def set_seqfeature(self):
"""
Create a SeqFeature object with which to populate the
`seqfeature` attribute.
:return:
"""
# SeqFeature coordinates are 0-based half-open
start, stop = basic.reformat_coordinates(self.start, self.stop,
self.coordinate_format,
"0_half_open")
# SeqFeature orientation is (-1, 1) instead of ("R", "F")
strand = basic.reformat_strand(self.orientation, "numeric")
# Standard genes will have start < stop
if self.start <= self.stop:
self.seqfeature = SeqFeature(FeatureLocation(start, stop),
strand=strand,
type=self.type)
# Wrap-around genes will have stop < start
else:
self.seqfeature = SeqFeature(CompoundLocation([
FeatureLocation(start, self.genome_length),
FeatureLocation(0, stop)
]),
strand=strand,
type=self.type)
# Add feature qualifiers
self.seqfeature.qualifiers = self.get_qualifiers()
def set_orientation(self, value, fmt, capitalize=False):
"""
Set the orientation based on the indicated format.
:param value: orientation value
:type value: int or str
:param fmt: how orientation should be formatted
:type fmt: str
:param capitalize: whether to capitalize the first letter of
orientation
:type capitalize: bool
:return:
"""
self.orientation = basic.reformat_strand(value, fmt, capitalize)
def get_begin_end(self):
"""
Accesses feature coordinates in transcription begin-end format.
:return: (begin, end)
"""
# Get a copy of the orientation in fr_long format:
orientation = basic.reformat_strand(self.orientation, "fr_long")
if orientation == "forward":
# Rightward transcribed gene
begin, end = self.start, self.stop
elif orientation == "reverse":
# Leftward transcribed gene
begin, end = self.stop, self.start
else:
# Unexpected orientation
begin = end = -1
return begin, end # tuple format is implicit
def check_feature_coordinates(self,
use_cds=False,
use_trna=False,
use_tmrna=False,
other=None,
strand=False,
eval_id=None,
success="correct",
fail="error",
eval_def=None):
"""Identify nested, duplicated, or partially-duplicated
features.
:param use_cds:
Indicates whether ids for CDS features should be generated.
:type use_cds: bool
:param use_trna:
Indicates whether ids for tRNA features should be generated.
:type use_trna: bool
:param use_tmrna:
Indicates whether ids for tmRNA features should be generated.
:type use_tmrna: bool
:param other: List of features that should be included.
:type other: list
:param strand: Indicates if feature orientation should be included.
:type strand: bool
:param eval_id: same as for check_attribute().
:param success: same as for check_attribute().
:param fail: same as for check_attribute().
:param eval_def: same as for check_attribute().
"""
unsorted_feature_lists = []
unsorted_features = []
ftr_types = set()
if use_cds:
ftr_types.add("cds")
unsorted_features.extend(self.cds_features)
if use_trna:
ftr_types.add("trna")
unsorted_features.extend(self.trna_features)
if use_tmrna:
ftr_types.add("tmrna")
unsorted_features.extend(self.tmrna_features)
if other is not None:
ftr_types.add("other")
unsorted_features.extend(other)
if strand:
s_info = "were"
unsorted_f_features = [] # Forward orientation
unsorted_r_features = [] # Reverse orientation
for index in range(len(unsorted_features)):
feature = unsorted_features[index]
strand = basic.reformat_strand(feature.orientation,
format="fr_short")
if strand == "f":
unsorted_f_features.append(feature)
else:
unsorted_r_features.append(feature)
unsorted_feature_lists.append(unsorted_f_features)
unsorted_feature_lists.append(unsorted_r_features)
else:
s_info = "were not"
unsorted_feature_lists.append(unsorted_features)
ft_string = basic.join_strings(ftr_types, delimiter=", ")
result = (
f"The following types of features were evaluated: {ft_string}. "
f"Features {ft_string} separately grouped "
"by orientation for evaluation. ")
msgs = ["There are one or more errors with the feature coordinates."]
for unsorted_features in unsorted_feature_lists:
sorted_features = sorted(unsorted_features,
key=attrgetter("start", "stop"))
index = 0
while index < len(sorted_features) - 1:
current = sorted_features[index]
next = sorted_features[index + 1]
ftrs = (f"Feature1 ID: {current.id}, "
f"start coordinate: {current.start}, "
f"stop coordinate: {current.stop}, "
f"orientation: {current.orientation}. "
f"Feature2 ID: {next.id}, "
f"start coordinate: {next.start}, "
f"stop coordinate: {next.stop}, "
f"orientation: {next.orientation}. ")
if (current.start == next.start and current.stop == next.stop):
msgs.append(ftrs)
msgs.append("Feature1 and Feature2 contain identical "
"start and stop coordinates.")
# To identify nested features, the following tests
# avoid false errors due to genes that may wrap around the
# genome.
elif (current.start < next.start and current.start < next.stop
and current.stop > next.start
and current.stop > next.stop):
msgs.append(ftrs)
msgs.append("Feature2 is nested within Feature1.")
elif (current.start == next.start and basic.reformat_strand(
current.orientation, format="fr_short") == "r"
and basic.reformat_strand(next.orientation,
format="fr_short") == "r"):
msgs.append(ftrs)
msgs.append(("Feature1 and Feature2 contain "
"identical stop coordinates."))
elif (current.stop == next.stop and basic.reformat_strand(
current.orientation, format="fr_short") == "f"
and basic.reformat_strand(next.orientation,
format="fr_short") == "f"):
msgs.append(ftrs)
msgs.append(("Feature1 and Feature2 contain "
"identical stop coordinates."))
else:
pass
index += 1
if len(msgs) > 1:
result = result + " ".join(msgs)
status = fail
else:
result = result + "The feature coordinates are correct."
status = success
definition = ("Check if there are any feature coordinate conflicts.")
definition = basic.join_strings([definition, eval_def])
self.set_eval(eval_id, definition, result, status)
