTTATTGTGAAGAACTAATATAATCAGA--G",
),
(
"ATGATAATGGTATCCTAGCTCAACACCTG-GAGTTCACCCCAACAGTTAACTAA----GTTTGAGGAAGTGTTAACAAGCCTA---ACAAAGAGGACATGCCAATAGCTGACAGAGTCAC",
"A-------CCTCTGCTAGCTCAACTCCTGAGAATCAATTATATAAGCTAGGTCAGTGGTTTTGAGAAAGTATTAGTAGACATTTCTCCAAAGAATACATAAAAATGGCC-A--CAAGTAT",
),
]
def toCigar(species, id, s):
I = [(0, 0)]
L = [len(_) for _ in s.split("-")]
NZ = [_ for _ in L if _]
if L[0] > 0:
I.append((0, L[0]))
NZ = NZ[1:]
L = L[1:]
for i in range(len(NZ)):
L.insert(0, 0)
size = NZ[i]
start = L.index(size)
I.append((I[-1][1] + start, I[-1][1] + start + size))
L = L[start + 1 :]
if len(L):
I.append((I[-1][1] + len(L), I[-1][1] + len(L)))
C = []
for i in range(1, len(I)):
dl = I[i][0] - I[i - 1][1]
ml = I[i][1] - I[i][0]
dc = ""
if dl:
dc = (dl > 1 and str(dl) or "") + "D"
mc = ""
if ml:
mc = (ml > 1 and str(ml) or "") + "M"
C.append(dc + mc)
MSUM = sum(i[1] - i[0] for i in I)
start = random.randint(50, 10000)
return "%s\t%d\t1\t%d\t%d\t%d\t%s" % (species, id, start, start + MSUM - 1, random.choice((-1, 1)), "".join(C))
class TestEpo(unittest.TestCase):
def setUp(self):
self.epo_records = []
for i, (t, q) in enumerate(cigar_pairs):
gab_pair = (toCigar("homo_sapiens", i, t), toCigar("mus_musculus", i, q))
A = EPOitem._strfactory(gab_pair[0])
B = EPOitem._strfactory(gab_pair[1])
if A and B:
self.epo_records.append((A, B))
def test_out(self):
def ch(c, ci):
th = 0
for l, t in ci:
if t == "M":
assert c[th : th + l].find("-") == -1
else:
assert c[th : th + l] == "-" * l
th += l
for a, b in self.epo_records:
ca, cb = cigar_pairs[int(a.gabid)]
ch(ca, a.cigar_iter(False))
ch(cb, b.cigar_iter(False))
def test_make_chain(self):
def cch(cigar, s, e):
return cigar[s:e].find("-") == -1
for p in self.epo_records:
chain = Chain._make_from_epo(p[0], p[1], {"chr1": 500}, {"chr1": 800})
if not chain:
continue
ch, S, T, Q = chain
i = int(ch.id)
c1, c2 = cigar_pairs[i]
if p[0].strand == "-":
c1 = c1[::-1]
c2 = c2[::-1]
th = 0
for s, t, q in zip(S, T, Q):
if not (cch(c1, th, th + s) and cch(c2, th, th + s)):
pdb.set_trace()
assert cch(c1, th, th + s) and cch(c2, th, th + s), f"{c1[th:th + s]} and {c2[th:th + s]}"
if t > q:
cch(c1, th + s, th + s + t) and c1[th + s : th + s + t] == "-" * t
else:
cch(c2, th + s, th + s + q) and c1[th + s : th + s + q] == "-" * q
th = th + s + max(t, q)
def test_rem_dash(self):
# ****--****-------**** 4M2D4M7D4M
# *******-------******* 7M7D7M
# has 4 dash columns and should become
# ****--****---**** 4M2D4M3D4M
# *******---******* 7M3D7M
for i in range(100):
dash_cols = random.randint(0, 10)
tStart = random.randint(0, 1000)
qStart = random.randint(0, 1000)
epo_pair = (
EPOitem._strfactory(
"homo_sapiens\t0\t1\t%d\t%d\t1\t%s" % (tStart, tStart + 12 - 1, "4M2D4M%dD4M" % (dash_cols + 3))
),
EPOitem._strfactory(
"mus_musculus\t0\t1\t%d\t%d\t1\t%s" % (qStart, qStart + 14 - 1, "7M%dD7M" % (dash_cols + 3))
),
)
chain = Chain._make_from_epo(epo_pair[0], epo_pair[1], {"chr1": 500}, {"chr1": 800})
ti = epo_pair[0].intervals(False)
qi = epo_pair[1].intervals(False)
assert ti[2][0] - ti[1][1] - dash_cols == chain[2][1]
assert qi[1][0] - qi[0][1] - dash_cols == chain[2][1]
# ----*****
# *-------*
# has 3 dash cols and should become
# *
# *
# with the qStart += 1 and tStart += 4
for i in range(100):
dash_cols = random.randint(0, 10)
tm = random.randint(6, 10)
qm = random.randint(1, 5)
tStart = random.randint(0, 1000)
qStart = random.randint(0, 1000)
epo_pair = (
EPOitem._strfactory(
"homo_sapiens\t0\t1\t%d\t%d\t1\t%s" % (tStart, tStart + tm - 1, "%dD%dM" % (dash_cols + 1, tm))
),
EPOitem._strfactory(
"mus_musculus\t0\t1\t%d\t%d\t1\t%s"
% (qStart, qStart + qm + 1 - 1, "M%dD%dM" % (dash_cols + tm - qm, qm))
),
)
chain = Chain._make_from_epo(epo_pair[0], epo_pair[1], {"chr1": 500}, {"chr1": 800})
if chain[1][-1] != qm:
pdb.set_trace()
assert chain[1][-1] == qm
# correct also for coordinate interpretation differences between UCSC and EPO
assert (qStart + 1) - 1 == chain[0].qStart, "%d != %d" % (qStart + 1, chain[0].qStart)
if __name__ == "__main__":
unittest.main()
|
