def open_trackfactory(parser, options):
tf = TrackFactory(options.file, "r+")
if tf.has_track(options.name):
tf.close()
parser.error("trackfactory '%s' already has track named '%s'" %
(options.file, options.name))
return tf
def view_track(parser, options):
tf = TrackFactory(options.file, "r")
if not tf.has_track(options.name):
tf.close()
parser.error("trackfactory '%s' does not contain track '%s'" %
(options.file, options.name))
region = parse_interval(options.region)
t = tf.get_track(options.name)
track_type = t.get_type()
logging.debug("opened track '%s' type '%s'" % (options.name, track_type))
if track_type == SequenceTrack.__name__:
print t[region]
if track_type == ArrayTrack.__name__:
if options.file_type == "bedgraph":
t.tobedgraph(region, sys.stdout)
else:
print t[region]
elif track_type == VectorTrack.__name__:
if options.file_type == "bedgraph":
readnum = options.readnum
allele = options.allele
t.tobedgraph(region, sys.stdout, norm=True,
read=readnum, allele=allele)
else:
print t[region]
elif track_type == RnaseqTrack.__name__:
cov_track = t.get_coverage_track()
print cov_track.density(region)
junc_track = t.get_junction_track()
print junc_track[region]
logging.debug("done")
tf.close()
def remove_track(parser, options):
tf = TrackFactory(options.file, "r+")
if not tf.has_track(options.name):
tf.close()
parser.error("trackfactory '%s' does not contain track '%s'" %
(options.file, options.name))
tf.delete_track(options.name)
tf.close()
logging.info("removed track '%s' from trackfactory '%s'" %
(options.name, options.file))
