def setUp(self):
iv = IntervalNode(Interval(50, 59))
for i in range(0, 110, 10):
if i == 50: continue
f = Interval(i, i + 9)
iv = iv.insert(f)
self.intervals = iv
def test_max_dist(self):
iv = self.intervals
r = iv.right(Interval(1, 1), max_dist=0, n=10)
self.assertEqual(len(r), 0)
for n, d in enumerate(range(10, 1000, 10)):
r = iv.right(Interval(1, 1), max_dist=d, n=10000)
self.assertEqual(len(r), n + 1)
def test_count(self):
iv = self.intervals
r = iv.right(Interval(1, 1), n=33)
self.assertEqual(len(r), 33)
l = iv.left(Interval(1, 1), n=33)
self.assertEqual(len(l), 1)
def setUp(self):
iv = IntervalNode(Interval(1, 2))
self.max = 1000000
for i in range(0, self.max, 10):
f = Interval(i, i)
iv = iv.insert(f)
for i in range(6000):
iv = iv.insert(Interval(0, 1))
self.intervals = iv
def test_left(self):
iv = self.intervals
self.assertEqual(str(iv.left(Interval(60, 70), n=2)),
str([Interval(50, 59),
Interval(40, 49)]))
for i in range(10, 100, 10):
f = Interval(i, i)
r = iv.left(f, max_dist=10, n=1)
self.assertEqual(r[0].end, i - 1)
def test_n(self):
iv = self.intervals
for i in range(0, 90, 10):
f = Interval(i + 1, i + 1)
r = iv.right(f, max_dist=20, n=2)
self.assertEqual(r[0].start, i + 10)
self.assertEqual(r[1].start, i + 20)
def test_right(self):
iv = self.intervals
self.assertEqual(str(iv.left(Interval(60, 70), n=2)),
str([Interval(50, 59),
Interval(40, 49)]))
def get_right_start(b10):
r = iv.right(Interval(b10, b10 + 1), n=1)
assert len(r) == 1
return r[0].start
for i in range(10, 100, 10):
self.assertEqual(get_right_start(i), i + 10)
for i in range(0, 100, 10):
f = Interval(i - 1, i - 1)
r = iv.right(f, max_dist=10, n=1)
self.assertEqual(r[0].start, i)
def test_tree_pickle(self):
a = IntervalTree()
for ichr in range(5):
for i in range(10, 100, 6):
f = Interval(i - 4, i + 4)
a.insert(f)
a.dump('a.pkl')
b = IntervalTree()
b.load('a.pkl')
for ichr in range(5):
for i in range(10, 100, 6):
f = Interval(i - 4, i + 4)
af = sorted(a.find(f), key=operator.attrgetter('start'))
bf = sorted(b.find(f), key=operator.attrgetter('start'))
assert len(bf) > 0
self.assertEqual(len(af), len(bf))
self.assertEqual(af[0].start, bf[0].start)
self.assertEqual(af[-1].start, bf[-1].start)
def annotation(self,
annotation_type,
start=None,
end=None) -> typing.List[Annotation]:
try:
if end is None or start is None:
anno_iter = self._annotations.find(Interval(0, self.end))
else:
anno_iter = filter(
lambda x: x.data.overlaps(Span(start, end)),
self._annotations.find(Interval(start, end)))
except:
return []
if annotation_type:
annotation_type = annotation_type.lower()
return sorted([
x.data for x in anno_iter
if x.data.annotation_type.lower() == annotation_type
and x.data != self
])
return sorted([x.data for x in anno_iter if x.data != self])
def parse_ribotricer_index(ribotricer_index):
"""
Parse ribotricer index to get only 'annotated'
features.
Parameters
----------
ribotricer_index: str
Path to the index file generated by ribotricer prepare_orfs
Returns
-------
annotated: List[ORF]
ORFs of CDS annotated
novel: List[ORF]
list of non-annotated ORFs
refseq: defaultdict(IntervalTree)
chrom: (start, end, strand)
"""
annotated = []
refseq = defaultdict(IntervalTree)
# First count the number of
# annotated regions to count.
# The annotated regions appear first in the index file
# so need to read only upto a point where the regions
# no longer have the annotated tag.
total_lines = 0
with open(ribotricer_index, "r") as anno:
# read header
anno.readline()
while "annotated" in anno.readline():
total_lines += 1
with open(ribotricer_index, "r") as anno:
with tqdm(total=total_lines, unit="lines", leave=False) as pbar:
# read header
anno.readline()
line = anno.readline()
while "annotated" in line:
pbar.update()
orf = ORF.from_string(line)
if orf is not None and orf.category == "annotated":
refseq[orf.chrom].insert(
Interval(
orf.intervals[0].start,
orf.intervals[-1].end,
STRAND_TO_NUM[orf.strand],
))
annotated.append(orf)
line = anno.readline()
return (annotated, refseq)
def setUp(self):
intervals = []
for i in range(11, 20000, 15):
for zz in range(random.randint(2, 5)):
m = random.randint(1, 10)
p = random.randint(1, 10)
intervals.append(Interval(i - m, i + p))
iv = IntervalNode(intervals[0])
for f in intervals[1:]:
iv = iv.insert(f)
self.intervals = intervals
self.tree = iv
def create_annotation(self,
type: str,
start: int,
end: int,
attributes=None) -> Annotation:
if attributes is None:
attributes = []
annotation = Annotation(self, start, end, type, attributes,
self._next_id)
self._next_id += 1
self._annotations.insert(
Interval(annotation.start, annotation.end, annotation))
self._aid_dict[annotation.annotation_id] = annotation
return annotation
def setUp(self):
tpath = os.path.dirname(__file__)
self.fa = os.path.join(tpath, 'test.fa')
self.fai = os.path.join(tpath, 'test.fa.fai')
self.gff3_1 = os.path.join(tpath, 'test_1.gff3')
self.gff3_2 = os.path.join(tpath, 'test_2.gff3')
self.A = np.array([[1, 1, 0, 0], [1, 1, 1, 1], [0, 1, 1, 0]])
self.i5 = (Interval(0, 10), Interval(5, 15))
self.i0 = (Interval(0, 10), Interval(10, 15))
self.i3 = (Interval(0, 9), Interval(0, 3))
def test_left(self):
max_dist = 200
n = 15
iv = self.tree
for i in range(11, 20000, 25):
for zz in range(random.randint(2, 5)):
s1 = random.randint(i + 1, i + 20)
f = Interval(s1, s1)
bf = brute_force_find_left(self.intervals, f, max_dist, n)
tf = iv.left(f, max_dist=max_dist, n=n)
if len(tf) == 0:
assert len(bf) == 0, bf
continue
mdist = max(distance(f, t) for t in tf)
self.assertTrue(set(bf).issuperset(tf))
diff = set(bf).difference(tf)
self.assertTrue(len(diff) == 0, (diff))
def infer_protocol(bam, gene_interval_tree, prefix, n_reads=20000):
"""Infer strandedness protocol given a bam file
Parameters
----------
bam: str
Path to bam file
gene_interval_tree: defaultdict(IntervalTree)
chrom: (start, end, strand)
prefix: str
Prefix for protocol file
n_reads: int
Number of reads to use (downsampled)
Returns
-------
protocol: string
forward/reverse
The strategy to do this is simple: keep a track
of mapped reads and their strand and then tally
if the location of their mapping has a gene defined
on the positive strand or the negative strand.
If the first and second characters denote the mapping and
gene strand respectively:
Higher proportion of (++, --) implies forward protocol
Higher proportion of (+-, -+) implies reverse protocol
Equal proportion of the above two scenairos implies unstranded protocol.
"""
iteration = 0
bam = pysam.AlignmentFile(bam, "rb")
strandedness = Counter()
for read in bam.fetch(until_eof=True):
if iteration <= n_reads:
if is_read_uniq_mapping(read):
if read.is_reverse:
mapped_strand = "-"
else:
mapped_strand = "+"
mapped_start = read.reference_start
mapped_end = read.reference_end
chrom = read.reference_name
# get corresponding gene's strand
interval = list(
set(gene_interval_tree[chrom].find(
Interval(mapped_start, mapped_end))))
if len(interval) == 1:
# Filter out genes with ambiguous strand info
# (those) that have a tx_start on opposite strands
gene_strand = NUM_TO_STRAND[interval[0].data]
# count table for mapped strand vs gene strand
strandedness["{}{}".format(mapped_strand,
gene_strand)] += 1
iteration += 1
# Add pseudocounts
strandedness["++"] += 1
strandedness["--"] += 1
strandedness["+-"] += 1
strandedness["-+"] += 1
total = sum(strandedness.values())
forward_mapped_reads = strandedness["++"] + strandedness["--"]
reverse_mapped_reads = strandedness["-+"] + strandedness["+-"]
to_write = (
"In total {} reads checked:\n"
'\tNumber of reads explained by "++, --": {} ({:.4f})\n'
'\tNumber of reads explained by "+-, -+": {} ({:.4f})\n').format(
total,
forward_mapped_reads,
forward_mapped_reads / total,
reverse_mapped_reads,
reverse_mapped_reads / total,
)
with open("{}_protocol.txt".format(prefix), "w") as output:
output.write(to_write)
protocol = "forward"
if reverse_mapped_reads > forward_mapped_reads:
protocol = "reverse"
return protocol
def test_find(self):
self.tree.find(Interval(46, 47))
def get_right_start(b10):
r = iv.right(Interval(b10, b10 + 1), n=1)
assert len(r) == 1
return r[0].start
def test_feature_pickle(self):
f = Interval(22, 38, data={'a': 22})
g = loads(dumps(f))
self.assertEqual(f.start, g.start)
self.assertEqual(g.data['a'], 22)
def test_left(self):
self.tree.left(Interval(46, 47))
def test_toomany(self):
iv = self.intervals
self.assertEqual(len(iv.left(Interval(60, 70), n=200)), 6)
def test_right(self):
self.tree.right(Interval(46, 47))
def test_left(self):
self.assertEqual(2, len(self.tree4.left(Interval(44, 55))))
self.assertEqual(0, len(self.tree4.left(Interval(11, 12))))
def setUp(self):
self.tree4 = IntervalTree()
self.tree4.insert(Interval(22, 33, data='example1'))
self.tree4.insert(Interval(22, 33, data='example2'))
