Python pybedtools.Interval方法代碼示例

# 需要導入模塊: import pybedtools [as 別名]
# 或者: from pybedtools import Interval [as 別名]
def __getitem__(self, idx):
        """Returns (pybedtools.Interval, labels)
        """
        row = self.df.iloc[idx]

        # TODO: use kipoiseq.dataclasses.interval instead of pybedtools
        import pybedtools
        interval = pybedtools.create_interval_from_list(
            [to_scalar(x) for x in row.iloc[:self.bed_columns]])

        if self.ignore_targets or self.n_tasks == 0:
            labels = {}
        else:
            labels = row.iloc[self.bed_columns:].values.astype(
                self.label_dtype)
        return interval, labels 

# 需要導入模塊: import pybedtools [as 別名]
# 或者: from pybedtools import Interval [as 別名]
def merged_interval_features(feature, bam_handle,find_svtype=False):
    support_list = feature.name.split(",")
    locations = sorted(map(int, support_list[0:-1:3]))
    other_bp_ends = support_list[-1] if not find_svtype else ','.join(support_list[1::3])
    num_unique_locations = len(set(locations))
    count_str = ",".join(["%s,%s" % (i, c) for (i, c) in collections.Counter(locations).items()])
    plus_support = len([i for i in support_list[2::3] if i == "+"])
    minus_support = len(locations) - plus_support
    locations_span = max(locations) - min(locations)
    interval_readcount = bam_handle.count(reference=str(feature.chrom), start=feature.start, end=feature.end)
    info = {"SC_PLUS_SUPPORT":plus_support, "SC_MINUS_SUPPORT":minus_support, 
            "SC_LOCATIONS_SPAN":locations_span, "SC_NUM_UNIQUE_LOCATIONS":num_unique_locations,
            "SC_COUNT_STR": count_str, "SC_COVERAGE":interval_readcount, "SC_OTHER_BP_ENDS": other_bp_ends, 
            "SC_SC_BP_ENDS": "%s-%s"%(feature.start, feature.end)}
    name = "%s,%s,0,SC" % (
        base64.b64encode(json.dumps(info)), feature.fields[6].split(',')[0])

    return pybedtools.Interval(feature.chrom, feature.start, feature.end, name=name, score=feature.score,
                               otherfields=[str(interval_readcount)]+feature.fields[6:]) 

# 需要導入模塊: import pybedtools [as 別名]
# 或者: from pybedtools import Interval [as 別名]
def get_full_interval(feature, pad):
    name_fields = feature.name.split(",")
    info = json.loads(base64.b64decode(name_fields[0]))
    other_bp_ends=info["SC_OTHER_BP_ENDS"]
    start = feature.start
    end = feature.end
    sv_type = name_fields[1]
    if "-" in other_bp_ends:
        other_bp_start,other_bp_end=map(lambda x:int(x),other_bp_ends.split("-"))
        if other_bp_start != 0 or other_bp_end != 0:
            start = min((feature.start+feature.end)/2,(other_bp_start+other_bp_end)/2)
            end = max((feature.start+feature.end)/2,(other_bp_start+other_bp_end)/2)

    sv_len = 0 if sv_type == "INS" else max(end-start,0)
    info["SOURCES"] = "%s-%d-%s-%d-%d-SoftClip" % (feature.chrom, start, feature.chrom, end, sv_len)
    name = "%s,%s,%d,%s"%(base64.b64encode(json.dumps(info)),sv_type,sv_len,'SC')

    return pybedtools.Interval(feature.chrom, start, end, name=name, score=feature.score,
                                   otherfields=feature.fields[6:]) 

# 需要導入模塊: import pybedtools [as 別名]
# 或者: from pybedtools import Interval [as 別名]
def find_other_bp_interval(feature,pad):
    name_fields = feature.name.split(",")
    sv_type = name_fields[1]
    sv_methods = name_fields[3]
    sv_length = int(name_fields[2])
    info = json.loads(base64.b64decode(name_fields[0]))

    other_bps=map(lambda y: map(int,y['SC_OTHER_BP_ENDS'].split('-')),info["SC_SUBINTERVAL_INFOs"])
    start_interval=min(map(lambda x:x[0],other_bps))
    end_interval=max(map(lambda x:x[1],other_bps))
    soft_clip_location = (start_interval+end_interval)/2
    sc_bp=feature.start if abs(soft_clip_location-feature.start)>abs(soft_clip_location-feature.end) else feature.end
    other_bp_field="%d-%d"%(max(sc_bp-pad,0),sc_bp+pad)
    name="%d,%d,+,%s"%(soft_clip_location,sc_bp,other_bp_field)
    return pybedtools.Interval(feature.chrom, start_interval, end_interval, name=name, score="1",
                               otherfields=[sv_type]) 

# 需要導入模塊: import pybedtools [as 別名]
# 或者: from pybedtools import Interval [as 別名]
def find_idp(feature, wiggle):
    n = len(feature.fields) / 2
    if feature.chrom != feature.fields[n]:
        return None
    start_dup = feature.start
    end_dup = feature.end
    start_del = int(feature.fields[n + 1])
    end_del = int(feature.fields[n + 2])
    if abs(start_del - end_del) > (abs(start_dup - end_dup) - wiggle):
        return None
    dist_ends = [abs(start_del - start_dup), abs(end_del - end_dup)]
    if min(dist_ends) > wiggle:
        return None
    del_pos = start_del if dist_ends[0] > dist_ends[1] else end_del
    name = "%s,%s" % (feature.name, feature.fields[n + 3])
    score = "%s,%s" % (feature.score, feature.fields[n + 4])
    return pybedtools.Interval(feature.chrom, feature.start, feature.end,
                               name=name, score=score,
                               otherfields=["%d" % del_pos,
                                            "%d-%d" % (start_del, end_del)]) 

# 需要導入模塊: import pybedtools [as 別名]
# 或者: from pybedtools import Interval [as 別名]
def filter_itxs(feature):
    n = len(feature.fields) / 2
    del_interval_idp = map(int, feature.fields[7].split("-"))
    del_interval_itx_1 = map(int,
                             feature.fields[n + 7].split(",")[0].split("-"))
    del_interval_itx_2 = map(int,
                             feature.fields[n + 7].split(",")[1].split("-"))
    if filter(lambda x: abs(x[0] - del_interval_idp[0]) + abs(
                    x[1] - del_interval_idp[1]) == 0,
              [del_interval_itx_1, del_interval_itx_2]) and "LowQual" not in \
            feature.fields[n + 4]:
        return None
    return pybedtools.Interval(feature.chrom, feature.start, feature.end,
                               name=feature.name,
                               score=feature.score,
                               otherfields=feature.fields[6:n]) 

# 需要導入模塊: import pybedtools [as 別名]
# 或者: from pybedtools import Interval [as 別名]
def to_bed_interval(self, sample_name):
        if self.start <= 0:
            return None
        if self.sv_type not in ["DEL", "INS", "INV", "ITX", "CTX", "DUP"]: return None
        # if not self.sub_intervals and list(self.sources)[0] == "HaplotypeCaller": return None
        # if len(self.sources) == 1 and list(self.sources)[0] == "HaplotypeCaller": return None
        if self.sv_type == "INS":
            end = self.end + 1
        elif self.sv_type in ["ITX","CTX"] :
            end = self.start + 1
        else:
            end = self.end
        info = self.get_info()
        
        if self.sv_type in ["ITX", "CTX"]:
            info["POS2"] = self.end
            info["END"] = end
            info["CHR2"] = self.chrom2
            if not self.is_precise:
                info.update({"IMPRECISE": True})

        return pybedtools.Interval(self.chrom, self.start, end, name="%s,%s,%d,%s" % (
            base64.b64encode(json.dumps(info)), self.sv_type, self.length,
            ";".join(self._get_svmethods())),
            score=str(len(self.sources))) 

# 需要導入模塊: import pybedtools [as 別名]
# 或者: from pybedtools import Interval [as 別名]
def add_weighted_score(in_bed, score_bed):
    out_bed = in_bed.intersect(score_bed, wao=True).saveas(os.path.join(args.tmpdir, "score.bed"))

    bed_array = []
    last_interval = pybedtools.Interval("", 0, 0)
    map_value = 0.0
    for interval in out_bed:
        if interval.chrom != last_interval.chrom or interval.start != last_interval.start or interval.end != last_interval.end:
            if last_interval.chrom:
                bed_array.append(tuple(last_interval.fields[:-5]) + (str(map_value),))
            map_value = 0.0
            last_interval = interval
        if float(interval.fields[-1]) > 0:
            map_value += float(interval.fields[-1]) * float(interval.fields[-2]) / float(interval.length)

    if last_interval.chrom:
        bed_array.append(tuple(last_interval.fields[:-5]) + (str(map_value),))

    return pybedtools.BedTool(bed_array) 

# 需要導入模塊: import pybedtools [as 別名]
# 或者: from pybedtools import Interval [as 別名]
def soft_clips_at_breakpoint(read, region):
    """
    Returns True if the given pysam read maps up to the edge of the given
    pybedtools.Interval, ``region`` and soft clips at that edge.

    Two cases are possible:

    1. The end of the read soft clips such that the read's reference end stops
    at the breakpoint start and the end of the read is softclipped.

    2. The beginning of the read soft clips such that the read's reference start
    begins at the breakpoint end and the beginning of the read is softclipped.

    In both cases, the read should be mapped in its best location in the
    reference ("perfect mapping").
    """
    return (
        (read.reference_end == region.start and read.cigar[-1][0] == BAM_CSOFT_CLIP) or
        (read.reference_start == region.end + 1 and read.cigar[0][0] == BAM_CSOFT_CLIP)
    ) 

# 需要導入模塊: import pybedtools [as 別名]
# 或者: from pybedtools import Interval [as 別名]
def test_bed3(tmpdir):
    bed_file = write_tmp('chr1\t1\t2\nchr1\t1\t3', tmpdir)
    bt = BedDataset(bed_file)
    assert bt.n_tasks == 0
    assert len(bt) == 2
    assert np.all(bt.df[0] == 'chr1')
    assert bt[0] == (Interval("chr1", 1, 2), {})
    assert bt[1] == (Interval("chr1", 1, 3), {}) 

# 需要導入模塊: import pybedtools [as 別名]
# 或者: from pybedtools import Interval [as 別名]
def test_bed3_labels(tmpdir):
    bed_file = write_tmp('chr1\t1\t2\t1\t0\nchr1\t1\t3\t0\t1', tmpdir)
    bt = BedDataset(bed_file)
    assert np.all(bt.get_targets() == np.array([[1, 0],
                                                [0, 1]]))
    assert len(bt) == 2
    assert bt.n_tasks == 2
    assert np.all(bt.df[0] == 'chr1')
    assert bt[0][0] == Interval("chr1", 1, 2)
    assert np.all(bt[0][1] == np.array([1, 0]))

    assert bt[1][0] == Interval("chr1", 1, 3)
    assert np.all(bt[1][1] == np.array([0, 1]))
    assert len(bt) == 2 

# 需要導入模塊: import pybedtools [as 別名]
# 或者: from pybedtools import Interval [as 別名]
def test_incl_excl_chromosomes(tmpdir):
    bed_file = write_tmp(
        'chr1\t1\t2\t1\t0\nchr2\t1\t3\t0\t1\nchr3\t1\t3\t0\t1', tmpdir)
    bt = BedDataset(bed_file)
    assert len(bt) == 3

    bt = BedDataset(bed_file, incl_chromosomes=['chr1'])
    assert len(bt) == 1
    assert bt[0][0] == Interval("chr1", 1, 2)

    bt = BedDataset(bed_file, excl_chromosomes=['chr1'])
    assert len(bt) == 2
    assert bt[0][0] == Interval("chr2", 1, 3) 

# 需要導入模塊: import pybedtools [as 別名]
# 或者: from pybedtools import Interval [as 別名]
def test_tsvreader(tsv_file, num_chr, label_dtype):
    ds = BedDataset(tsv_file, label_dtype=label_dtype, num_chr=num_chr)
    interval, labels = ds[0]
    assert isinstance(interval, Interval)
    if not num_chr:
        assert interval.chrom.startswith("chr")
    assert isinstance(labels[0], label_dtype)
    assert interval.start == 2
    assert interval.end == 4 

# 需要導入模塊: import pybedtools [as 別名]
# 或者: from pybedtools import Interval [as 別名]
def from_pybedtools(cls, interval):
        """Create the ranges object from `pybedtools.Interval`

        # Arguments
            interval: `pybedtools.Interval` instance
        """
        return cls(chrom=interval.chrom,
                   start=interval.start,
                   end=interval.stop,
                   name=interval.name,
                   score=interval.score,
                   strand=interval.strand,
                   attrs=dict(interval.attrs or dict())
                   ) 

# 需要導入模塊: import pybedtools [as 別名]
# 或者: from pybedtools import Interval [as 別名]
def test_fasta_extractor_valid_intervals():
    extractor = FastaExtractor("tests/data/fasta_test.fa")
    intervals = [Interval("chr1", 0, 10), Interval("chr2", 0, 10)]
    expected_data = np.array(
        [
            [
                [1., 0., 0., 0.],
                [0., 1., 0., 0.],
                [0., 1., 0., 0.],
                [0., 0., 1., 0.],
                [0., 0., 0., 1.],
                [1., 0., 0., 0.],
                [0., 1., 0., 0.],
                [0., 1., 0., 0.],
                [0., 0., 1., 0.],
                [0., 0., 0., 1.],
            ],
            [
                [1., 0., 0., 0.],
                [0., 1., 0., 0.],
                [0., 0., 1., 0.],
                [0., 0., 0., 1.],
                [0.25, 0.25, 0.25, 0.25],
                [1., 0., 0., 0.],
                [0., 1., 0., 0.],
                [0., 0., 1., 0.],
                [0., 0., 0., 1.],
                [0.25, 0.25, 0.25, 0.25],
            ],
        ],
        dtype=np.float32,
    )
    data = extractor(intervals)
    assert (data == expected_data).all()