def test_add_info_table():
vcf = viola.read_vcf(os.path.join(HERE, 'data/test.manta.vcf'))
vcf_expected = viola.read_vcf(
os.path.join(HERE, 'data/test.info.added.manta.vcf'))
table = vcf.svlen
table.columns = ['id', 'value_idx', 'test']
vcf.add_info_table('test', table, 1, 'Integer', 'test info')
assert_vcf_equal(vcf, vcf_expected)
def test_drop_by_id():
vcf = viola.read_vcf(os.path.join(HERE, 'data/test.manta.vcf'))
vcf_dropped_expected = viola.read_vcf(os.path.join(HERE, 'data/test.dropped.manta.vcf'))
vcf_dropped2_expected = viola.read_vcf(os.path.join(HERE, 'data/test.dropped2.manta.vcf'))
vcf_dropped = vcf.drop_by_id('test1')
vcf_dropped2 = vcf.drop_by_id(['test2', 'test3'])
assert_vcf_equal(vcf_dropped, vcf_dropped_expected)
assert_vcf_equal(vcf_dropped2, vcf_dropped2_expected)
def generate_feature_matrix(input_dir, input_files, input_files_id, format_,
caller, svtype_col_name, as_breakpoint,
definitions, output):
"""
Generate feature matrix from VCF or BEDPE files.
"""
if format_ == 'bedpe':
if (input_dir is None) & (input_files is None):
return
elif (input_files is None):
data = viola.read_bedpe_multi(input_dir,
svtype_col_name=svtype_col_name)
elif (input_dir is None):
ls_input = input_files.split(',')
ls_bedpe = [
viola.read_bedpe(path, svtype_col_name=svtype_col_name)
for path in ls_input
]
if input_files_id is None:
ls_names = range(len(ls_bedpe))
else:
ls_names = input_files_id.split(',')
data = viola.MultiBedpe(ls_bedpe, ls_names)
else:
return
else:
if (input_dir is None) & (input_files is None):
return
elif (input_files is None):
data = viola.read_vcf_multi(input_dir,
variant_caller=caller,
as_breakpoint=as_breakpoint)
elif (input_dir is None):
ls_input = input_files.split(',')
if as_breakpoint:
ls_vcf = [
viola.read_vcf(
path, variant_caller=caller).breakend2breakpoint()
for path in ls_input
]
else:
ls_vcf = [
viola.read_vcf(path, variant_caller=caller)
for path in ls_input
]
if input_files_id is None:
ls_names = range(len(ls_vcf))
else:
ls_names = input_files_id.split(',')
data = viola.MultiBedpe(ls_vcf, ls_names)
else:
return
result = data.classify_manual_svtype(definitions=definitions)
result.to_csv(output, sep='\t')
def test_merge3():
manta = viola.read_vcf(StringIO(DATA1), variant_caller='manta')
delly = viola.read_vcf(StringIO(DATA2), variant_caller='delly')
result = viola.merge([delly, manta],
mode='confidence_intervals',
integration=True)
assert result.sv_count == 4
assert result.get_ids() == {
'manta_M1', 'delly_MD1', 'delly_MDL1', 'delly_D1'
}
def test_merge():
manta = viola.read_vcf(os.path.join(HERE, 'data/test.merge.manta.vcf'),
variant_caller='manta')
delly = viola.read_vcf(os.path.join(HERE, 'data/test.merge.delly.vcf'),
variant_caller='delly')
lumpy = viola.read_vcf(os.path.join(HERE, 'data/test.merge.lumpy.vcf'),
variant_caller='lumpy')
gridss = viola.read_vcf(os.path.join(HERE, 'data/test.merge.gridss.vcf'),
variant_caller='gridss')
merged = manta.merge(threshold=100,
ls_caller_names=['manta', 'delly', 'lumpy', 'gridss'],
ls_vcf=[manta, delly, lumpy, gridss])
def test_merge2():
gridss = viola.read_vcf(StringIO(DATA1), variant_caller='gridss').breakend2breakpoint()
manta = viola.read_vcf(StringIO(DATA2), variant_caller='manta').breakend2breakpoint()
result = viola.merge([manta, gridss], mode='confidence_intervals', integration=True)
result = result.filter('supportingcallercount > 1')
assert result.sv_count == 5
assert result.get_ids() == {
'manta_MantaDUP:TANDEM:88695:0:1:0:0:0',
'manta_viola_breakpoint:0',
'manta_MantaDUP:TANDEM:93040:0:1:0:0:0',
'manta_viola_breakpoint:1',
'manta_viola_breakpoint:2'
}
def test_merge1():
gridss = viola.read_vcf(StringIO(DATA1), variant_caller='gridss').breakend2breakpoint()
manta = viola.read_vcf(StringIO(DATA2), variant_caller='manta').breakend2breakpoint()
result = viola.merge([gridss, manta], mode='confidence_intervals', integration=True)
result = result.filter('supportingcallercount > 1')
assert result.sv_count == 5
assert result.get_ids() == {
'gridss_viola_breakpoint:0',
'gridss_viola_breakpoint:1',
'gridss_viola_breakpoint:6',
'gridss_viola_breakpoint:7',
'gridss_viola_breakpoint:8',
}
def test_copy():
manta_path = os.path.join(HERE, '../io/data/test.manta.vcf')
delly_path = os.path.join(HERE, '../io/data/test.delly.vcf')
lumpy_path = os.path.join(HERE, '../io/data/test.lumpy.vcf')
gridss_path = os.path.join(HERE, '../io/data/test.gridss.vcf')
manta_vcf = viola.read_vcf(manta_path)
delly_vcf = viola.read_vcf(delly_path, variant_caller='delly')
lumpy_vcf = viola.read_vcf(lumpy_path, variant_caller='lumpy')
gridss_vcf = viola.read_vcf(gridss_path, variant_caller='gridss')
assert_vcf_equal(manta_vcf, manta_vcf.copy())
assert_vcf_equal(delly_vcf, delly_vcf.copy())
assert_vcf_equal(lumpy_vcf, lumpy_vcf.copy())
assert_vcf_equal(gridss_vcf, gridss_vcf.copy())
class TestToVcf:
#manta_path = os.path.join(HERE, 'data/manta1.inv.vcf')
#result = viola.read_vcf(manta_path)
body = """chr10 39984191 43 N <INV> . . SVTYPE=INV;STRANDS=++:4,--:2;SVLEN=176;END=39984367;CIPOS=-8,11;CIEND=-17,31;CIPOS95=-3,6;CIEND95=-1,15;IMPRECISE;SU=6;PE=6;SR=0 GT:SU:PE:SR ./.:3:3:0 ./.:3:3:0
chr10 121422696 788 N <DEL> . . SVTYPE=DEL;STRANDS=+-:8;SVLEN=-21;END=121422717;CIPOS=-9,8;CIEND=-9,8;CIPOS95=0,0;CIEND95=0,0;SU=8;PE=0;SR=8 GT:SU:PE:SR ./.:8:0:8 ./.:0:0:0
chr14 45812810 7294_1 N [chr14:65332314[N . . SVTYPE=BND;STRANDS=--:10;EVENT=7294;MATEID=7294_2;CIPOS=-7,6;CIEND=-7,6;CIPOS95=0,0;CIEND95=0,0;SU=10;PE=0;SR=10 GT:SU:PE:SR ./.:10:0:10 ./.:0:0:0
chr14 65332314 7294_2 N [chr14:45812810[N . . SVTYPE=BND;STRANDS=--:10;SECONDARY;EVENT=7294;MATEID=7294_1;CIPOS=-7,6;CIEND=-7,6;CIPOS95=0,0;CIEND95=0,0;SU=10;PE=0;SR=10 GT:SU:PE:SR ./.:10:0:10 ./.:0:0:0
chr15 60882465 8801 N <DUP> . . SVTYPE=DUP;STRANDS=-+:41;SVLEN=3099777;END=63982242;CIPOS=-3,1;CIEND=-3,2;CIPOS95=0,0;CIEND95=0,0;SU=41;PE=19;SR=22 GT:SU:PE:SR ./.:41:19:22 ./.:0:0:0
"""
expected_out = """chr10 39984191 43_1 N <INV> . PASS SVTYPE=INV;STRANDS=++:4;EVENT=43;SVLEN=176;END=39984367;CIPOS=-8,11;CIEND=-17,31;CIPOS95=-3,6;CIEND95=-1,15;IMPRECISE;SU=4;PE=6;SR=0;SUORG=6 GT:SU:PE:SR ./.:3:3:0 ./.:3:3:0
chr10 39984191 43_2 N <INV> . PASS SVTYPE=INV;STRANDS=--:2;EVENT=43;SVLEN=176;END=39984367;CIPOS=-8,11;CIEND=-17,31;CIPOS95=-3,6;CIEND95=-1,15;IMPRECISE;SU=2;PE=6;SR=0;SUORG=6 GT:SU:PE:SR ./.:3:3:0 ./.:3:3:0
chr10 121422696 788 N <DEL> . PASS SVTYPE=DEL;STRANDS=+-:8;SVLEN=-21;END=121422717;CIPOS=-9,8;CIEND=-9,8;CIPOS95=0,0;CIEND95=0,0;SU=8;PE=0;SR=8 GT:SU:PE:SR ./.:8:0:8 ./.:0:0:0
chr14 45812810 7294_1 N [chr14:65332314[N . PASS SVTYPE=BND;STRANDS=--:10;EVENT=7294;MATEID=7294_2;CIPOS=-7,6;CIEND=-7,6;CIPOS95=0,0;CIEND95=0,0;SU=10;PE=0;SR=10 GT:SU:PE:SR ./.:10:0:10 ./.:0:0:0
chr14 65332314 7294_2 N [chr14:45812810[N . PASS SVTYPE=BND;STRANDS=--:10;SECONDARY;EVENT=7294;MATEID=7294_1;CIPOS=-7,6;CIEND=-7,6;CIPOS95=0,0;CIEND95=0,0;SU=10;PE=0;SR=10 GT:SU:PE:SR ./.:10:0:10 ./.:0:0:0
chr15 60882465 8801 N <DUP> . PASS SVTYPE=DUP;STRANDS=-+:41;SVLEN=3099777;END=63982242;CIPOS=-3,1;CIEND=-3,2;CIPOS95=0,0;CIEND95=0,0;SU=41;PE=19;SR=22 GT:SU:PE:SR ./.:41:19:22 ./.:0:0:0
"""
b = StringIO(HEADER + body)
result = viola.read_vcf(b, variant_caller='lumpy')
def test_to_vcf_like(self):
df_vcf = self.result.to_vcf_like()
df_expected = pd.read_csv(StringIO(self.expected_out),
index_col=False,
names=df_vcf.columns,
sep='\t')
pd.testing.assert_frame_equal(df_vcf, df_expected)
def test_classify_manual_svtype():
vcf = viola.read_vcf(os.path.join(HERE, 'data/manta1.vcf'))
vcf2 = vcf.copy()
vcf = vcf.breakend2breakpoint()
vcf2 = vcf2.breakend2breakpoint()
multi_vcf = viola.MultiVcf([vcf, vcf2], ['vcf1', 'vcf2'])
ls_conditions = [
small_del, large_del, small_dup, large_dup, small_inv, tra
]
ls_names = [
'small_del', 'large_del', 'small_dup', 'large_dup', 'small_inv', 'tra'
]
result = multi_vcf.classify_manual_svtype(ls_conditions=ls_conditions,
ls_names=ls_names)
manual_sv_type = multi_vcf.manual_sv_type
manual_sv_type.set_index('id', inplace=True)
manual_sv_type_expected = pd.read_csv(StringIO(data_expected),
sep='\t',
names=('id', 'value_idx',
'manual_sv_type'))
manual_sv_type_expected.set_index('id', inplace=True)
pd.testing.assert_frame_equal(manual_sv_type,
manual_sv_type_expected,
check_like=True)
result_expected = pd.DataFrame([[2, 3, 1, 0, 2, 2, 1],
[2, 3, 1, 0, 2, 2, 1]])
result_expected.columns = ls_names + ['others']
result_expected.columns.name = 'manual_sv_type'
result_expected.index = ['vcf1', 'vcf2']
result_expected.index.name = 'patients'
pd.testing.assert_frame_equal(result, result_expected)
class TestReadVcfLumpy:
vcf_lumpy_inv = viola.read_vcf(lumpy_body_inv_buf, variant_caller='lumpy')
def test_read_vcf_lumpy_inv(self):
vcf = self.vcf_lumpy_inv
# assert positions table equal
df_pos_expected = pd.read_csv(
StringIO(
"""id,chrom1,pos1,chrom2,pos2,strand1,strand2,ref,alt,qual,svtype
43_1,chr10,39984191,chr10,39984367,+,+,N,<INV>,None,INV
43_2,chr10,39984192,chr10,39984367,-,-,N,<INV>,None,INV"""))
df_pos_expected['qual'] = None
pd.testing.assert_frame_equal(vcf.positions, df_pos_expected)
# assert strands table equal
df_info_strands_expected = pd.read_csv(
StringIO("""id,value_idx,strands
43_1,0,++:4
43_2,0,--:2"""))
pd.testing.assert_frame_equal(vcf.strands, df_info_strands_expected)
# assert su table equal
df_info_su_expected = pd.read_csv(
StringIO("""id,value_idx,su
43_1,0,4
43_2,0,2"""))
pd.testing.assert_frame_equal(vcf.su, df_info_su_expected)
# assert suorg table equal
df_info_suorg_expected = pd.read_csv(
StringIO("""id,value_idx,suorg
43_1,0,6
43_2,0,6"""))
pd.testing.assert_frame_equal(vcf.suorg, df_info_suorg_expected)
def test_replace_svid():
vcf = viola.read_vcf(StringIO(HEADER + body))
vcf_expected1 = viola.read_vcf(StringIO(HEADER + body_expected1))
vcf_expected2 = viola.read_vcf(StringIO(HEADER + body_expected2))
vcf1 = vcf.copy()
vcf1.replace_svid('test1', 'a')
assert_vcf_equal(vcf1, vcf_expected1)
vcf1_ex = vcf.copy()
vcf1_ex.replace_svid(['test1'], ['a'])
assert_vcf_equal(vcf1_ex, vcf_expected1)
vcf2 = vcf.copy()
vcf2.replace_svid(['test2', 'test3'], ['a', 'b'])
assert_vcf_equal(vcf2, vcf_expected2)
def test_breakend2breakpoint():
vcf = viola.read_vcf(StringIO(HEADER + body), variant_caller='lumpy')
vcf_expected = viola.read_vcf(StringIO(HEADER_expected + body_expected),
variant_caller='lumpy')
ex_svpos = vcf_expected.get_table('positions')
ex_svpos.loc[3, 'svtype'] = 'INV'
ex_svtype = vcf_expected.get_table('svtype')
ex_svtype.iloc[3, 2] = 'INV'
ex_infos_meta = vcf_expected.get_table('infos_meta')
ex_infos_meta.index = [
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 17
]
vcf_expected._odict_alltables['positions'] = ex_svpos
vcf_expected._odict_alltables['svtype'] = ex_svtype
vcf_expected._odict_alltables['infos_meta'] = ex_infos_meta
vcf_result = vcf.breakend2breakpoint()
assert_vcf_equal(vcf_result, vcf_expected)
def test_filter_by_id(self):
body_expected = """chr1 82550461 test1 G <DEL> . MinSomaticScore END=82554225;SVTYPE=DEL;SVLEN=-3764;IMPRECISE;CIPOS=-51,52;CIEND=-51,52;SOMATIC;SOMATICSCORE=10 PR:SR 21,0:10,0 43,4:15,3
chr1 60567906 test3 T <DEL> . MinSomaticScore END=60675940;SVTYPE=DEL;SVLEN=-108034;CIPOS=-44,44;CIEND=-38,39;SOMATIC;SOMATICSCORE=18 PR 23,0 44,6
"""
expected_b = StringIO(HEADER + body_expected)
obj_expected = viola.read_vcf(expected_b)
obj_result = self.obj.filter_by_id(['test1', 'test3'])
viola.testing.assert_vcf_equal(obj_expected, obj_result)
def test_get_table():
data = viola.read_vcf(os.path.join(HERE, 'data/test.manta.vcf'))
# get positions table
positions = data.get_table('positions')
## test for TableNotFoundError
with pytest.raises(TableNotFoundError):
data.get_table("notexists")
def vcf2bedpe(caller, info, filter_, format_, vcf):
"""
Convert a VCF file into a BEDPE file.
A VCF argument is the path to the input VCF file.
"""
if isinstance(vcf, TextIOWrapper):
vcf_obj = viola.read_vcf(StringIO(vcf.read()), variant_caller=caller)
else:
vcf_obj = viola.read_vcf(vcf, variant_caller=caller)
if info is not None:
ls_info = info.split(',')
ls_info_lower = [i.lower() for i in ls_info]
else:
ls_info_lower = []
bedpe_like = vcf_obj.to_bedpe_like(custom_infonames=ls_info_lower,
add_filters=filter_,
add_formats=format_)
click.echo(bedpe_like.to_string(index=None))
def test_merge():
manta = viola.read_vcf(os.path.join(HERE, 'data/test.merge.manta.vcf'),
variant_caller='manta')
delly = viola.read_vcf(os.path.join(HERE, 'data/test.merge.delly.vcf'),
variant_caller='delly')
lumpy = viola.read_vcf(os.path.join(HERE, 'data/test.merge.lumpy.vcf'),
variant_caller='lumpy')
gridss = viola.read_vcf(os.path.join(HERE, 'data/test.merge.gridss.vcf'),
variant_caller='gridss')
result = manta._generate_distance_matrix_by_confidence_intervals(
viola.TmpVcfForMerge([manta, delly, gridss, lumpy],
['manta', 'delly', 'gridss', 'lumpy']))
result = viola.merge([manta, delly, lumpy, gridss],
mode='confidence_intervals')
assert result.get_ids() == {
'manta_M1', 'manta_MD1', 'manta_ML1', 'manta_MG1', 'manta_MDL1',
'manta_MDG1', 'manta_MLG1', 'manta_MDLG1o', 'delly_D1', 'delly_DL1',
'delly_DG1', 'delly_DLG1', 'lumpy_L1', 'lumpy_LG1', 'gridss_G1o'
}
class TestWriteVcf:
# get vcf class
#manta_path = os.path.join(HERE, 'data/manta1.inv.vcf')
manta_path = os.path.join(HERE, 'data/test.manta.vcf')
lumpy_path = os.path.join(HERE, 'data/test.lumpy.vcf')
delly_path = os.path.join(HERE, 'data/test.delly.vcf')
gridss_path = os.path.join(HERE, 'data/test.gridss.vcf')
vcf_manta = viola.read_vcf(manta_path)
vcf_lumpy = viola.read_vcf(lumpy_path, variant_caller='lumpy')
vcf_delly = viola.read_vcf(delly_path, variant_caller='delly')
vcf_gridss = viola.read_vcf(gridss_path, variant_caller='gridss')
def test_write_vcf_manta(self):
# self.df.to_csv('path/to/csv')
self.vcf_manta.to_vcf('tests/io/output/write_vcf_manta.vcf')
#assert filecmp.cmp('tests/io/output/write_vcf.vcf', 'tests/io/data/manta1.inv.vcf')
assert filecmp.cmp('tests/io/output/write_vcf_manta.vcf',
'tests/io/data/test.manta.validation.vcf')
def test_write_vcf_lumpy(self):
# self.df.to_csv('path/to/csv')
self.vcf_lumpy.to_vcf('tests/io/output/write_vcf_lumpy.vcf')
#assert filecmp.cmp('tests/io/output/write_vcf.vcf', 'tests/io/data/manta1.inv.vcf')
assert filecmp.cmp('tests/io/output/write_vcf_lumpy.vcf',
'tests/io/data/test.lumpy.validation.vcf')
def test_write_vcf_delly(self):
self.vcf_delly.to_vcf('tests/io/output/write_vcf_delly.vcf')
assert filecmp.cmp('tests/io/output/write_vcf_delly.vcf',
'tests/io/data/test.delly.validation.vcf')
def test_write_vcf_gridss(self):
self.vcf_gridss.to_vcf('tests/io/output/write_vcf_gridss.vcf')
assert filecmp.cmp('tests/io/output/write_vcf_gridss.vcf',
'tests/io/data/test.gridss.validation.vcf')
def test_write_info(self):
self.vcf_manta.to_vcf('tests/io/output/write_info.vcf', onlyinfo=True)
#assert filecmp.cmp('tests/io/output/write_info.vcf', 'tests/io/data/manta1.inv_info.vcf')
assert filecmp.cmp('tests/io/output/write_info.vcf',
'tests/io/data/test_info.vcf')
class TestAppendInfos:
manta_path = os.path.join(HERE, 'data/test.manta.vcf')
reader = viola.read_vcf(manta_path)
positions = reader.get_table('positions')
def test_append_svlen(self):
if 'svlen' in self.reader.table_list:
result = viola.Vcf.append_infos(self.reader,
self.positions,
ls_tablenames=['svlen'])
assert result.columns[-1] == 'svlen_0'
assert result['svlen_0'].notnull().any()
class TestFilters:
body = """chr1 82550461 test1 G <DEL> . MinSomaticScore END=82554225;SVTYPE=DEL;SVLEN=-3764;IMPRECISE;CIPOS=-51,52;CIEND=-51,52;SOMATIC;SOMATICSCORE=10 PR:SR 21,0:10,0 43,4:15,3
chr1 22814216 test2 T <INV> . MinSomaticScore END=92581131;SVTYPE=INV;SVLEN=69766915;IMPRECISE;CIPOS=-51,51;CIEND=-89,90;SOMATIC;SOMATICSCORE=11;INV5 PR 24,0 35,5
chr1 60567906 test3 T <DEL> . MinSomaticScore END=60675940;SVTYPE=DEL;SVLEN=-108034;CIPOS=-44,44;CIEND=-38,39;SOMATIC;SOMATICSCORE=18 PR 23,0 44,6
chr1 69583190 test4 T <DEL> . PASS END=69590947;SVTYPE=DEL;SVLEN=-7757;IMPRECISE;CIPOS=-123,123;CIEND=-135,136;SOMATIC;SOMATICSCORE=47 PR 21,0 20,12
"""
data = HEADER + body
b = StringIO(data)
obj = viola.read_vcf(b)
def test_filter_infos(self):
result_svlen = self.obj._filter_infos('svlen',
0,
operator="<",
threshold=10000)
result_svtype = self.obj._filter_infos('svtype',
0,
operator='==',
threshold='INV')
assert result_svlen == {'test1', 'test3', 'test4'}
assert result_svtype == {'test2'}
def test_filter_infos_flag(self):
result_imprecise = self.obj._filter_infos_flag('imprecise',
exclude=False)
result_imprecise_ex = self.obj._filter_infos_flag('imprecise',
exclude=True)
assert result_imprecise == {'test1', 'test2', 'test4'}
assert result_imprecise_ex == {'test3'}
def test_filter_filters(self):
result_filter = self.obj._filter_filters('PASS', exclude=False)
result_filter_ex = self.obj._filter_filters('PASS', exclude=True)
assert result_filter == {'test4'}
assert result_filter_ex == {'test1', 'test2', 'test3'}
def test_filter_formats(self):
result_format = self.obj._filter_formats('mouse1_T', 'PR', 1, '>', 5)
assert result_format == {'test3', 'test4'}
def test_filter_by_id(self):
body_expected = """chr1 82550461 test1 G <DEL> . MinSomaticScore END=82554225;SVTYPE=DEL;SVLEN=-3764;IMPRECISE;CIPOS=-51,52;CIEND=-51,52;SOMATIC;SOMATICSCORE=10 PR:SR 21,0:10,0 43,4:15,3
chr1 60567906 test3 T <DEL> . MinSomaticScore END=60675940;SVTYPE=DEL;SVLEN=-108034;CIPOS=-44,44;CIEND=-38,39;SOMATIC;SOMATICSCORE=18 PR 23,0 44,6
"""
expected_b = StringIO(HEADER + body_expected)
obj_expected = viola.read_vcf(expected_b)
obj_result = self.obj.filter_by_id(['test1', 'test3'])
viola.testing.assert_vcf_equal(obj_expected, obj_result)
class TestReadVcfLumpy:
vcf_delly = viola.read_vcf(delly_body_buf, variant_caller='delly')
def test_read_vcf_delly(self):
vcf = self.vcf_delly
# assert positions table equal
df_pos_expected = pd.read_csv(
StringIO(
"""id,chrom1,pos1,chrom2,pos2,strand1,strand2,ref,alt,qual,svtype
DEL00001,chr10,3485568,chr10,3485618,+,-,C,<DEL>,180,DEL
INV00001,chr10,8825910,chr10,32816609,-,-,A,<INV>,17,INV
DUP00001,chr10,11350704,chr10,122603091,-,+,G,<DUP>,29,DUP
INV00002,chr10,61016659,chr10,111424580,+,+,G,<INV>,10,INV
BND00001,chr11,15249914,chr10,72297333,+,+,A,A]chr10:72297333],193,BND
"""))
pd.testing.assert_frame_equal(vcf.positions, df_pos_expected)
class TestToBedpe:
#manta_path = os.path.join(HERE, 'data/manta1.inv.vcf')
#result = viola.read_vcf(manta_path)
body = """chr1 82550461 test1 G <DEL> . MinSomaticScore END=82554225;SVTYPE=DEL;SVLEN=-3764;IMPRECISE;CIPOS=-51,52;CIEND=-51,52;SOMATIC;SOMATICSCORE=10 PR:SR 21,0:10,0 43,4:15,3
chr1 22814216 test2 T <INV> . MinSomaticScore END=92581131;SVTYPE=INV;SVLEN=69766915;IMPRECISE;CIPOS=-51,51;CIEND=-89,90;SOMATIC;SOMATICSCORE=11;INV5 PR 24,0 35,5
chr1 60567906 test3 T <DEL> . MinSomaticScore END=60675940;SVTYPE=DEL;SVLEN=-108034;CIPOS=-44,44;CIEND=-38,39;SOMATIC;SOMATICSCORE=18 PR 23,0 44,6
chr1 69583190 test4 T <DEL> . PASS END=69590947;SVTYPE=DEL;SVLEN=-7757;IMPRECISE;CIPOS=-123,123;CIEND=-135,136;SOMATIC;SOMATICSCORE=47 PR 21,0 20,12
"""
b = StringIO(HEADER + body)
result = viola.read_vcf(b)
def test_to_bedpe_like(self):
self.result.to_bedpe(os.path.join(HERE, 'data/out.bedpe'))
assert filecmp.cmp(os.path.join(HERE, 'data/out.bedpe'),
os.path.join(HERE, 'data/expected.bedpe'))
def test_to_bedpe_like_with_info(self):
self.result.to_bedpe(os.path.join(HERE, 'data/out.svlen.bedpe'),
custom_infonames=['svlen'])
assert filecmp.cmp(os.path.join(HERE, 'data/out.svlen.bedpe'),
os.path.join(HERE, 'data/expected.svlen.bedpe'))
import viola
import numpy as np
import os
HERE = os.path.abspath(os.path.dirname(__file__))
delly = viola.read_vcf(os.path.join(HERE, 'data', "test.merge.delly.vcf"),
variant_caller="delly")
manta = viola.read_vcf(os.path.join(HERE, 'data', "test.merge.manta.vcf"),
variant_caller="manta")
gridss = viola.read_vcf(os.path.join(HERE, 'data', "test.merge.gridss.vcf"),
variant_caller="gridss")
lumpy = viola.read_vcf(os.path.join(HERE, 'data', "test.merge.lumpy.vcf"),
variant_caller="lumpy")
def test_merge_to_vcf_like():
merged = viola.merge([manta, gridss, delly, lumpy], integration=True)
merged = merged.filter('supportingcallercount > 1')
merged.to_vcf(os.path.join(HERE, 'data/output_merged.vcf'))
##FILTER=<ID=MaxMQ0Frac,Description="For a small variant (<1000 bases) in the normal sample, the fraction of reads with MAPQ0 around either breakend exceeds 0.4">
##ALT=<ID=INV,Description="Inversion">
##ALT=<ID=DEL,Description="Deletion">
##ALT=<ID=INS,Description="Insertion">
##ALT=<ID=DUP:TANDEM,Description="Tandem Duplication">
#CHROM POS ID REF ALT QUAL FILTER INFO FORMAT mouse1_N mouse1_T
"""
#manta_path = os.path.join(HERE, 'data/manta1.inv.vcf')
#result = viola.read_vcf(manta_path)
body = """chr1 82550461 test1 G <DEL> . MinSomaticScore END=82554225;SVTYPE=DEL;SVLEN=-3764;IMPRECISE;CIPOS=-51,52;CIEND=-51,52;SOMATIC;SOMATICSCORE=10 PR:SR 21,0:10,0 43,4:15,3
chr1 22814216 test2 T <INV> . MinSomaticScore END=92581131;SVTYPE=INV;SVLEN=69766915;IMPRECISE;CIPOS=-51,51;CIEND=-89,90;SOMATIC;SOMATICSCORE=11;INV5 PR 24,0 35,5
chr1 60567906 test3 T <DEL> . MinSomaticScore END=60675940;SVTYPE=DEL;SVLEN=-108034;CIPOS=-44,44;CIEND=-38,39;SOMATIC;SOMATICSCORE=18 PR 23,0 44,6
chr1 69583190 test4 T <DEL> . PASS END=69590947;SVTYPE=DEL;SVLEN=-7757;IMPRECISE;CIPOS=-123,123;CIEND=-135,136;SOMATIC;SOMATICSCORE=47 PR 21,0 20,12
"""
b = StringIO(HEADER + body)
result = viola.read_vcf(b)
def test_to_bedpe_like():
expected_data = """chrom1\tstart1\tend1\tchrom2\tstart2\tend2\tname\tscore\tstrand1\tstrand2
chr1\t82550460\t82550461\tchr1\t82554225\t82554226\ttest1\t\t+\t-
chr1\t22814216\t22814217\tchr1\t92581131\t92581132\ttest2\t\t-\t-
chr1\t60567905\t60567906\tchr1\t60675940\t60675941\ttest3\t\t+\t-
chr1\t69583189\t69583190\tchr1\t69590947\t69590948\ttest4\t\t+\t-
"""
df_expected = pd.read_csv(StringIO(expected_data), sep='\t')
df_expected['score'] = df_expected['score'].astype(
object) # because score field is empty in this case
bedpe = result.to_bedpe_like()
pd.testing.assert_frame_equal(bedpe, df_expected, check_exact=True)
def test_breakend2breakpoint():
vcf = viola.read_vcf(StringIO(HEADER + body))
vcf_expected = viola.read_vcf(StringIO(HEADER_expected + body_expected))
vcf_result = vcf.breakend2breakpoint()
assert_vcf_equal(vcf_result, vcf_expected)
def test_remove_info_table():
vcf = viola.read_vcf(os.path.join(HERE, 'data/test.info.added.manta.vcf'))
vcf_expected = viola.read_vcf(os.path.join(HERE, 'data/test.manta.vcf'))
vcf.remove_info_table('test')
assert_vcf_equal(vcf, vcf_expected)
def test_read_vcf_empty_lumpy():
vcf = viola.read_vcf(StringIO(GRIDSS), variant_caller='gridss')
import viola
import numpy as np
delly = viola.read_vcf("/shared_data/share/merge/test.merge.delly.vcf",
variant_caller="delly")
gridss = viola.read_vcf("/shared_data/share/merge/test.merge.gridss.vcf",
variant_caller="gridss")
lumpy = viola.read_vcf("/shared_data/share/merge/test.merge.lumpy.vcf",
variant_caller="lumpy")
manta = viola.read_vcf("/shared_data/share/merge/test.merge.manta.vcf",
variant_caller="manta")
def test_merge():
merged_all = gridss.merge(ls_vcf=[delly, lumpy, manta, gridss],
threshold=100)
viola.testing.assert_vcf_equal(merged_all, merged_all.copy())
import os
import shutil
import viola
vcf_in = str(snakemake.input)
vcf_org = vcf_in + '.org'
vcf_out = str(snakemake.output)
caller = str(snakemake.wildcards.prefix)
if caller == 'gridss':
os.rename(vcf_in, vcf_org)
with open(vcf_in, 'w') as new:
with open(vcf_org, 'r') as org:
for line in org:
# FIX INFO field: change PARID to MATEID
new.write(line.replace('PARID', 'MATEID'))
try:
sv = viola.read_vcf(vcf_in, variant_caller=caller).breakend2breakpoint()
sv.to_vcf(vcf_out)
except Exception:
shutil.copyfile(vcf_in, vcf_out)
def test_single():
vcf = viola.read_vcf(StringIO(HEADER + body), variant_caller='gridss')
vcf_single = vcf.idx['single_test']
print(vcf_single.positions)
