def do_reduction(subset, args, nrfuzzykey, location):
seen = set()
for i in subset:
seen.add(i)
for j in subset[i]:
seen.add(j)
singles = []
for num in nrfuzzykey:
if num not in seen:
singles.append(num)
#if len(subset.keys()) == 0 and len(compatible.keys()) == 0: return
families = get_subset_evidence(subset, nrfuzzykey, args)
gpdlines = ""
tablelines = ""
for num in singles:
families.append(nrfuzzykey[num])
# find gpds not in the graph...
for fz in families:
info = fz.get_info_string()
gpdline = fz.get_genepred_line()
#print '&&&&&&&&&&&&&&&&'
#print gpdline
#print fz.get_info_string()
#print '&&&&&&&&&&&&&&&&'
gpd = GenePredEntry(gpdline)
if not gpd.is_valid():
sys.stderr.write("WARNING: invalid genepred entry generated\n" +
gpdline + "\n" + fz.get_info_string() + "\n")
gpd = sorted(
fz.gpds, key=lambda x: x.get_exon_count(),
reverse=True)[0] #just grab one that has all the exons
fz = FuzzyGenePred(gpd, juntol=args.junction_tolerance * 2)
gpdline = fz.get_genepred_line()
if not gpd.is_valid():
sys.stderr.write("WARNING: still problem skilling\n")
continue
gpdlines += gpdline + "\n"
if args.output_original_table:
name = gpd.entry['name']
for g in fz.gpds:
tablelines += name + "\t" + g.entry['name'] + "\n"
grng = gpd.get_bed()
grng.direction = None
if not location:
location = grng
location = location.merge(grng)
locstring = ''
if location: locstring = location.get_range_string()
return [gpdlines, tablelines, locstring]
def do_reduction(subset,args,nrfuzzykey,location):
seen = set()
for i in subset:
seen.add(i)
for j in subset[i]: seen.add(j)
singles = []
for num in nrfuzzykey:
if num not in seen:
singles.append(num)
#if len(subset.keys()) == 0 and len(compatible.keys()) == 0: return
families = get_subset_evidence(subset,nrfuzzykey,args)
gpdlines = ""
tablelines = ""
for num in singles:
families.append(nrfuzzykey[num])
# find gpds not in the graph...
for fz in families:
info = fz.get_info_string()
gpdline = fz.get_genepred_line()
#print '&&&&&&&&&&&&&&&&'
#print gpdline
#print fz.get_info_string()
#print '&&&&&&&&&&&&&&&&'
gpd = GenePredEntry(gpdline)
if not gpd.is_valid():
sys.stderr.write("WARNING: invalid genepred entry generated\n"+gpdline+"\n"+fz.get_info_string()+"\n")
gpd = sorted(fz.gpds, key=lambda x: x.get_exon_count(), reverse=True)[0] #just grab one that has all the exons
fz = FuzzyGenePred(gpd,juntol=args.junction_tolerance*2)
gpdline = fz.get_genepred_line()
if not gpd.is_valid():
sys.stderr.write("WARNING: still problem skilling\n")
continue
gpdlines += gpdline+"\n"
if args.output_original_table:
name = gpd.entry['name']
for g in fz.gpds:
tablelines+=name+"\t"+g.entry['name']+"\n"
grng = gpd.get_bed()
grng.direction = None
if not location:
location = grng
location = location.merge(grng)
locstring = ''
if location: locstring = location.get_range_string()
return [gpdlines, tablelines, locstring]
def evaluate_junctions(fz, sr, args):
cnt = 0
source_names = [x.entry['name'] for x in fz.gpds]
working = fz.copy()
if len(working.fuzzy_junctions) == 0: return []
for i in range(0, len(working.fuzzy_junctions)):
newjun = working.fuzzy_junctions[i]
newjun.left.get_payload()['junc'] = []
newjun.right.get_payload()['junc'] = []
oldjun = fz.fuzzy_junctions[i]
for srjun in sr:
sjun = sr[srjun]['fzjun']
if oldjun.overlaps(sjun, args.junction_tolerance):
for i in range(0, min(sr[srjun]['cnt'], args.downsample)):
newjun.left.get_payload()['junc'].append(
sjun.left.get_payload()['junc'][0])
newjun.right.get_payload()['junc'].append(
sjun.right.get_payload()['junc'][0])
cnt += 1
juncs = []
starts = []
ends = []
evidences = []
for i in range(0, len(fz.fuzzy_junctions)):
evidence = len(working.fuzzy_junctions[i].left.get_payload()['junc'])
if evidence >= args.required_evidence:
if i == 0:
starts.append(working.start.start)
elif working.fuzzy_junctions[i].left.get_payload()['start']:
starts.append(working.fuzzy_junctions[i].left.get_payload()
['start'].start)
else:
starts.append(working.fuzzy_junctions[i - 1].right.start)
#now ends
if i == len(fz.fuzzy_junctions) - 1:
ends.append(working.end.end)
elif working.fuzzy_junctions[i].right.get_payload()['end']:
ends.append(
working.fuzzy_junctions[i].right.get_payload()['end'].end)
else:
ends.append(working.fuzzy_junctions[i + 1].left.end)
bestleft = GenePredFuzzyBasics.mode(
working.fuzzy_junctions[i].left.get_payload()['junc'])
bestright = GenePredFuzzyBasics.mode(
working.fuzzy_junctions[i].right.get_payload()['junc'])
juncs.append([bestleft, bestright])
#print 'jun '+str(i)+' evid: '+str(evidence)+" "+str(bestleft)+" "+str(bestright)
else:
starts.append([])
ends.append([])
juncs.append([])
evidences.append(evidence)
#print juncs
#print starts
#print ends
#print evidences
# now we can put together the runs
runs = []
current_run = []
for i in range(0, len(evidences)):
if evidences[i] < args.required_evidence:
if len(current_run) > 0:
runs.append(current_run)
current_run = []
continue
current_run.append(i)
if len(current_run) > 0:
runs.append(current_run)
# now the runs are in runs
#print 'runs:'
parts = []
for run in runs:
sarr = []
sarr.append(starts[run[0]] - 1) #put back to zero index
earr = []
for i in range(0, len(run)):
sarr.append(juncs[run[i]][1] - 1)
earr.append(juncs[run[i]][0])
earr.append(ends[run[-1]])
# ready to build a genepred!
part = ''
part += str(working.start.chr) + "\t"
part += '+' + "\t"
part += str(sarr[0]) + "\t"
part += str(earr[-1]) + "\t"
part += str(sarr[0]) + "\t"
part += str(earr[-1]) + "\t"
part += str(len(sarr)) + "\t"
part += ','.join([str(x) for x in sarr]) + ',' + "\t"
part += ','.join([str(x) for x in earr]) + ','
# Final quality check here
gpd = GenePredEntry("test1\ttest1\t" + part)
if not gpd.is_valid():
sys.stderr.write("\nWARNING skipping invalid GPD\n" +
gpd.get_line() + "\n")
continue
parts.append([part, source_names])
#print parts
return parts
def evaluate_junctions(fz, sr, args):
cnt = 0
source_names = [x.entry["name"] for x in fz.gpds]
working = fz.copy()
if len(working.fuzzy_junctions) == 0:
return []
for i in range(0, len(working.fuzzy_junctions)):
newjun = working.fuzzy_junctions[i]
newjun.left.get_payload()["junc"] = []
newjun.right.get_payload()["junc"] = []
oldjun = fz.fuzzy_junctions[i]
for srjun in sr:
sjun = sr[srjun]["fzjun"]
if oldjun.overlaps(sjun, args.junction_tolerance):
for i in range(0, min(sr[srjun]["cnt"], args.downsample)):
newjun.left.get_payload()["junc"].append(sjun.left.get_payload()["junc"][0])
newjun.right.get_payload()["junc"].append(sjun.right.get_payload()["junc"][0])
cnt += 1
juncs = []
starts = []
ends = []
evidences = []
for i in range(0, len(fz.fuzzy_junctions)):
evidence = len(working.fuzzy_junctions[i].left.get_payload()["junc"])
if evidence >= args.required_evidence:
if i == 0:
starts.append(working.start.start)
elif working.fuzzy_junctions[i].left.get_payload()["start"]:
starts.append(working.fuzzy_junctions[i].left.get_payload()["start"].start)
else:
starts.append(working.fuzzy_junctions[i - 1].right.start)
# now ends
if i == len(fz.fuzzy_junctions) - 1:
ends.append(working.end.end)
elif working.fuzzy_junctions[i].right.get_payload()["end"]:
ends.append(working.fuzzy_junctions[i].right.get_payload()["end"].end)
else:
ends.append(working.fuzzy_junctions[i + 1].left.end)
bestleft = GenePredFuzzyBasics.mode(working.fuzzy_junctions[i].left.get_payload()["junc"])
bestright = GenePredFuzzyBasics.mode(working.fuzzy_junctions[i].right.get_payload()["junc"])
juncs.append([bestleft, bestright])
# print 'jun '+str(i)+' evid: '+str(evidence)+" "+str(bestleft)+" "+str(bestright)
else:
starts.append([])
ends.append([])
juncs.append([])
evidences.append(evidence)
# print juncs
# print starts
# print ends
# print evidences
# now we can put together the runs
runs = []
current_run = []
for i in range(0, len(evidences)):
if evidences[i] < args.required_evidence:
if len(current_run) > 0:
runs.append(current_run)
current_run = []
continue
current_run.append(i)
if len(current_run) > 0:
runs.append(current_run)
# now the runs are in runs
# print 'runs:'
parts = []
for run in runs:
sarr = []
sarr.append(starts[run[0]] - 1) # put back to zero index
earr = []
for i in range(0, len(run)):
sarr.append(juncs[run[i]][1] - 1)
earr.append(juncs[run[i]][0])
earr.append(ends[run[-1]])
# ready to build a genepred!
part = ""
part += str(working.start.chr) + "\t"
part += "+" + "\t"
part += str(sarr[0]) + "\t"
part += str(earr[-1]) + "\t"
part += str(sarr[0]) + "\t"
part += str(earr[-1]) + "\t"
part += str(len(sarr)) + "\t"
part += ",".join([str(x) for x in sarr]) + "," + "\t"
part += ",".join([str(x) for x in earr]) + ","
# Final quality check here
gpd = GenePredEntry("test1\ttest1\t" + part)
if not gpd.is_valid():
sys.stderr.write("\nWARNING skipping invalid GPD\n" + gpd.get_line() + "\n")
continue
parts.append([part, source_names])
# print parts
return parts
def do_prediction(compatible,args,nrfuzzykey,location):
#if len(compatible.keys()) == 0: return None
#all reads could be standing alone version
families = []
for num in nrfuzzykey:
families.append(nrfuzzykey[num])
nrfuzzykey[num].params['proper_set'] = False #partial overlap is enough
#get_compatible_evidence(compatible,nrfuzzykey,args)
for i in compatible:
for j in compatible[i]:
#see if its already in there
g1lines = set()
for g1 in nrfuzzykey[i].gpds: g1lines.add(g1.get_line())
repeat = False
for g2 in nrfuzzykey[j].gpds:
if g2.get_line() in g1lines:
repeat = True
break
if not repeat: continue
together = nrfuzzykey[i].concat_fuzzy_gpd(nrfuzzykey[j])
if together:
families.append(together)
# now we need to find any duplicate entries and combine them
newfam = []
beforefam = len(families)
while len(families) > 0:
fam = families.pop(0)
remaining = []
for i in range(0,len(families)):
if fam.is_equal_fuzzy(families[i]):
added = fam.add_fuzzy_gpd(families[i])
if not added:
sys.stderr.write("WARNING NOT SURE WHY NOT ADDED EQUAL\n")
fam = added
else: remaining.append(families[i])
families = remaining
newfam.append(fam)
families = newfam
afterfam = len(families)
# Replace the family with a set where we haven't used the same gpd line twice
# This may damage the fuzzy object
for i in range(0,len(families)):
gset = set()
for g in families[i].gpds:
gset.add(g.get_line())
families[i].gpds = [GenePredEntry(x) for x in gset]
# sys.stderr.write("\n\ncahnged from "+str(beforefam)+"\t"+str(afterfam)+"\n\n")
gpdlines = ""
tablelines = ""
# find gpds not in the graph...
for fz in families:
info = fz.get_info_string()
gpdline = fz.get_genepred_line()
#print '&&&&&&&&&&&&&&&&'
#print gpdline
#print fz.get_info_string()
#print '&&&&&&&&&&&&&&&&'
gpd = GenePredEntry(gpdline)
if not gpd.is_valid():
sys.stderr.write("WARNING: invalid genepred entry generated\n"+gpdline+"\n"+fz.get_info_string()+"\n")
gpd = sorted(fz.gpds, key=lambda x: x.get_exon_count(), reverse=True)[0] #just grab one that has all the exons
fz = FuzzyGenePred(gpd,juntol=args.junction_tolerance*2)
gpdline = fz.get_genepred_line()
if not gpd.is_valid():
sys.stderr.write("WARNING: still problem skilling\n")
continue
gpdlines += gpdline+"\n"
if args.output_original_table:
name = gpd.entry['name']
for g in fz.gpds:
tablelines+=name+"\t"+g.entry['name']+"\n"
grng = gpd.get_bed()
grng.direction = None
if not location:
location = grng
location = location.merge(grng)
locstring = ''
if location: locstring = location.get_range_string()
return [gpdlines, tablelines, locstring]
def do_prediction(compatible, args, nrfuzzykey, location):
#if len(compatible.keys()) == 0: return None
#all reads could be standing alone version
families = []
for num in nrfuzzykey:
families.append(nrfuzzykey[num])
nrfuzzykey[num].params[
'proper_set'] = False #partial overlap is enough
#get_compatible_evidence(compatible,nrfuzzykey,args)
for i in compatible:
for j in compatible[i]:
#see if its already in there
g1lines = set()
for g1 in nrfuzzykey[i].gpds:
g1lines.add(g1.get_line())
repeat = False
for g2 in nrfuzzykey[j].gpds:
if g2.get_line() in g1lines:
repeat = True
break
if not repeat: continue
together = nrfuzzykey[i].concat_fuzzy_gpd(nrfuzzykey[j])
if together:
families.append(together)
# now we need to find any duplicate entries and combine them
newfam = []
beforefam = len(families)
while len(families) > 0:
fam = families.pop(0)
remaining = []
for i in range(0, len(families)):
if fam.is_equal_fuzzy(families[i]):
added = fam.add_fuzzy_gpd(families[i])
if not added:
sys.stderr.write("WARNING NOT SURE WHY NOT ADDED EQUAL\n")
fam = added
else:
remaining.append(families[i])
families = remaining
newfam.append(fam)
families = newfam
afterfam = len(families)
# Replace the family with a set where we haven't used the same gpd line twice
# This may damage the fuzzy object
for i in range(0, len(families)):
gset = set()
for g in families[i].gpds:
gset.add(g.get_line())
families[i].gpds = [GenePredEntry(x) for x in gset]
# sys.stderr.write("\n\ncahnged from "+str(beforefam)+"\t"+str(afterfam)+"\n\n")
gpdlines = ""
tablelines = ""
# find gpds not in the graph...
for fz in families:
info = fz.get_info_string()
gpdline = fz.get_genepred_line()
#print '&&&&&&&&&&&&&&&&'
#print gpdline
#print fz.get_info_string()
#print '&&&&&&&&&&&&&&&&'
gpd = GenePredEntry(gpdline)
if not gpd.is_valid():
sys.stderr.write("WARNING: invalid genepred entry generated\n" +
gpdline + "\n" + fz.get_info_string() + "\n")
gpd = sorted(
fz.gpds, key=lambda x: x.get_exon_count(),
reverse=True)[0] #just grab one that has all the exons
fz = FuzzyGenePred(gpd, juntol=args.junction_tolerance * 2)
gpdline = fz.get_genepred_line()
if not gpd.is_valid():
sys.stderr.write("WARNING: still problem skilling\n")
continue
gpdlines += gpdline + "\n"
if args.output_original_table:
name = gpd.entry['name']
for g in fz.gpds:
tablelines += name + "\t" + g.entry['name'] + "\n"
grng = gpd.get_bed()
grng.direction = None
if not location:
location = grng
location = location.merge(grng)
locstring = ''
if location: locstring = location.get_range_string()
return [gpdlines, tablelines, locstring]
