def test_grow2(self):
def sample_data():
return pd.DataFrame([
{
"chr": "1",
"start": 7774885,
"stop": 7791673
},
{
"chr": "1",
"start": 8286026,
"stop": 8298500
},
{
"chr": "1",
"start": 8323232,
"stop": 8342008
},
])
a = regions.GenomicRegions("sharum", sample_data, [],
get_genome_chr_length())
b = a.convert("agrown",
regions.convert.grow(50000),
on_overlap="merge")
force_load(b.load())
run_pipegraph()
assert (b.df["start"] == [7724885, 8236026]).all()
assert (b.df["stop"] == [7841673, 8392008]).all()
def test_random_same_number(self):
def sample_data():
return pd.DataFrame({
"chr": ["1", "2", "1"],
"start": [10, 100, 1000],
"stop": [12, 110, 1110],
"column_that_will_disappear": ["A", "b", "c"],
})
def convert(df):
res = df[["chr", "start", "stop"]]
res = res.assign(start=res["start"] + 1)
return res
if ppg.inside_ppg():
deps = [ppg.ParameterInvariant("shuParam", ("hello"))]
else:
deps = []
a = regions.GenomicRegions("sharum", sample_data, [],
get_genome_chr_length())
a.add_annotator(Constant("Constant", 5))
a.annotate()
b = a.convert("a+1", convert, dependencies=deps)
force_load(b.load())
for d in deps:
assert d in b.load().lfg.prerequisites
run_pipegraph()
assert len(a.df) == len(b.df)
assert (a.df["start"] == b.df["start"] - 1).all()
assert "column_that_will_disappear" in a.df.columns
assert not ("column_that_will_disappear" in b.df.columns)
def test_cookiecutter_summit(self):
def sample_data():
return pd.DataFrame({
"chr": ["1", "2"],
"start": [0, 0],
"stop": [200, 99 * 3]
})
a = regions.GenomicRegions("sharum", sample_data, [],
get_genome_chr_length())
b = a.convert("cookie",
regions.convert.cookie_summit(a.summit_annotator, 220))
c = a.convert(
"cookieB",
regions.convert.cookie_summit(a.summit_annotator,
220,
drop_those_outside_chromosomes=True),
)
force_load(b.load())
force_load(c.load())
run_pipegraph()
assert len(b.df) == 2
assert len(c.df) == 1
assert (b.df["start"] == [0, math.floor(99 * 3 / 2) - 110]).all()
assert (b.df["stop"] == [100 + 110,
math.floor(99 * 3 / 2) + 110]).all()
def test_name_must_be_string(self):
def sample_data():
return pd.DataFrame({
"chr": ["1", "2"],
"start": [0, 0],
"stop": [200, 99 * 3]
})
a = regions.GenomicRegions("sharum", sample_data, [],
get_genome_chr_length())
with pytest.raises(ValueError):
a.convert(123, regions.convert.shift(50))
def test_grow(self):
def sample_data():
return pd.DataFrame({
"chr": ["1", "1", "2"],
"start": [10, 100, 1000],
"stop": [12, 110, 1110],
})
a = regions.GenomicRegions("sharum", sample_data, [],
get_genome_chr_length())
b = a.convert("agrown", regions.convert.grow(12))
force_load(b.load())
run_pipegraph()
assert (b.df["start"] == [0, 100 - 12, 1000 - 12]).all()
assert (b.df["stop"] == [24, 110 + 12, 1110 + 12]).all()
def test_merge_connected_2(self):
def sample_data():
return pd.DataFrame({
"chr": ["1", "1", "2"],
"start": [27897200, 27898600, 0],
"stop": [27897300, 27898700, 100],
})
a = regions.GenomicRegions("sharum", sample_data, [],
get_genome_chr_length())
b = a.convert("agrown", regions.convert.merge_connected())
force_load(b.load())
run_pipegraph()
assert (b.df["start"] == [27897200, 27898600, 0]).all()
assert (b.df["stop"] == [27897300, 27898700, 100]).all()
def test_summit(self):
def sample_data():
return pd.DataFrame({
"chr": ["1", "2"],
"start": [0, 0],
"stop": [200, 99 * 3]
})
a = regions.GenomicRegions("sharum", sample_data, [],
get_genome_chr_length())
b = a.convert("cookie", regions.convert.summit(a.summit_annotator))
force_load(b.load())
run_pipegraph()
assert len(b.df) == 2
assert (b.df["start"] == [100, 148]).all()
assert (b.df["stop"] == [101, 149]).all()
def test_raises_on_conversion_function_not_returning_df(self):
def sample_data():
return pd.DataFrame({
"chr": ["1", "2", "1"],
"start": [10, 100, 1000],
"stop": [12, 110, 1110],
})
def convert(df):
return None
a = regions.GenomicRegions("sharum", sample_data, [],
get_genome_chr_length())
with pytest.raises(ValueError):
a.convert("a+1", convert)
force_load(a.load())
run_pipegraph()
def test_cookie_cutter(self):
def sample_data():
return pd.DataFrame({
"chr": ["1", "2"],
"start": [0, 0],
"stop": [200, 99 * 3],
"strand": [-1, 1],
})
a = regions.GenomicRegions("sharum", sample_data, [],
get_genome_chr_length())
b = a.convert("cookie", regions.convert.cookie_cutter(100))
force_load(b.load())
run_pipegraph()
assert (b.df["start"] == [50, 98]).all()
assert (b.df["stop"] == [50 + 100, 98 + 100]).all()
assert (b.df["strand"] == [-1, 1]).all()
def test_liftover(self):
def sample_data():
return pd.DataFrame({
"chr": ["1", "1", "2"],
"start": [27897200, 27898600, 100000],
"stop": [27897300, 27898700, 100100],
})
a = regions.GenomicRegions("sharum", sample_data, [],
get_genome_chr_length())
b = a.convert("hg38", regions.convert.lift_over("hg19ToHg38"))
force_load(b.load())
run_pipegraph()
# made these with the ucsc web liftover utility
# http://genome.ucsc.edu/cgi-bin/hgLiftOver
assert (b.df["start"] == [27570689, 27572089, 100000]).all()
assert (b.df["stop"] == [27570789, 27572189, 100100]).all()
def test_overlap_genes_requires_two_genes(self):
genome = get_genome()
a = genes.Genes(genome)
def sample_data():
return pd.DataFrame({
"chr": ["Chromosome"],
"start": [1000],
"stop": [1100]
})
b = regions.GenomicRegions("sha", sample_data, [], genome)
force_load(a.load())
force_load(b.load())
run_pipegraph()
with pytest.raises(ValueError):
a.overlap_genes(b)
def test_raises_on_non_genome(self):
def sample_data():
return pd.DataFrame({
"chr": ["1", "2", "1"],
"start": [10, 100, 1000],
"stop": [12, 110, 1110],
})
def convert(df):
res = df[:]
res["start"] += 1
return res
genome = get_genome_chr_length()
a = regions.GenomicRegions("sharum", sample_data, [], genome)
a.convert("a+1", convert, genome)
with pytest.raises(ValueError):
a.convert("a+1b", convert, "hello")
def test_windows(self):
def sample_data():
return pd.DataFrame({
"chr": ["1", "2"],
"start": [0, 0],
"stop": [200, 99 * 3]
})
a = regions.GenomicRegions("sharum", sample_data, [],
get_genome_chr_length())
b = a.convert("ndiwo", regions.convert.windows(99, False))
c = a.convert("ndiwo2", regions.convert.windows(99, True))
force_load(b.load())
force_load(c.load())
run_pipegraph()
assert (b.df["start"] == [0, 99, 99 * 2, 0, 99, 99 * 2]).all()
assert (b.df["stop"] == [99, 99 * 2, 200, 99, 99 * 2, 99 * 3]).all()
assert (c.df["start"] == [0, 99, 0, 99, 99 * 2]).all()
assert (c.df["stop"] == [99, 99 * 2, 99, 99 * 2, 99 * 3]).all()
def test_liftover_filter_chr(self):
def sample_data():
return pd.DataFrame({
"chr": ["2", "1", "11_gl000202_random", "MT"],
"start": [100, 27897200, 500, 100000],
"stop": [10000, 27897300, 5000, 100100],
"copy": ["D", "A", "B", "C"],
"name": ["d", "a", "b", "c"],
})
a = regions.GenomicRegions(
"sharum",
sample_data,
[],
get_genome_chr_length({
"1": 100000,
"2": 100000,
"11_gl000202_random": 100000,
"MT": 100000,
"11": 1000000,
}),
)
b = a.convert(
"hg38",
regions.convert.lift_over("hg19ToHg38",
keep_name=True,
filter_to_these_chromosomes=["1"]),
)
force_load(b.load())
run_pipegraph()
# made these with the ucsc web liftover utility
# http://genome.ucsc.edu/cgi-bin/hgLiftOver
print(b.df)
assert (b.df["start"] == [27570689]).all()
assert (b.df["stop"] == [27570789]).all()
assert (b.df["copy"] == ["A"]).all()
assert (b.df["name"] == ["a"]).all()
assert (b.df["chr"] == ["1"]).all()
def test_merge_connected(self):
def sample_data():
return pd.DataFrame({
"chr": [
"1",
"1",
"1",
"1",
"1",
"2",
"3",
"3",
"3",
"4",
"4",
"4",
"5",
],
"start": [
10,
13,
110,
300,
400,
102,
5,
6,
6000,
10,
100,
200,
100,
],
"stop": [
18,
100,
200,
400,
410,
1000,
5000,
4900,
6010,
100,
150,
300,
110,
],
})
a = regions.GenomicRegions("sharum",
sample_data, [],
get_genome_chr_length(),
on_overlap="ignore")
b = a.convert("agrown", regions.convert.merge_connected())
force_load(b.load())
run_pipegraph()
assert (b.df["chr"] == ["1", "1", "1", "2", "3", "3", "4", "4",
"5"]).all()
assert (b.df["start"] == [10, 110, 300, 102, 5, 6000, 10, 200,
100]).all()
assert (b.df["stop"] == [
100, 200, 410, 1000, 5000, 6010, 150, 300, 110
]).all()
