def test_get_features_by_feature(frag3, frag6, region3, region6):
from pybedtools import BedTool
for f in [frag6]:
t = Track.load(f)
for r in [region3, region6]:
result = [len(x[1]) for x in t._get_features_by_feature(BedTool(r))]
assert [0, 1, 3] == sorted(result)
def tracks():
ftypes = ["bam", "bed", "wig", "bg", "bw", "wig.gz", "bg.gz", "bigWig", "bedGraph"]#, "bed.gz"]
my_tracks = []
for ftype in ftypes:
fname = "tests/data/profile." + ftype
my_tracks.append(Track.load(fname))
return my_tracks
def __init__(self, bamfile, height=1, color=None, bgmode=None, alpha=None, fragmentsize=200, rmdup=True,
rmrepeats=True, **kwargs):
self.height = height
self.track = Track.load(bamfile, fragmentsize=fragmentsize, rmdup=rmdup, rmrepeats=rmrepeats)
self.ymax = None
self.bgmode = bgmode
self.scalepm = kwargs.get("adjscale", False)
self.show_scale = kwargs.get("show_scale", True)
if color:
self.color = color
else:
self.color = "#a7004b"
if alpha:
self.alpha = alpha
else:
self.alpha = 1
self.fragmentsize = fragmentsize
self.rmdup = rmdup
self.rmrepeats = rmrepeats
self.name = kwargs.get('name')
def test_fetch_to_counts(frag3, frag6, region3, region6):
from pybedtools import BedTool
for f in [frag3, frag6]:
t = Track.load(f)
for r in [region3, region6]:
overlap = [x for x in t.fetch_to_counts(BedTool(r))]
assert 3 == len(overlap)
counts = sorted([len(x[1]) + len(x[2]) for x in overlap])
assert [0, 1, 3] == counts
def test_get_features_by_feature(frag3, frag6, region3, region6):
from pybedtools import BedTool
for f in [frag6]:
t = Track.load(f)
for r in [region3, region6]:
result = [
len(x[1]) for x in t._get_features_by_feature(BedTool(r))
]
assert [0, 1, 3] == sorted(result)
def test_fetch_to_counts(frag3, frag6, region3, region6):
from pybedtools import BedTool
for f in [frag3, frag6]:
t = Track.load(f)
for r in [region3, region6]:
overlap = [x for x in t.fetch_to_counts(BedTool(r))]
assert 3 == len(overlap)
counts = sorted([len(x[1]) + len(x[2]) for x in overlap])
assert [0, 1, 3] == counts
def tracks():
ftypes = [
"bam", "bed", "wig", "bg", "bw", "wig.gz", "bg.gz", "bigWig",
"bedGraph"
] #, "bed.gz"]
my_tracks = []
for ftype in ftypes:
fname = "tests/data/profile." + ftype
my_tracks.append(Track.load(fname))
return my_tracks
def load_heatmap_data(featurefile, datafile, bins=100, up=5000, down=5000, rmdup=True, rpkm=False, rmrepeats=True,fragmentsize=None, dynam=False, guard=None):
if guard is None:
guard = []
#try mode='w' to make py2 and py3 work
tmp = tempfile.NamedTemporaryFile(mode='w+', encoding='utf-8', delete=False, prefix="fluff")
regions = []
order = {}
count = 0
hashcounter = 0
if not guard and dynam:
filt = True
else:
filt = False
for i, line in enumerate(open(featurefile)):
if line.startswith("#") or line[:5] == "track":
hashcounter += 1
continue
vals = line.strip().split("\t")
strand = "+"
gene = ""
if len(vals) >= 6:
strand = vals[5]
if len(vals) >= 4:
gene = vals[3]
middle = int((int(vals[2]) + int(vals[1])) / 2)
start, end = middle, middle
if strand == "+":
start -= up
end += down
else:
start -= down
end += up
if filt:
if start >= 0:
guard.append(True)
else:
guard.append(False)
if not filt and start >= 0:
if not dynam or guard[i - hashcounter]:
regions.append([vals[0], start, end, gene, strand])
order["{0}:{1}-{2}".format(vals[0], start, end)] = count
count += 1
#add encode() to make py3 work
tmp.write("{0}\t{1}\t{2}\t{3}\t0\t{4}\n".format(vals[0], start, end, gene, strand))
tmp.flush()
track = Track.load(datafile,
rmdup=rmdup,
rmrepeats=rmrepeats,
fragmentsize=fragmentsize)
result = track.binned_stats(tmp.name, bins, split=True, rpkm=rpkm)
# Retrieve original order
r_data = np.array([[float(x) for x in row[3:]] for row in result])
return os.path.basename(datafile), regions, r_data, guard # [r_order]
def load_heatmap_data(featurefile, datafile, bins=100, up=5000, down=5000, rmdup=True, rpkm=False, rmrepeats=True,fragmentsize=None, dynam=False, guard=None):
if guard is None:
guard = []
tmp = tempfile.NamedTemporaryFile(delete=False, prefix="fluff")
regions = []
order = {}
count = 0
hashcounter = 0
if not guard and dynam:
filt = True
else:
filt = False
for i, line in enumerate(open(featurefile)):
if line.startswith("#") or line[:5] == "track":
hashcounter += 1
continue
vals = line.strip().split("\t")
strand = "+"
gene = ""
if len(vals) >= 6:
strand = vals[5]
if len(vals) >= 4:
gene = vals[3]
middle = (int(vals[2]) + int(vals[1])) / 2
start, end = middle, middle
if strand == "+":
start -= up
end += down
else:
start -= down
end += up
if filt:
if start >= 0:
guard.append(True)
else:
guard.append(False)
if not filt and start >= 0:
if not dynam or guard[i - hashcounter]:
regions.append([vals[0], start, end, gene, strand])
order["{0}:{1}-{2}".format(vals[0], start, end)] = count
count += 1
tmp.write("{0}\t{1}\t{2}\t{3}\t0\t{4}\n".format(vals[0], start, end, gene, strand))
tmp.flush()
track = Track.load(datafile,
rmdup=rmdup,
rmrepeats=rmrepeats,
fragmentsize=fragmentsize)
result = track.binned_stats(tmp.name, bins, split=True, rpkm=rpkm)
# Retrieve original order
r_data = np.array([[float(x) for x in row[3:]] for row in result])
return os.path.basename(datafile), regions, r_data, guard # [r_order]
def load_cluster_data(clust_file, datafiles, bins, rpkm, rmdup, rmrepeats, fragmentsize=None):
data = {}
for datafile in datafiles:
result = []
track = Track.load(datafile,
rmdup=rmdup,
rmrepeats=rmrepeats,
fragmentsize=fragmentsize)
result = track.binned_stats(clust_file,
bins,
split=True,
rpkm=rpkm
)
data[os.path.basename(datafile)] = dict(
[["{0}:{1}-{2}".format(vals[0], vals[1], vals[2]), [float(x) for x in vals[3:]]] for vals in result])
return data
def load_cluster_data(clust_file, datafiles, bins, rpkm, rmdup, rmrepeats, fragmentsize=None):
data = {}
for datafile in datafiles:
result = []
track = Track.load(datafile,
rmdup=rmdup,
rmrepeats=rmrepeats,
fragmentsize=fragmentsize)
result = track.binned_stats(clust_file,
bins,
split=True,
rpkm=rpkm
)
data[os.path.basename(datafile)] = dict(
[["{0}:{1}-{2}".format(vals[0], vals[1], vals[2]), [float(x) for x in vals[3:]]] for vals in result])
return data
def test_fragmentsize(region_fs, fragments):
track = Track.load(fragments)
result = track.binned_stats(region_fs, 4)
assert 1 == len(result)
counts = [int(x) for x in result[0].split("\t")[-4:]]
assert [1, 0, 0, 1] == counts
track.fragmentsize = 50
result = track.binned_stats(region_fs, 4)
counts = [int(x) for x in result[0].split("\t")[-4:]]
assert [1, 0, 0, 1] == counts
track.fragmentsize = 100
result = track.binned_stats(region_fs, 4)
counts = [int(x) for x in result[0].split("\t")[-4:]]
assert [1, 1, 1, 1] == counts
track.fragmentsize = 200
result = track.binned_stats(region_fs, 4)
counts = [int(x) for x in result[0].split("\t")[-4:]]
assert [2, 2, 2, 2] == counts
def test_fragmentsize(region_fs, fragments):
track = Track.load(fragments)
result = track.binned_stats(region_fs, 4)
assert 1 == len(result)
counts = [int(x) for x in result[0].split("\t")[-4:]]
assert [1, 0, 0, 1] == counts
track.fragmentsize = 50
result = track.binned_stats(region_fs, 4)
counts = [int(x) for x in result[0].split("\t")[-4:]]
assert [1, 0, 0, 1] == counts
track.fragmentsize = 100
result = track.binned_stats(region_fs, 4)
counts = [int(x) for x in result[0].split("\t")[-4:]]
assert [1, 1, 1, 1] == counts
track.fragmentsize = 200
result = track.binned_stats(region_fs, 4)
counts = [int(x) for x in result[0].split("\t")[-4:]]
assert [2, 2, 2, 2] == counts
def __init__(self,
bamfile,
height=1,
color=None,
bgmode=None,
alpha=None,
fragmentsize=200,
rmdup=True,
rmrepeats=True,
**kwargs):
self.height = height
self.track = Track.load(bamfile,
fragmentsize=fragmentsize,
rmdup=rmdup,
rmrepeats=rmrepeats)
self.ymax = None
self.bgmode = bgmode
self.scalepm = kwargs.get("adjscale", False)
self.show_scale = kwargs.get("show_scale", True)
if color:
self.color = color
else:
self.color = "#a7004b"
if alpha:
self.alpha = alpha
else:
self.alpha = 1
self.fragmentsize = fragmentsize
self.rmdup = rmdup
self.rmrepeats = rmrepeats
self.name = kwargs.get('name')
