def _draw_family(self, axes, family):
col_labels = [
"familyId",
"individualId",
"father",
"mother",
"sex",
"status",
"role",
"layout",
"generated",
"not_sequenced",
]
table_vals = []
for member in family:
table_vals.append([
member.family_id,
member.person_id,
member.dad_id,
member.mom_id,
Sex.from_name(member.sex),
member.status,
member.role,
member.layout,
"G" if member.generated else "",
"N" if member.not_sequenced else "",
])
axes.table = plt.table(cellText=table_vals,
colLabels=col_labels,
loc="center")
def _format_criterias(cls, standard_criterias):
"""
Replicates functionality from denovo gene set config parser.
Given a TOML config's standard criterias, it does additional formatting
which was done before in the parser.
"""
effect_type_criterias = []
for name, criteria in standard_criterias.effect_types.segments.items():
effect_type_criterias.append({
"property":
"effect_types",
"name":
name,
"value":
expand_effect_types(criteria),
})
sex_criterias = []
for name, criteria in standard_criterias.sexes.segments.items():
sex_criterias.append({
"property": "sexes",
"name": name,
"value": [Sex.from_name(criteria)],
})
return (effect_type_criterias, sex_criterias)
def test_sex_attribute():
assert Sex.from_value(1) == Sex.male
assert Sex.from_name("M") == Sex.male
assert Sex.from_name("male") == Sex.male
assert Sex.from_value(2) == Sex.female
assert Sex.from_name("F") == Sex.female
assert Sex.from_name("female") == Sex.female
assert Sex.from_value(0) == Sex.unspecified
assert Sex.from_name("U") == Sex.unspecified
assert Sex.from_name("unspecified") == Sex.unspecified
def read_in_sexes(stream):
length = int.from_bytes(stream.read(4), "big", signed=False)
out = []
for _i in range(0, length):
is_not_none = read_int8(stream)
if is_not_none:
out.append(Sex(read_int8(stream)))
else:
out.append(None)
return out
def redefine(self):
assert "person_id" in self._attributes
self.family_id = self._attributes["family_id"]
self.family = None
self.person_id = self._attributes["person_id"]
self.sample_id = self._attributes.get("sample_id", None)
self.index = self._attributes.get("index", None)
self._sex = Sex.from_name(self._attributes["sex"])
if "role" not in self._attributes:
self._role = None
else:
self._role = Role.from_name(self._attributes.get("role"))
self._status = Status.from_name(self._attributes["status"])
self._attributes["sex"] = self._sex
self._attributes["role"] = self._role
self._attributes["status"] = self._status
self.mom_id = self.get_attr("mom_id")
if self.mom_id == "0":
self.mom_id = None
self._attributes["mom_id"] = None
self.dad_id = self.get_attr("dad_id")
if self.dad_id == "0":
self.dad_id = None
self._attributes["dad_id"] = None
self.mom = None
self.dad = None
assert self.mom_id is None or type(self.mom_id) == str, \
(self, self._attributes)
assert self.dad_id is None or type(self.dad_id) == str, \
(self, self._attributes)
if self._attributes.get("not_sequenced"):
value = self._attributes.get("not_sequenced")
if value == "None" or value == "0" or value == "False":
self._attributes["not_sequenced"] = None
if self._attributes.get("generated"):
value = self._attributes.get("generated")
if value == "None" or value == "0" or value == "False":
self._attributes["generated"] = None
def _draw_members(self, axes, layout):
for level in layout.positions:
for individual in level:
if individual.individual.member.generated or \
individual.individual.member.not_sequenced:
individual_color = "grey"
elif individual.individual.member.status == Status.unaffected:
individual_color = "white"
elif individual.individual.member.status == Status.affected:
individual_color = "red"
else:
individual_color = "purple"
if Sex.from_name(individual.individual.member.sex) == Sex.male:
coords = [
individual.x + self._x_offset,
individual.y + self._y_offset,
]
axes.add_patch(
mpatches.Rectangle(
coords,
individual.size,
individual.size,
facecolor=individual_color,
edgecolor="black",
))
cx = coords[0] + individual.size / 2.0
cy = coords[1] + individual.size / 2.0
dlx = coords[0]
dly = coords[1]
elif (Sex.from_name(
individual.individual.member.sex) == Sex.female):
coords = [
individual.x_center + self._x_offset,
individual.y_center + self._y_offset,
]
axes.add_patch(
mpatches.Circle(
coords,
individual.size / 2,
facecolor=individual_color,
edgecolor="black",
))
cx = coords[0]
cy = coords[1]
dlx = coords[0] + (individual.size / 2.0) * math.cos(
math.radians(225))
dly = coords[1] + (individual.size / 2.0) * math.sin(
math.radians(225))
else:
size = math.sqrt((individual.size**2) / 2)
coords = [
individual.x + self._x_offset + (individual.size / 2),
individual.y + self._y_offset,
]
axes.add_patch(
mpatches.Rectangle(
coords,
size,
size,
facecolor=individual_color,
edgecolor="black",
angle=45.0,
))
cx = coords[0]
cy = coords[1] + individual.size / 2.0
dlx = coords[0] - individual.size / 4
dly = coords[1] + individual.size / 4
if individual.individual.member.role == Role.prb:
axes.add_patch(
mpatches.FancyArrow(
dlx - self._gap,
dly - self._gap,
self._gap,
self._gap,
length_includes_head=True,
color="black",
head_width=2.0,
linewidth=0.1,
))
if self.show_id:
axes.annotate(
individual.individual.member.person_id,
(cx, cy),
color="black",
weight="bold",
fontsize=2,
ha="center",
va="center",
)
def load_simple_families_file(infile, ped_sep="\t"):
fam_df = pd.read_csv(
infile,
sep=ped_sep,
index_col=False,
skipinitialspace=True,
converters={
"role": lambda r: Role.from_name(r),
"gender": lambda s: Sex.from_name(s),
"sex": lambda s: Sex.from_name(s),
},
dtype={
"familyId": str,
"personId": str
},
comment="#",
)
fam_df = fam_df.rename(columns={
"gender": "sex",
"personId": "person_id",
"familyId": "family_id",
"momId": "mom_id",
"dadId": "dad_id",
"sampleId": "sample_id",
}, )
fam_df["status"] = pd.Series(index=fam_df.index, data=1)
fam_df.loc[fam_df.role == Role.prb, "status"] = 2
fam_df["status"] = fam_df.status.apply(lambda s: Status.from_value(s))
fam_df["mom_id"] = pd.Series(index=fam_df.index, data="0")
fam_df["dad_id"] = pd.Series(index=fam_df.index, data="0")
if "sample_id" not in fam_df.columns:
sample_ids = pd.Series(data=fam_df["person_id"].values)
fam_df["sample_id"] = sample_ids
families = defaultdict(list)
for rec in fam_df.to_dict(orient="records"):
families[rec["family_id"]].append(rec)
result = defaultdict(list)
for fam_id, members in families.items():
mom_id = None
dad_id = None
children = []
for member in members:
role = member["role"]
if role == Role.mom:
mom_id = member["person_id"]
elif role == Role.dad:
dad_id = member["person_id"]
else:
assert role in set([Role.prb, Role.sib])
children.append(member)
for child in children:
child["mom_id"] = mom_id
child["dad_id"] = dad_id
result[fam_id] = [Person(**member) for member in members]
return FamiliesData.from_family_persons(result)
def sex_converter(a):
if not isinstance(a, Sex):
return Sex.from_name(a)
return a
def test_bad_sex_name():
with pytest.raises(ValueError):
Sex.from_name("gaga")
def test_bad_sex_value():
with pytest.raises(ValueError):
Sex.from_value(100)