def generate_read_to_contig_map(rawread_dir=rawread_dir,
pread_dir=pread_dir,
asm_dir=asm_dir):
read_map_dir = os.path.abspath(os.path.join(asm_dir, "read_maps"))
make_dirs(read_map_dir)
PypeMPWorkflow.setNumThreadAllowed(12, 12)
wf = PypeMPWorkflow()
rawread_db = makePypeLocalFile(os.path.join(rawread_dir, "raw_reads.db"))
rawread_id_file = makePypeLocalFile(
os.path.join(rawread_dir, "raw_read_ids"))
@PypeTask(inputs={"rawread_db": rawread_db},
outputs={"rawread_id_file": rawread_id_file},
TaskType=PypeThreadTaskBase,
URL="task://localhost/dump_rawread_ids")
def dump_rawread_ids(self):
rawread_db = fn(self.rawread_db)
rawread_id_file = fn(self.rawread_id_file)
os.system("DBshow -n %s | tr -d '>' | awk '{print $1}' > %s" %
(rawread_db, rawread_id_file))
wf.addTask(dump_rawread_ids)
pread_db = makePypeLocalFile(os.path.join(pread_dir, "preads.db"))
pread_id_file = makePypeLocalFile(os.path.join(pread_dir, "pread_ids"))
@PypeTask(inputs={"pread_db": pread_db},
outputs={"pread_id_file": pread_id_file},
TaskType=PypeThreadTaskBase,
URL="task://localhost/dump_pread_ids")
def dump_pread_ids(self):
pread_db = fn(self.pread_db)
pread_id_file = fn(self.pread_id_file)
os.system("DBshow -n %s | tr -d '>' | awk '{print $1}' > %s" %
(pread_db, pread_id_file))
wf.addTask(dump_pread_ids)
all_raw_las_files = {}
for las_fn in glob.glob(os.path.join(rawread_dir, "raw_reads.*.las")):
idx = las_fn.split("/")[
-1] # well, we will use regex someday to parse to get the number
idx = int(idx.split(".")[1])
las_file = makePypeLocalFile(las_fn)
all_raw_las_files["r_las_%s" % idx] = las_file
all_pread_las_files = {}
for las_fn in glob.glob(os.path.join(pread_dir, "preads.*.las")):
idx = las_fn.split("/")[
-1] # well, we will use regex someday to parse to get the number
idx = int(idx.split(".")[1])
las_file = makePypeLocalFile(las_fn)
all_pread_las_files["p_las_%s" % idx] = las_file
wf.refreshTargets() # block
sg_edges_list = makePypeLocalFile(os.path.join(asm_dir, "sg_edges_list"))
utg_data = makePypeLocalFile(os.path.join(asm_dir, "utg_data"))
ctg_paths = makePypeLocalFile(os.path.join(asm_dir, "ctg_paths"))
inputs = {
"rawread_id_file": rawread_id_file,
"pread_id_file": pread_id_file,
"sg_edges_list": sg_edges_list,
"utg_data": utg_data,
"ctg_paths": ctg_paths
}
read_to_contig_map = makePypeLocalFile(
os.path.join(read_map_dir, "read_to_contig_map"))
@PypeTask(inputs=inputs,
outputs={"read_to_contig_map": read_to_contig_map},
TaskType=PypeThreadTaskBase,
URL="task://localhost/get_ctg_read_map")
def generate_read_to_ctg_map(self):
rawread_id_file = fn(self.rawread_id_file)
pread_id_file = fn(self.pread_id_file)
read_to_contig_map = fn(self.read_to_contig_map)
pread_did_to_rid = open(pread_id_file).read().split("\n")
rid_to_oid = open(rawread_id_file).read().split("\n")
asm_G = AsmGraph(fn(self.sg_edges_list), fn(self.utg_data),
fn(self.ctg_paths))
pread_to_contigs = {}
with open(read_to_contig_map, "w") as f:
for ctg in asm_G.ctg_data:
if ctg[-1] == "R":
continue
ctg_g = asm_G.get_sg_for_ctg(ctg)
for n in ctg_g.nodes():
pid = int(n.split(":")[0])
rid = pread_did_to_rid[pid].split("/")[1]
rid = int(int(rid) / 10)
oid = rid_to_oid[rid]
k = (pid, rid, oid)
pread_to_contigs.setdefault(k, set())
pread_to_contigs[k].add(ctg)
for k in pread_to_contigs:
pid, rid, oid = k
for ctg in list(pread_to_contigs[k]):
print >> f, "%09d %09d %s %s" % (pid, rid, oid, ctg)
wf.addTask(generate_read_to_ctg_map)
def dump_rawread_to_ctg(self):
rawread_db = fn(self.rawread_db)
rawread_id_file = fn(self.rawread_id_file)
#pread_id_file = fn( self.pread_id_file )
las_file = fn(self.las_file)
rawread_to_contig_file = fn(self.rawread_to_contig_file)
read_to_contig_map = fn(self.read_to_contig_map)
rid_to_oid = open(rawread_id_file).read().split("\n")
#pread_did_to_rid = open(pread_id_file).read().split("\n")
ovlp_data = []
ovlp_count = 0
longest_ovlp = 0
a_id = None
rid_to_contigs = {}
with open(read_to_contig_map) as f:
for row in f:
row = row.strip().split()
pid, rid, oid, ctg = row
rid = int(rid)
rid_to_contigs.setdefault(rid, (oid, set()))
rid_to_contigs[rid][1].add(ctg)
with open(rawread_to_contig_file, "w") as f:
ovlp_data = {}
cur_read_id = None
for row in sp.check_output(
shlex.split("LA4Falcon -m %s %s " %
(rawread_db, las_file))).splitlines():
row = row.strip().split()
t_id = int(row[1])
q_id = int(row[0])
if q_id != cur_read_id:
if cur_read_id == None:
cur_read_id = q_id
else:
if len(ovlp_data) == 0:
o_id = rid_to_oid[cur_read_id]
print >> f, "%09d %s %s %d %d %d %d" % (
cur_read_id, o_id, "NA", 0, 0, 0, 0)
else:
ovlp_v = ovlp_data.values()
ovlp_v.sort()
rank = 0
for score, count, q_id_, o_id, ctg, in_ctg in ovlp_v:
print >> f, "%09d %s %s %d %d %d %d" % (
q_id_, o_id, ctg, count, rank, score,
in_ctg)
rank += 1
ovlp_data = {}
cur_read_id = q_id
if q_id in rid_to_contigs and len(
ovlp_data) == 0: #if the query is in some contig....
t_o_id, ctgs = rid_to_contigs[q_id]
o_id = rid_to_oid[q_id]
for ctg in list(ctgs):
ovlp_data.setdefault(ctg, [0, 0, q_id, o_id, ctg, 1])
ovlp_data[ctg][0] = -int(row[7])
ovlp_data[ctg][1] += 1
if t_id not in rid_to_contigs:
continue
t_o_id, ctgs = rid_to_contigs[t_id]
o_id = rid_to_oid[q_id]
for ctg in list(ctgs):
ovlp_data.setdefault(ctg, [0, 0, q_id, o_id, ctg, 0])
ovlp_data[ctg][0] += int(row[2])
ovlp_data[ctg][1] += 1
if len(ovlp_data) != 0:
ovlp_v = ovlp_data.values()
ovlp_v.sort()
rank = 0
for score, count, q_id_, o_id, ctg, in_ctg in ovlp_v:
print >> f, "%09d %s %s %d %d %d %d" % (
q_id_, o_id, ctg, count, rank, score, in_ctg)
rank += 1
def dump_pread_to_ctg(self):
pread_db = fn(self.pread_db)
rawread_id_file = fn(self.rawread_id_file)
pread_id_file = fn(self.pread_id_file)
read_to_contig_map = fn(self.read_to_contig_map)
las_file = fn(self.las_file)
pread_to_contig_file = fn(self.pread_to_contig_file)
read_to_contig_map = fn(self.read_to_contig_map)
pid_to_rid = open(pread_id_file).read().split("\n")
rid_to_oid = open(rawread_id_file).read().split("\n")
ovlp_data = []
ovlp_count = 0
longest_ovlp = 0
a_id = None
pid_to_contigs = {}
with open(read_to_contig_map) as f:
for row in f:
row = row.strip().split()
pid, rid, oid, ctg = row
pid = int(pid)
pid_to_contigs.setdefault(pid, (oid, set()))
pid_to_contigs[pid][1].add(ctg)
with open(pread_to_contig_file, "w") as f:
ovlp_data = {}
cur_read_id = None
skip_rest = 0
for row in sp.check_output(
shlex.split("LA4Falcon -mo %s %s " %
(pread_db, las_file))).splitlines():
row = row.strip().split()
t_id = int(row[1])
q_id = int(row[0])
if q_id != cur_read_id:
if cur_read_id == None:
cur_read_id = q_id
else:
if len(ovlp_data) == 0:
rid = pid_to_rid[cur_read_id].split("/")[1]
rid = int(int(rid) / 10)
o_id = rid_to_oid[rid]
print >> f, "%09d %s %s %d %d %d %d" % (
cur_read_id, o_id, "NA", 0, 0, 0, 0)
else:
ovlp_v = ovlp_data.values()
ovlp_v.sort()
rank = 0
for score, count, q_id_, o_id, ctg, in_ctg in ovlp_v:
print >> f, "%09d %s %s %d %d %d %d" % (
q_id_, o_id, ctg, count, rank, score,
in_ctg)
rank += 1
ovlp_data = {}
cur_read_id = q_id
skip_rest = 0
if q_id in pid_to_contigs and len(
ovlp_data) == 0: #if the query is in some contig....
t_o_id, ctgs = pid_to_contigs[q_id]
rid = pid_to_rid[q_id].split("/")[1]
rid = int(int(rid) / 10)
o_id = rid_to_oid[rid]
for ctg in list(ctgs):
ovlp_data.setdefault(ctg, [0, 0, q_id, o_id, ctg, 1])
ovlp_data[ctg][0] = -int(row[7])
ovlp_data[ctg][1] += 1
skip_rest = 1
if skip_rest == 1:
continue
if t_id not in pid_to_contigs:
continue
t_o_id, ctgs = pid_to_contigs[t_id]
rid = pid_to_rid[q_id].split("/")[1]
rid = int(int(rid) / 10)
o_id = rid_to_oid[rid]
for ctg in list(ctgs):
ovlp_data.setdefault(ctg, [0, 0, q_id, o_id, ctg, 0])
ovlp_data[ctg][0] += int(row[2])
ovlp_data[ctg][1] += 1
if len(ovlp_data) != 0:
ovlp_v = ovlp_data.values()
ovlp_v.sort()
rank = 0
for score, count, q_id_, o_id, ctg, in_ctg in ovlp_v:
print >> f, "%09d %s %s %d %d %d %d" % (
q_id_, o_id, ctg, count, rank, score, in_ctg)
rank += 1
for las_key, las_file in all_raw_las_files.items():
las_fn = fn(las_file)
idx = las_fn.split("/")[
-1] # well, we will use regex someday to parse to get the number
idx = int(idx.split(".")[1])
rawread_to_contig_file = makePypeLocalFile(
os.path.join(read_map_dir, "rawread_to_contigs.%s" % idx))
make_dump_rawread_to_ctg = PypeTask(
inputs={
"las_file": las_file,
"rawread_db": rawread_db,
"read_to_contig_map": read_to_contig_map,
"rawread_id_file": rawread_id_file,
"pread_id_file": pread_id_file
},
outputs={"rawread_to_contig_file": rawread_to_contig_file},
TaskType=PypeThreadTaskBase,
URL="task://localhost/r_read_to_contigs.%s" % idx)
dump_rawread_to_ctg_task = make_dump_rawread_to_ctg(
dump_rawread_to_ctg)
wf.addTask(dump_rawread_to_ctg_task)
for las_key, las_file in all_pread_las_files.items():
las_fn = fn(las_file)
idx = las_fn.split("/")[
-1] # well, we will use regex someday to parse to get the number
idx = int(idx.split(".")[1])
pread_to_contig_file = makePypeLocalFile(
os.path.join(read_map_dir, "pread_to_contigs.%s" % idx))
make_dump_pread_to_ctg = PypeTask(
inputs={
"las_file": las_file,
"pread_db": pread_db,
"read_to_contig_map": read_to_contig_map,
"rawread_id_file": rawread_id_file,
"pread_id_file": pread_id_file
},
outputs={"pread_to_contig_file": pread_to_contig_file},
TaskType=PypeThreadTaskBase,
URL="task://localhost/pread_to_contigs.%s" % idx)
dump_pread_to_ctg_task = make_dump_pread_to_ctg(dump_pread_to_ctg)
wf.addTask(dump_pread_to_ctg_task)
wf.refreshTargets() # block
def testDistributed(runmode, cleanup):
logger.info("test start")
baseDir = "."
import random
random.seed(1984)
#PypeThreadWorkflow.setNumThreadAllowed(20,20)
#wf = PypeThreadWorkflow()
PypeMPWorkflow.setNumThreadAllowed(20,20)
wf = PypeMPWorkflow()
allTasks = []
for layer in range(5):
fN = random.randint(3,7)
fin = [None] * fN
fout = [None] * fN
fmut = [None] * fN
for w in range(fN):
fin[w] = makePypeLocalFile(baseDir + "/testdata/testfile_l%d_w%d.dat" % (layer, w) )
fout[w] = makePypeLocalFile(baseDir + "/testdata/testfile_l%d_w%d.dat" % (layer+1, w) )
fmut[w] = makePypeLocalFile(baseDir + "/testdata/m_testfile_l%d_w%d.dat" % (layer+1, w) )
#wf.addObjects([fin[w], fout[w], fmut[w]])
for w in range(fN):
inputDataObjs = {}
outputDataObjs = {}
mutableDataObjs = {}
for i in range(5):
inputDataObjs["infile%d" % i] = random.choice(fin)
i = 0
for obj in random.sample(fmut,2):
#mutableDataObjs["outfile%d" % i] = obj
i += 1
outputDataObjs["outfile%d" % i] = fout[w]
shellCmd = "sleep 1\n" + "\n".join([ "echo %d %d ... >> %s" % (layer, w, of.localFileName) for of in outputDataObjs.values() ]) + "\nsleep 10"
shellCmd += "sleep 1\n" + "\n".join([ "echo %d %d ... >> %s" % (layer, w, of.localFileName) for of in mutableDataObjs.values() ]) + "\nsleep 10"
shellFileName = baseDir + "/testdata/task_l%d_w%d.sh" % (layer, w)
shfile = open(shellFileName, 'w')
print(shellCmd, file=shfile)
shfile.close()
if runmode == "internal":
def t1(self):
runShellCmd(["sleep", "%d" % random.randint(0,20) ])
for of in self.outputDataObjs.values():
runShellCmd(["touch", of.localFileName])
task = PypeTask(inputDataObjs = inputDataObjs,
outputDataObjs = outputDataObjs,
mutableDataObjs = mutableDataObjs,
URL="task://internal/task_l%d_w%d" % (layer, w),
TaskType=PypeThreadTaskBase) ( t1 )
elif runmode == "localshell":
task = PypeShellTask(inputDataObjs = inputDataObjs,
outputDataObjs = outputDataObjs,
mutableDataObjs = mutableDataObjs,
URL="task://localshell/task_l%d_w%d" % (layer, w),
TaskType=PypeThreadTaskBase) ( "%s" % shellFileName )
elif runmode == "sge":
task = PypeSGETask(inputDataObjs = inputDataObjs,
outputDataObjs = outputDataObjs,
mutableDataObjs = mutableDataObjs,
URL="task://sge/task_l%d_w%d" % (layer, w),
TaskType=PypeThreadTaskBase) ( "%s" % shellFileName )
elif runmode == "mixed":
#distributed = random.choice( (False, True) )
distributed = True if w % 3 == 0 else False
task = PypeDistributibleTask(inputDataObjs = inputDataObjs,
outputDataObjs = outputDataObjs,
mutableDataObjs = mutableDataObjs,
URL="task://sge/task_l%d_w%d" % (layer, w),
distributed=distributed,
TaskType=PypeThreadTaskBase) ( "%s" % shellFileName )
wf.addTasks([task])
allTasks.append(task)
for URL in wf._pypeObjects:
prereqJobURLs = [str(u) for u in wf._RDFGraph.transitive_objects(URIRef(URL), pypeNS["prereq"])
if isinstance(wf._pypeObjects[str(u)], PypeLocalFile) and str(u) != URL ]
if len(prereqJobURLs) == 0:
if cleanup == "1":
os.system("echo start > %s" % wf._pypeObjects[URL].localFileName)
pass
wf.refreshTargets(allTasks)
dotFile = open("test.dot","w")
#print >>dotFile, wf.graphvizShortNameDot
print(wf.graphvizDot, file=dotFile)
dotFile.close()
dotFile = open("test_short_name.dot","w")
print(wf.graphvizShortNameDot, file=dotFile)
dotFile.close()
rdfFile = open("test.rdf","w")
print(wf.RDFXML, file=rdfFile)
rdfFile.close()
if runmode != "internal":
mkFile = open("test.mk","w")
print(wf.makeFileStr, file=mkFile)
mkFile.close()
wf.addTask( dump_rawread_ids )
pread_db = makePypeLocalFile( os.path.join( pread_dir, "preads.db" ) )
pread_id_file = makePypeLocalFile( os.path.join( pread_dir, "pread_ids" ) )
@PypeTask( inputs = {"pread_db": pread_db},
outputs = {"pread_id_file": pread_id_file},
TaskType = PypeThreadTaskBase,
URL = "task://localhost/dump_pread_ids" )
def dump_pread_ids(self):
pread_db = fn( self.pread_db )
pread_id_file = fn( self.pread_id_file )
os.system("DBshow -n %s | tr -d '>' | awk '{print $1}' > %s" % (pread_db, pread_id_file) )
wf.addTask( dump_pread_ids )
wf.refreshTargets() # block
all_raw_las_files = {}
for las_fn in glob.glob( os.path.join( rawread_dir, "m*/raw_reads.*.las") ):
idx = las_fn.split("/")[-1] # well, we will use regex someday to parse to get the number
idx = int(idx.split(".")[1])
las_file = makePypeLocalFile( las_fn )
all_raw_las_files["r_las_%s" % idx] = las_file
all_pread_las_files = {}
for las_fn in glob.glob( os.path.join( pread_dir, "m*/preads.*.las") ):
idx = las_fn.split("/")[-1] # well, we will use regex someday to parse to get the number
idx = int(idx.split(".")[1])
las_file = makePypeLocalFile( las_fn )
all_pread_las_files["p_las_%s" % idx] = las_file
def generate_read_to_contig_map(rawread_dir=rawread_dir, pread_dir=pread_dir, asm_dir=asm_dir):
read_map_dir = os.path.abspath(os.path.join(asm_dir, "read_maps"))
make_dirs(read_map_dir)
PypeMPWorkflow.setNumThreadAllowed(12, 12)
wf = PypeMPWorkflow()
rawread_db = makePypeLocalFile(os.path.join(rawread_dir, "raw_reads.db"))
rawread_id_file = makePypeLocalFile(os.path.join(rawread_dir, "raw_read_ids"))
@PypeTask(
inputs={"rawread_db": rawread_db},
outputs={"rawread_id_file": rawread_id_file},
TaskType=PypeThreadTaskBase,
URL="task://localhost/dump_rawread_ids",
)
def dump_rawread_ids(self):
rawread_db = fn(self.rawread_db)
rawread_id_file = fn(self.rawread_id_file)
os.system("DBshow -n %s | tr -d '>' | awk '{print $1}' > %s" % (rawread_db, rawread_id_file))
wf.addTask(dump_rawread_ids)
pread_db = makePypeLocalFile(os.path.join(pread_dir, "preads.db"))
pread_id_file = makePypeLocalFile(os.path.join(pread_dir, "pread_ids"))
@PypeTask(
inputs={"pread_db": pread_db},
outputs={"pread_id_file": pread_id_file},
TaskType=PypeThreadTaskBase,
URL="task://localhost/dump_pread_ids",
)
def dump_pread_ids(self):
pread_db = fn(self.pread_db)
pread_id_file = fn(self.pread_id_file)
os.system("DBshow -n %s | tr -d '>' | awk '{print $1}' > %s" % (pread_db, pread_id_file))
wf.addTask(dump_pread_ids)
all_raw_las_files = {}
for las_fn in glob.glob(os.path.join(rawread_dir, "raw_reads.*.las")):
idx = las_fn.split("/")[-1] # well, we will use regex someday to parse to get the number
idx = int(idx.split(".")[1])
las_file = makePypeLocalFile(las_fn)
all_raw_las_files["r_las_%s" % idx] = las_file
all_pread_las_files = {}
for las_fn in glob.glob(os.path.join(pread_dir, "preads.*.las")):
idx = las_fn.split("/")[-1] # well, we will use regex someday to parse to get the number
idx = int(idx.split(".")[1])
las_file = makePypeLocalFile(las_fn)
all_pread_las_files["p_las_%s" % idx] = las_file
wf.refreshTargets() # block
sg_edges_list = makePypeLocalFile(os.path.join(asm_dir, "sg_edges_list"))
utg_data = makePypeLocalFile(os.path.join(asm_dir, "utg_data"))
ctg_paths = makePypeLocalFile(os.path.join(asm_dir, "ctg_paths"))
inputs = {
"rawread_id_file": rawread_id_file,
"pread_id_file": pread_id_file,
"sg_edges_list": sg_edges_list,
"utg_data": utg_data,
"ctg_paths": ctg_paths,
}
read_to_contig_map = makePypeLocalFile(os.path.join(read_map_dir, "read_to_contig_map"))
@PypeTask(
inputs=inputs,
outputs={"read_to_contig_map": read_to_contig_map},
TaskType=PypeThreadTaskBase,
URL="task://localhost/get_ctg_read_map",
)
def generate_read_to_ctg_map(self):
rawread_id_file = fn(self.rawread_id_file)
pread_id_file = fn(self.pread_id_file)
read_to_contig_map = fn(self.read_to_contig_map)
pread_did_to_rid = open(pread_id_file).read().split("\n")
rid_to_oid = open(rawread_id_file).read().split("\n")
asm_G = AsmGraph(fn(self.sg_edges_list), fn(self.utg_data), fn(self.ctg_paths))
pread_to_contigs = {}
with open(read_to_contig_map, "w") as f:
for ctg in asm_G.ctg_data:
if ctg[-1] == "R":
continue
ctg_g = asm_G.get_sg_for_ctg(ctg)
for n in ctg_g.nodes():
pid = int(n.split(":")[0])
rid = pread_did_to_rid[pid].split("/")[1]
rid = int(int(rid) / 10)
oid = rid_to_oid[rid]
k = (pid, rid, oid)
pread_to_contigs.setdefault(k, set())
pread_to_contigs[k].add(ctg)
for k in pread_to_contigs:
pid, rid, oid = k
for ctg in list(pread_to_contigs[k]):
print >> f, "%09d %09d %s %s" % (pid, rid, oid, ctg)
wf.addTask(generate_read_to_ctg_map)
def dump_rawread_to_ctg(self):
rawread_db = fn(self.rawread_db)
rawread_id_file = fn(self.rawread_id_file)
# pread_id_file = fn( self.pread_id_file )
las_file = fn(self.las_file)
rawread_to_contig_file = fn(self.rawread_to_contig_file)
read_to_contig_map = fn(self.read_to_contig_map)
rid_to_oid = open(rawread_id_file).read().split("\n")
# pread_did_to_rid = open(pread_id_file).read().split("\n")
ovlp_data = []
ovlp_count = 0
longest_ovlp = 0
a_id = None
rid_to_contigs = {}
with open(read_to_contig_map) as f:
for row in f:
row = row.strip().split()
pid, rid, oid, ctg = row
rid = int(rid)
rid_to_contigs.setdefault(rid, (oid, set()))
rid_to_contigs[rid][1].add(ctg)
with open(rawread_to_contig_file, "w") as f:
ovlp_data = {}
cur_read_id = None
for row in sp.check_output(shlex.split("LA4Falcon -m %s %s " % (rawread_db, las_file))).splitlines():
row = row.strip().split()
t_id = int(row[1])
q_id = int(row[0])
if q_id != cur_read_id:
if cur_read_id == None:
cur_read_id = q_id
else:
if len(ovlp_data) == 0:
o_id = rid_to_oid[cur_read_id]
print >> f, "%09d %s %s %d %d %d %d" % (cur_read_id, o_id, "NA", 0, 0, 0, 0)
else:
ovlp_v = ovlp_data.values()
ovlp_v.sort()
rank = 0
for score, count, q_id_, o_id, ctg, in_ctg in ovlp_v:
print >> f, "%09d %s %s %d %d %d %d" % (q_id_, o_id, ctg, count, rank, score, in_ctg)
rank += 1
ovlp_data = {}
cur_read_id = q_id
if q_id in rid_to_contigs and len(ovlp_data) == 0: # if the query is in some contig....
t_o_id, ctgs = rid_to_contigs[q_id]
o_id = rid_to_oid[q_id]
for ctg in list(ctgs):
ovlp_data.setdefault(ctg, [0, 0, q_id, o_id, ctg, 1])
ovlp_data[ctg][0] = -int(row[7])
ovlp_data[ctg][1] += 1
if t_id not in rid_to_contigs:
continue
t_o_id, ctgs = rid_to_contigs[t_id]
o_id = rid_to_oid[q_id]
for ctg in list(ctgs):
ovlp_data.setdefault(ctg, [0, 0, q_id, o_id, ctg, 0])
ovlp_data[ctg][0] += int(row[2])
ovlp_data[ctg][1] += 1
if len(ovlp_data) != 0:
ovlp_v = ovlp_data.values()
ovlp_v.sort()
rank = 0
for score, count, q_id_, o_id, ctg, in_ctg in ovlp_v:
print >> f, "%09d %s %s %d %d %d %d" % (q_id_, o_id, ctg, count, rank, score, in_ctg)
rank += 1
def dump_pread_to_ctg(self):
pread_db = fn(self.pread_db)
rawread_id_file = fn(self.rawread_id_file)
pread_id_file = fn(self.pread_id_file)
read_to_contig_map = fn(self.read_to_contig_map)
las_file = fn(self.las_file)
pread_to_contig_file = fn(self.pread_to_contig_file)
read_to_contig_map = fn(self.read_to_contig_map)
pid_to_rid = open(pread_id_file).read().split("\n")
rid_to_oid = open(rawread_id_file).read().split("\n")
ovlp_data = []
ovlp_count = 0
longest_ovlp = 0
a_id = None
pid_to_contigs = {}
with open(read_to_contig_map) as f:
for row in f:
row = row.strip().split()
pid, rid, oid, ctg = row
pid = int(pid)
pid_to_contigs.setdefault(pid, (oid, set()))
pid_to_contigs[pid][1].add(ctg)
with open(pread_to_contig_file, "w") as f:
ovlp_data = {}
cur_read_id = None
skip_rest = 0
for row in sp.check_output(shlex.split("LA4Falcon -mo %s %s " % (pread_db, las_file))).splitlines():
row = row.strip().split()
t_id = int(row[1])
q_id = int(row[0])
if q_id != cur_read_id:
if cur_read_id == None:
cur_read_id = q_id
else:
if len(ovlp_data) == 0:
rid = pid_to_rid[cur_read_id].split("/")[1]
rid = int(int(rid) / 10)
o_id = rid_to_oid[rid]
print >> f, "%09d %s %s %d %d %d %d" % (cur_read_id, o_id, "NA", 0, 0, 0, 0)
else:
ovlp_v = ovlp_data.values()
ovlp_v.sort()
rank = 0
for score, count, q_id_, o_id, ctg, in_ctg in ovlp_v:
print >> f, "%09d %s %s %d %d %d %d" % (q_id_, o_id, ctg, count, rank, score, in_ctg)
rank += 1
ovlp_data = {}
cur_read_id = q_id
skip_rest = 0
if q_id in pid_to_contigs and len(ovlp_data) == 0: # if the query is in some contig....
t_o_id, ctgs = pid_to_contigs[q_id]
rid = pid_to_rid[q_id].split("/")[1]
rid = int(int(rid) / 10)
o_id = rid_to_oid[rid]
for ctg in list(ctgs):
ovlp_data.setdefault(ctg, [0, 0, q_id, o_id, ctg, 1])
ovlp_data[ctg][0] = -int(row[7])
ovlp_data[ctg][1] += 1
skip_rest = 1
if skip_rest == 1:
continue
if t_id not in pid_to_contigs:
continue
t_o_id, ctgs = pid_to_contigs[t_id]
rid = pid_to_rid[q_id].split("/")[1]
rid = int(int(rid) / 10)
o_id = rid_to_oid[rid]
for ctg in list(ctgs):
ovlp_data.setdefault(ctg, [0, 0, q_id, o_id, ctg, 0])
ovlp_data[ctg][0] += int(row[2])
ovlp_data[ctg][1] += 1
if len(ovlp_data) != 0:
ovlp_v = ovlp_data.values()
ovlp_v.sort()
rank = 0
for score, count, q_id_, o_id, ctg, in_ctg in ovlp_v:
print >> f, "%09d %s %s %d %d %d %d" % (q_id_, o_id, ctg, count, rank, score, in_ctg)
rank += 1
for las_key, las_file in all_raw_las_files.items():
las_fn = fn(las_file)
idx = las_fn.split("/")[-1] # well, we will use regex someday to parse to get the number
idx = int(idx.split(".")[1])
rawread_to_contig_file = makePypeLocalFile(os.path.join(read_map_dir, "rawread_to_contigs.%s" % idx))
make_dump_rawread_to_ctg = PypeTask(
inputs={
"las_file": las_file,
"rawread_db": rawread_db,
"read_to_contig_map": read_to_contig_map,
"rawread_id_file": rawread_id_file,
"pread_id_file": pread_id_file,
},
outputs={"rawread_to_contig_file": rawread_to_contig_file},
TaskType=PypeThreadTaskBase,
URL="task://localhost/r_read_to_contigs.%s" % idx,
)
dump_rawread_to_ctg_task = make_dump_rawread_to_ctg(dump_rawread_to_ctg)
wf.addTask(dump_rawread_to_ctg_task)
for las_key, las_file in all_pread_las_files.items():
las_fn = fn(las_file)
idx = las_fn.split("/")[-1] # well, we will use regex someday to parse to get the number
idx = int(idx.split(".")[1])
pread_to_contig_file = makePypeLocalFile(os.path.join(read_map_dir, "pread_to_contigs.%s" % idx))
make_dump_pread_to_ctg = PypeTask(
inputs={
"las_file": las_file,
"pread_db": pread_db,
"read_to_contig_map": read_to_contig_map,
"rawread_id_file": rawread_id_file,
"pread_id_file": pread_id_file,
},
outputs={"pread_to_contig_file": pread_to_contig_file},
TaskType=PypeThreadTaskBase,
URL="task://localhost/pread_to_contigs.%s" % idx,
)
dump_pread_to_ctg_task = make_dump_pread_to_ctg(dump_pread_to_ctg)
wf.addTask(dump_pread_to_ctg_task)
wf.refreshTargets() # block
@PypeTask(
inputs={"pread_db": pread_db},
outputs={"pread_id_file": pread_id_file},
TaskType=PypeThreadTaskBase,
URL="task://localhost/dump_pread_ids",
)
def dump_pread_ids(self):
pread_db = fn(self.pread_db)
pread_id_file = fn(self.pread_id_file)
os.system("DBshow -n %s | tr -d '>' | awk '{print $1}' > %s" % (pread_db, pread_id_file))
wf.addTask(dump_pread_ids)
wf.refreshTargets() # block
all_raw_las_files = {}
for las_fn in glob.glob(os.path.join(rawread_dir, "raw_reads.*.las")):
idx = las_fn.split("/")[-1] # well, we will use regex someday to parse to get the number
idx = int(idx.split(".")[1])
las_file = makePypeLocalFile(las_fn)
all_raw_las_files["r_las_%s" % idx] = las_file
all_pread_las_files = {}
for las_fn in glob.glob(os.path.join(pread_dir, "preads.*.las")):
idx = las_fn.split("/")[-1] # well, we will use regex someday to parse to get the number
idx = int(idx.split(".")[1])
las_file = makePypeLocalFile(las_fn)
all_pread_las_files["p_las_%s" % idx] = las_file
def get_read_hctg_map(rawread_dir, pread_dir, asm_dir, hasm_dir):
PypeMPWorkflow.setNumThreadAllowed(12, 12)
wf = PypeMPWorkflow()
rawread_id_file = makePypeLocalFile(
os.path.join(asm_dir, "read_maps/raw_read_ids"))
pread_id_file = makePypeLocalFile(
os.path.join(asm_dir, "read_maps/pread_ids"))
h_ctg_edges = makePypeLocalFile(os.path.join(hasm_dir, "all_h_ctg_edges"))
p_ctg_edges = makePypeLocalFile(os.path.join(hasm_dir, "all_p_ctg_edges"))
h_ctg_ids = makePypeLocalFile(os.path.join(hasm_dir, "all_h_ctg_ids"))
read_map_dir = os.path.join(hasm_dir, "read_maps")
make_dirs(read_map_dir)
read_to_contig_map = makePypeLocalFile(
os.path.join(read_map_dir, "read_to_contig_map"))
inputs = {
"rawread_id_file": rawread_id_file,
"pread_id_file": pread_id_file,
"h_ctg_edges": h_ctg_edges,
"p_ctg_edges": p_ctg_edges,
"h_ctg_ids": h_ctg_ids
}
@PypeTask(inputs=inputs,
outputs={"read_to_contig_map": read_to_contig_map},
TaskType=PypeThreadTaskBase,
URL="task://localhost/get_ctg_read_map")
def generate_read_to_hctg_map(self):
rawread_id_file = fn(self.rawread_id_file)
pread_id_file = fn(self.pread_id_file)
read_to_contig_map = fn(self.read_to_contig_map)
pread_did_to_rid = open(pread_id_file).read().split("\n")
rid_to_oid = open(rawread_id_file).read().split("\n")
h_ctg_edges = fn(self.h_ctg_edges)
p_ctg_edges = fn(self.p_ctg_edges)
h_ctg_ids = set()
with open(fn(self.h_ctg_ids)) as f:
for row in f:
row = row.strip()
h_ctg_ids.add(row)
pread_to_contigs = {}
for fnanme in (p_ctg_edges, h_ctg_edges):
with open(fnanme) as f:
for row in f:
row = row.strip().split()
ctg = row[0]
if len(ctg.split("_")) > 1 and ctg not in h_ctg_ids:
continue
n1 = row[1]
n2 = row[2]
pid1 = int(n1.split(":")[0])
pid2 = int(n2.split(":")[0])
rid1 = pread_did_to_rid[pid1].split("/")[1]
rid2 = pread_did_to_rid[pid2].split("/")[1]
rid1 = int(int(rid1) / 10)
rid2 = int(int(rid2) / 10)
oid1 = rid_to_oid[rid1]
oid2 = rid_to_oid[rid2]
k1 = (pid1, rid1, oid1)
pread_to_contigs.setdefault(k1, set())
pread_to_contigs[k1].add(ctg)
k2 = (pid2, rid2, oid2)
pread_to_contigs.setdefault(k2, set())
pread_to_contigs[k2].add(ctg)
with open(read_to_contig_map, "w") as f:
for k in pread_to_contigs:
pid, rid, oid = k
for ctg in list(pread_to_contigs[k]):
print >> f, "%09d %09d %s %s" % (pid, rid, oid, ctg)
wf.addTask(generate_read_to_hctg_map)
wf.refreshTargets() # block
def get_read_ctg_map(rawread_dir, pread_dir, asm_dir):
read_map_dir = os.path.abspath(os.path.join(asm_dir, "read_maps"))
make_dirs(read_map_dir)
PypeMPWorkflow.setNumThreadAllowed(12, 12)
wf = PypeMPWorkflow()
rawread_db = makePypeLocalFile( os.path.join( rawread_dir, "raw_reads.db" ) )
rawread_id_file = makePypeLocalFile( os.path.join( read_map_dir, "raw_read_ids" ) )
@PypeTask( inputs = {"rawread_db": rawread_db},
outputs = {"rawread_id_file": rawread_id_file},
TaskType = PypeThreadTaskBase,
URL = "task://localhost/dump_rawread_ids" )
def dump_rawread_ids(self):
rawread_db = fn( self.rawread_db )
rawread_id_file = fn( self.rawread_id_file )
os.system("DBshow -n %s | tr -d '>' | LD_LIBRARY_PATH= awk '{print $1}' > %s" % (rawread_db, rawread_id_file) )
wf.addTask( dump_rawread_ids )
pread_db = makePypeLocalFile( os.path.join( pread_dir, "preads.db" ) )
pread_id_file = makePypeLocalFile( os.path.join( read_map_dir, "pread_ids" ) )
@PypeTask( inputs = {"pread_db": pread_db},
outputs = {"pread_id_file": pread_id_file},
TaskType = PypeThreadTaskBase,
URL = "task://localhost/dump_pread_ids" )
def dump_pread_ids(self):
pread_db = fn( self.pread_db )
pread_id_file = fn( self.pread_id_file )
os.system("DBshow -n %s | tr -d '>' | LD_LIBRARY_PATH= awk '{print $1}' > %s" % (pread_db, pread_id_file) )
wf.addTask( dump_pread_ids )
wf.refreshTargets() # block
sg_edges_list = makePypeLocalFile( os.path.join(asm_dir, "sg_edges_list") )
utg_data = makePypeLocalFile( os.path.join(asm_dir, "utg_data") )
ctg_paths = makePypeLocalFile( os.path.join(asm_dir, "ctg_paths") )
inputs = { "rawread_id_file": rawread_id_file,
"pread_id_file": pread_id_file,
"sg_edges_list": sg_edges_list,
"utg_data": utg_data,
"ctg_paths": ctg_paths }
read_to_contig_map = makePypeLocalFile( os.path.join(read_map_dir, "read_to_contig_map") )
@PypeTask( inputs = inputs,
outputs = {"read_to_contig_map": read_to_contig_map},
TaskType = PypeThreadTaskBase,
URL = "task://localhost/get_ctg_read_map" )
def generate_read_to_ctg_map(self):
rawread_id_file = fn( self.rawread_id_file )
pread_id_file = fn( self.pread_id_file )
read_to_contig_map = fn( self.read_to_contig_map )
pread_did_to_rid = open(pread_id_file).read().split("\n")
rid_to_oid = open(rawread_id_file).read().split("\n")
asm_G = AsmGraph(fn(self.sg_edges_list),
fn(self.utg_data),
fn(self.ctg_paths) )
pread_to_contigs = {}
with open(read_to_contig_map, "w") as f:
for ctg in asm_G.ctg_data:
if ctg[-1] == "R":
continue
ctg_g = asm_G.get_sg_for_ctg(ctg)
for n in ctg_g.nodes():
pid = int(n.split(":")[0])
rid = pread_did_to_rid[pid].split("/")[1]
rid = int(int(rid)/10)
oid = rid_to_oid[rid]
k = (pid, rid, oid)
pread_to_contigs.setdefault( k, set() )
pread_to_contigs[ k ].add( ctg )
for k in pread_to_contigs:
pid, rid, oid = k
for ctg in list(pread_to_contigs[ k ]):
print >>f, "%09d %09d %s %s" % (pid, rid, oid, ctg)
wf.addTask( generate_read_to_ctg_map )
wf.refreshTargets() # block