def sanity_check_daligner(scriptDir, testDirName="daligner_test_dir"): """ Run daligner on gcon_in.fa, but don't care about results. Just make sure it runs. """ scriptDir = realpath(scriptDir) testDir = op.join(scriptDir, testDirName) mkdir(scriptDir) mkdir(testDir) testInFa = op.join(testDir, "daligner.fasta") if op.exists(testInFa): os.remove(testInFa) shutil.copy(GCON_IN_FA, testInFa) assert op.exists(testInFa) runner = DalignerRunner(query_filename=testInFa, target_filename=testInFa, is_FL=True, same_strand_only=True, query_converted=False, target_converted=False, use_sge=False, cpus=4, sge_opts=None) runner.run(output_dir=testDir, min_match_len=300, sensitive_mode=False) runner.clean_run() shutil.rmtree(testDir) logging.info("daligner check passed.") return True
def _align_withDALIGNER(self, queryFa, output_dir): """Align input reads against itself using DALIGNER.""" # run this locally runner = DalignerRunner(query_filename=queryFa, target_filename=queryFa, query_converted=False, target_converted=False, is_FL=True, same_strand_only=True, use_sge=False, sge_opts=None, cpus=4) runner.run(min_match_len=self.ice_opts.low_cDNA_size, output_dir=output_dir, sensitive_mode=self.ice_opts.sensitive_mode) return runner
def _test_daligner_against_ref(self, test_name, use_sge, sge_opts, prob_model_from="fake"): """Test daligner_against_ref with and without using sge.""" copy_dir = op.join(self.dataDir, "test_daligner_against_ref") output_dir = op.join(self.outDir, test_name) mknewdir(output_dir) qname, tname = "test_daligner_query.fasta", "test_daligner_target.fasta" query_filename = op.join(output_dir, qname) target_filename = op.join(output_dir, tname) prob_model = None if prob_model_from == "fake": prob_model = ProbFromModel(0.01, 0.07, 0.06) elif prob_model_from == "fastq": fastq_fn = op.join(copy_dir, "test_daligner_reads.fastq") prob_model = ProbFromFastq(fastq_fn) else: self.assertTrue(False) qver_get_func = prob_model.get_smoothed qvmean_get_func = prob_model.get_mean dummy_o, c, dummy_m = backticks("cp %s %s" % (op.join(copy_dir, qname), query_filename)) self.assertTrue(c == 0) dummy_o, c, dummy_m = backticks("cp %s %s" % (op.join(copy_dir, tname), target_filename)) self.assertTrue(c == 0) old_dir = os.getcwd() os.chdir(output_dir) runner = DalignerRunner(query_filename=query_filename, target_filename=target_filename, is_FL=True, same_strand_only=True, use_sge=use_sge, sge_opts=sge_opts) runner.run(output_dir=op.join(self.outDir, test_name)) hits = [] for la4ice_filename in runner.la4ice_filenames: hits.extend(daligner_against_ref(query_dazz_handler=runner.query_dazz_handler, target_dazz_handler=runner.target_dazz_handler, la4ice_filename=la4ice_filename, is_FL=True, sID_starts_with_c=False, qver_get_func=qver_get_func, qvmean_get_func=qvmean_get_func)) # Num of hits may change when daligner or parameters change. self.assertTrue(len(hits), 706) self.assertEqual(str(hits[0]), "m54007_160109_025449/27984844/29_646_CCS/0_617 aligns to m54007_160109_025449/28836279/631_54_CCS") os.chdir(output_dir)
def setUp(self): """Initialize.""" self.data_dir = op.join(DATA_DIR, "test_daligner_against_ref") self.script_dir = op.join(OUT_DIR, "test_ice_daligner_script") self.dazz_dir = op.join(OUT_DIR, "test_ice_daligner_dazz") self.out_dir = op.join(OUT_DIR, "test_ice_daligner_out") mkdir(self.dazz_dir) mkdir(self.out_dir) self.stdout_dir = STD_DIR self.sivDataDir = SIV_DATA_DIR self.query_filename = "test_daligner_query.fasta" self.target_filename = "test_daligner_target.fasta" self.runner = DalignerRunner( query_filename=op.join(self.data_dir, self.query_filename), target_filename=op.join(self.data_dir, self.target_filename), is_FL=False, same_strand_only=True, dazz_dir=self.dazz_dir, script_dir=self.script_dir) self.runner.output_dir = self.out_dir
def _align_withDALIGNER(self, queryFa, output_dir): """ Align input reads against itself using DALIGNER. """ # run this locally # Liz: is_FL is currently turned OFF! because LA4Ice has ICE_FL(-E) set with 200/50bp missed, too strict runner = DalignerRunner(query_filename=queryFa, target_filename=queryFa, query_converted=False, target_converted=False, is_FL=False, same_strand_only=True, use_sge=False, sge_opts=None, cpus=4) runner.run(min_match_len=self.ice_opts.min_match_len, output_dir=output_dir, sensitive_mode=self.ice_opts.sensitive_mode) return runner
def setUp(self): """Initialize.""" self.data_dir = op.join(DATA_DIR, "test_daligner_against_ref") self.script_dir = op.join(OUT_DIR, "test_ice_daligner_script") self.dazz_dir = op.join(OUT_DIR, "test_ice_daligner_dazz") self.out_dir = op.join(OUT_DIR, "test_ice_daligner_out") mkdir (self.dazz_dir) mkdir (self.out_dir) self.stdout_dir = STD_DIR self.sivDataDir = SIV_DATA_DIR self.query_filename = "test_daligner_query.fasta" self.target_filename = "test_daligner_target.fasta" self.runner = DalignerRunner(query_filename=op.join(self.data_dir, self.query_filename), target_filename=op.join(self.data_dir, self.target_filename), is_FL=False, same_strand_only=True, dazz_dir=self.dazz_dir, script_dir=self.script_dir) self.runner.output_dir = self.out_dir
def build_uc_from_partial_daligner(input_fasta, ref_fasta, out_pickle, done_filename, ice_opts, probqv, qv_prob_threshold=0.3, cpus=4, no_qv_or_aln_checking=False, tmp_dir=None, sID_starts_with_c=False): """ Given an input_fasta file of non-full-length (partial) reads and (unpolished) consensus isoforms sequences in ref_fasta, align reads to consensus isoforms using DALIGNER, and then build up a mapping between consensus isoforms and reads (i.e., assign reads to isoforms). Finally, save {isoform_id: [read_ids], nohit: set(no_hit_read_ids)} to an output pickle file. tmp_dir - where to save intermediate files such as dazz files. if None, writer dazz files to the same directory as query/target. """ input_fasta = realpath(input_fasta) ref_fasta = realpath(ref_fasta) out_pickle = realpath(out_pickle) output_dir = op.dirname(out_pickle) ice_opts.detect_cDNA_size(ref_fasta) # ice_partial is already being called through qsub, so run everything local! runner = DalignerRunner(query_filename=input_fasta, target_filename=ref_fasta, is_FL=False, same_strand_only=False, query_converted=False, target_converted=True, dazz_dir=tmp_dir, script_dir=op.join(output_dir, "script"), use_sge=False, sge_opts=None, cpus=cpus) runner.run(min_match_len=ice_opts.min_match_len, output_dir=output_dir, sensitive_mode=ice_opts.sensitive_mode) partial_uc = {} # Maps each isoform (cluster) id to a list of reads # which can map to the isoform seen = set() # reads seen logging.info("Building uc from DALIGNER hits.") for la4ice_filename in runner.la4ice_filenames: start_t = time.time() # not providing full_missed_start/end since aligning nFLs, ok to partially align only hitItems = daligner_against_ref2(query_dazz_handler=runner.query_dazz_handler, target_dazz_handler=runner.target_dazz_handler, la4ice_filename=la4ice_filename, is_FL=False, sID_starts_with_c=sID_starts_with_c, qver_get_func=probqv.get_smoothed, qvmean_get_func=probqv.get_mean, qv_prob_threshold=qv_prob_threshold, ece_penalty=ice_opts.ece_penalty, ece_min_len=ice_opts.ece_min_len, same_strand_only=True, no_qv_or_aln_checking=no_qv_or_aln_checking, max_missed_start=ice_opts.max_missed_start, max_missed_end=ice_opts.max_missed_end, full_missed_start=ice_opts.full_missed_start, full_missed_end=ice_opts.full_missed_end) for h in hitItems: if h.ece_arr is not None: if h.cID not in partial_uc: partial_uc[h.cID] = set() partial_uc[h.cID].add(h.qID) seen.add(h.qID) logging.info("processing %s took %s sec", la4ice_filename, str(time.time()-start_t)) for k in partial_uc: partial_uc[k] = list(partial_uc[k]) allhits = set(r.name.split()[0] for r in ContigSetReaderWrapper(input_fasta)) logging.info("Counting reads with no hit.") nohit = allhits.difference(seen) logging.info("Dumping uc to a pickle: %s.", out_pickle) with open(out_pickle, 'w') as f: if out_pickle.endswith(".pickle"): dump({'partial_uc': partial_uc, 'nohit': nohit}, f) elif out_pickle.endswith(".json"): f.write(json.dumps({'partial_uc': partial_uc, 'nohit': nohit})) else: raise IOError("Unrecognized extension: %s" % out_pickle) done_filename = realpath(done_filename) if done_filename is not None \ else out_pickle + '.DONE' logging.debug("Creating %s.", done_filename) touch(done_filename) # remove all the .las and .las.out filenames runner.clean_run()
def build_uc_from_partial_daligner(input_fasta, ref_fasta, out_pickle, ccs_fofn=None, done_filename=None, use_finer_qv=False, cpus=24, no_qv_or_aln_checking=True, tmp_dir=None): """ Given an input_fasta file of non-full-length (partial) reads and (unpolished) consensus isoforms sequences in ref_fasta, align reads to consensus isoforms using BLASR, and then build up a mapping between consensus isoforms and reads (i.e., assign reads to isoforms). Finally, save {isoform_id: [read_ids], nohit: set(no_hit_read_ids)} to an output pickle file. ccs_fofn --- If None, assume no quality value is available, otherwise, use QV from ccs_fofn. tmp_dir - where to save intermediate files such as dazz files. if None, writer dazz files to the same directory as query/target. """ input_fasta = realpath(input_fasta) ref_fasta = realpath(ref_fasta) out_pickle = realpath(out_pickle) output_dir = op.dirname(out_pickle) ice_opts = IceOptions() ice_opts.detect_cDNA_size(ref_fasta) # ice_partial is already being called through qsub, so run everything local! runner = DalignerRunner(query_filename=input_fasta, target_filename=ref_fasta, is_FL=False, same_strand_only=False, query_converted=False, target_converted=True, dazz_dir=tmp_dir, script_dir=op.join(output_dir, "script"), use_sge=False, sge_opts=None, cpus=cpus) runner.run(min_match_len=300, output_dir=output_dir, sensitive_mode=ice_opts.sensitive_mode) if no_qv_or_aln_checking: # not using QVs or alignment checking! # this probqv is just a DUMMY to pass to daligner_against_ref, which won't be used logging.info("Not using QV for partial_uc. Loading dummy QV.") probqv = ProbFromModel(.01, .07, .06) else: if ccs_fofn is None: logging.info("Loading probability from model (0.01,0.07,0.06)") probqv = ProbFromModel(.01, .07, .06) else: start_t = time.time() if use_finer_qv: probqv = ProbFromQV(input_fofn=ccs_fofn, fasta_filename=input_fasta) logging.info("Loading QVs from %s + %s took %s secs", ccs_fofn, input_fasta, time.time()-start_t) else: input_fastq = input_fasta[:input_fasta.rfind('.')] + '.fastq' logging.info("Converting %s + %s --> %s", input_fasta, ccs_fofn, input_fastq) ice_fa2fq(input_fasta, ccs_fofn, input_fastq) probqv = ProbFromFastq(input_fastq) logging.info("Loading QVs from %s took %s secs", input_fastq, time.time()-start_t) logging.info("Calling dalign_against_ref ...") partial_uc = {} # Maps each isoform (cluster) id to a list of reads # which can map to the isoform seen = set() # reads seen logging.info("Building uc from DALIGNER hits.") for la4ice_filename in runner.la4ice_filenames: start_t = time.time() hitItems = daligner_against_ref(query_dazz_handler=runner.query_dazz_handler, target_dazz_handler=runner.target_dazz_handler, la4ice_filename=la4ice_filename, is_FL=False, sID_starts_with_c=True, qver_get_func=probqv.get_smoothed, qvmean_get_func=probqv.get_mean, ece_penalty=1, ece_min_len=20, same_strand_only=False, no_qv_or_aln_checking=no_qv_or_aln_checking) for h in hitItems: if h.ece_arr is not None: if h.cID not in partial_uc: partial_uc[h.cID] = set() partial_uc[h.cID].add(h.qID) seen.add(h.qID) logging.info("processing %s took %s sec", la4ice_filename, str(time.time()-start_t)) for k in partial_uc: partial_uc[k] = list(partial_uc[k]) allhits = set(r.name.split()[0] for r in ContigSetReaderWrapper(input_fasta)) logging.info("Counting reads with no hit.") nohit = allhits.difference(seen) logging.info("Dumping uc to a pickle: %s.", out_pickle) with open(out_pickle, 'w') as f: if out_pickle.endswith(".pickle"): dump({'partial_uc': partial_uc, 'nohit': nohit}, f) elif out_pickle.endswith(".json"): f.write(json.dumps({'partial_uc': partial_uc, 'nohit': nohit})) else: raise IOError("Unrecognized extension: %s" % out_pickle) done_filename = realpath(done_filename) if done_filename is not None \ else out_pickle + '.DONE' logging.debug("Creating %s.", done_filename) touch(done_filename) # remove all the .las and .las.out filenames runner.clean_run()
class TestDalignerRunner(unittest.TestCase): """Test pbtranscript.ice_daligner.DalignerRunner""" def setUp(self): """Initialize.""" self.data_dir = op.join(DATA_DIR, "test_daligner_against_ref") self.script_dir = op.join(OUT_DIR, "test_ice_daligner_script") self.dazz_dir = op.join(OUT_DIR, "test_ice_daligner_dazz") self.out_dir = op.join(OUT_DIR, "test_ice_daligner_out") mkdir(self.dazz_dir) mkdir(self.out_dir) self.stdout_dir = STD_DIR self.sivDataDir = SIV_DATA_DIR self.query_filename = "test_daligner_query.fasta" self.target_filename = "test_daligner_target.fasta" self.runner = DalignerRunner( query_filename=op.join(self.data_dir, self.query_filename), target_filename=op.join(self.data_dir, self.target_filename), is_FL=False, same_strand_only=True, dazz_dir=self.dazz_dir, script_dir=self.script_dir) self.runner.output_dir = self.out_dir def test_query_prefix(self): """Test query_prefix.""" self.assertEqual( self.runner.query_prefix(1), op.join(self.dazz_dir, self.query_filename[0:-6] + ".dazz.fasta")) def test_target_prefix(self): """Test target_prefix.""" self.assertEqual( self.runner.target_prefix(1), op.join(self.dazz_dir, self.target_filename[0:-6] + ".dazz.fasta")) def test_thread_prefix(self): """Test local_job_runner.""" self.assertEqual(self.runner.thread_prefix(2, is_forward=True), 'N2') self.assertEqual(self.runner.thread_prefix(2, is_forward=False), 'C2') def test_las_filenames(self): """Test las_filenames.""" expected = [ op.join( self.out_dir, "{q}.{t}.{k}.las".format( q=self.query_filename[0:-6] + ".dazz.fasta", t=self.target_filename[0:-6] + ".dazz.fasta", k=k)) for k in ('N0', 'N1', 'N2', 'N3') ] print 'las_filenames\n' print expected self.assertEqual(self.runner.las_filenames, expected) def test_la4ice_filenames(self): """Test la4ice_filenames.""" expected = [ op.join( self.out_dir, "{q}.{t}.{k}.las.out".format( q=self.query_filename[0:-6] + ".dazz.fasta", t=self.target_filename[0:-6] + ".dazz.fasta", k=k)) for k in ('N0', 'N1', 'N2', 'N3') ] self.assertEqual(self.runner.la4ice_filenames, expected) def test_run(self): """Test run(output_dir, min_match_len, sensitive_mode). running on sge and locally. """ run_on_sge = (backticks('qstat')[1] == 0) if run_on_sge: self.runner.use_sge = True self.runner.sge_opts = SgeOptions(100) mknewdir(self.out_dir) self.runner.run(output_dir=self.out_dir) for las_filename in self.runner.las_filenames: print "Checking existance of " + las_filename self.assertTrue(op.exists(las_filename)) for la4ice_filename in self.runner.la4ice_filenames: print "Checking existance of " + la4ice_filename self.assertTrue(op.exists(la4ice_filename)) # Run locally self.runner.use_sge = False mknewdir(self.out_dir) self.runner.run(output_dir=self.out_dir) for las_filename in self.runner.las_filenames: print "Checking existance of " + las_filename self.assertTrue(op.exists(las_filename)) for la4ice_filename in self.runner.la4ice_filenames: print "Checking existance of " + la4ice_filename self.assertTrue(op.exists(la4ice_filename)) # clean all output self.runner.clean_run() for las_filename in self.runner.las_filenames: print "Checking %s has been removed.\n" % las_filename self.assertTrue(not op.exists(las_filename)) for la4ice_filename in self.runner.la4ice_filenames: print "Checking %s has been removed.\n" % la4ice_filename self.assertTrue(not op.exists(la4ice_filename))
class TestDalignerRunner(unittest.TestCase): """Test pbtranscript.ice_daligner.DalignerRunner""" def setUp(self): """Initialize.""" self.data_dir = op.join(DATA_DIR, "test_daligner_against_ref") self.script_dir = op.join(OUT_DIR, "test_ice_daligner_script") self.dazz_dir = op.join(OUT_DIR, "test_ice_daligner_dazz") self.out_dir = op.join(OUT_DIR, "test_ice_daligner_out") mkdir (self.dazz_dir) mkdir (self.out_dir) self.stdout_dir = STD_DIR self.sivDataDir = SIV_DATA_DIR self.query_filename = "test_daligner_query.fasta" self.target_filename = "test_daligner_target.fasta" self.runner = DalignerRunner(query_filename=op.join(self.data_dir, self.query_filename), target_filename=op.join(self.data_dir, self.target_filename), is_FL=False, same_strand_only=True, dazz_dir=self.dazz_dir, script_dir=self.script_dir) self.runner.output_dir = self.out_dir def test_query_prefix(self): """Test query_prefix.""" self.assertEqual(self.runner.query_prefix(1), op.join(self.dazz_dir, self.query_filename[0:-6] + ".dazz.fasta")) def test_target_prefix(self): """Test target_prefix.""" self.assertEqual(self.runner.target_prefix(1), op.join(self.dazz_dir, self.target_filename[0:-6] + ".dazz.fasta")) def test_thread_prefix(self): """Test local_job_runner.""" self.assertEqual(self.runner.thread_prefix(2, is_forward=True), 'N2') self.assertEqual(self.runner.thread_prefix(2, is_forward=False), 'C2') def test_las_filenames(self): """Test las_filenames.""" expected = [op.join(self.out_dir, "{q}.{t}.{k}.las".format( q=self.query_filename[0:-6] + ".dazz.fasta", t=self.target_filename[0:-6] + ".dazz.fasta", k=k)) for k in ('N0', 'N1', 'N2', 'N3')] print 'las_filenames\n' print expected self.assertEqual(self.runner.las_filenames, expected) def test_la4ice_filenames(self): """Test la4ice_filenames.""" expected = [op.join(self.out_dir, "{q}.{t}.{k}.las.out".format( q=self.query_filename[0:-6] + ".dazz.fasta", t=self.target_filename[0:-6] + ".dazz.fasta", k=k)) for k in ('N0', 'N1', 'N2', 'N3')] self.assertEqual(self.runner.la4ice_filenames, expected) def test_run(self): """Test run(output_dir, min_match_len, sensitive_mode). running on sge and locally. """ run_on_sge = (backticks('qstat')[1] == 0) if run_on_sge: self.runner.use_sge = True self.runner.sge_opts = SgeOptions(100) mknewdir(self.out_dir) self.runner.run(output_dir=self.out_dir) for las_filename in self.runner.las_filenames: print "Checking existance of " + las_filename self.assertTrue(op.exists(las_filename)) for la4ice_filename in self.runner.la4ice_filenames: print "Checking existance of " + la4ice_filename self.assertTrue(op.exists(la4ice_filename)) # Run locally self.runner.use_sge = False mknewdir(self.out_dir) self.runner.run(output_dir=self.out_dir) for las_filename in self.runner.las_filenames: print "Checking existance of " + las_filename self.assertTrue(op.exists(las_filename)) for la4ice_filename in self.runner.la4ice_filenames: print "Checking existance of " + la4ice_filename self.assertTrue(op.exists(la4ice_filename)) # clean all output self.runner.clean_run() for las_filename in self.runner.las_filenames: print "Checking %s has been removed.\n" % las_filename self.assertTrue(not op.exists(las_filename)) for la4ice_filename in self.runner.la4ice_filenames: print "Checking %s has been removed.\n" % la4ice_filename self.assertTrue(not op.exists(la4ice_filename))
def build_uc_from_partial_daligner(input_fasta, ref_fasta, out_pickle, ccs_fofn=None, done_filename=None, use_finer_qv=False, cpus=24, no_qv_or_aln_checking=True, tmp_dir=None): """ Given an input_fasta file of non-full-length (partial) reads and (unpolished) consensus isoforms sequences in ref_fasta, align reads to consensus isoforms using BLASR, and then build up a mapping between consensus isoforms and reads (i.e., assign reads to isoforms). Finally, save {isoform_id: [read_ids], nohit: set(no_hit_read_ids)} to an output pickle file. ccs_fofn --- If None, assume no quality value is available, otherwise, use QV from ccs_fofn. tmp_dir - where to save intermediate files such as dazz files. if None, writer dazz files to the same directory as query/target. """ input_fasta = realpath(input_fasta) ref_fasta = realpath(ref_fasta) out_pickle = realpath(out_pickle) output_dir = op.dirname(out_pickle) ice_opts = IceOptions() ice_opts.detect_cDNA_size(ref_fasta) # ice_partial is already being called through qsub, so run everything local! runner = DalignerRunner(query_filename=input_fasta, target_filename=ref_fasta, is_FL=False, same_strand_only=False, query_converted=False, target_converted=True, dazz_dir=tmp_dir, script_dir=op.join(output_dir, "script"), use_sge=False, sge_opts=None, cpus=cpus) runner.run(min_match_len=300, output_dir=output_dir, sensitive_mode=ice_opts.sensitive_mode) if no_qv_or_aln_checking: # not using QVs or alignment checking! # this probqv is just a DUMMY to pass to daligner_against_ref, which won't be used logging.info("Not using QV for partial_uc. Loading dummy QV.") probqv = ProbFromModel(.01, .07, .06) else: if ccs_fofn is None: logging.info("Loading probability from model (0.01,0.07,0.06)") probqv = ProbFromModel(.01, .07, .06) else: start_t = time.time() if use_finer_qv: probqv = ProbFromQV(input_fofn=ccs_fofn, fasta_filename=input_fasta) logging.info("Loading QVs from %s + %s took %s secs", ccs_fofn, input_fasta, time.time() - start_t) else: input_fastq = input_fasta[:input_fasta.rfind('.')] + '.fastq' logging.info("Converting %s + %s --> %s", input_fasta, ccs_fofn, input_fastq) ice_fa2fq(input_fasta, ccs_fofn, input_fastq) probqv = ProbFromFastq(input_fastq) logging.info("Loading QVs from %s took %s secs", input_fastq, time.time() - start_t) logging.info("Calling dalign_against_ref ...") partial_uc = {} # Maps each isoform (cluster) id to a list of reads # which can map to the isoform seen = set() # reads seen logging.info("Building uc from DALIGNER hits.") for la4ice_filename in runner.la4ice_filenames: start_t = time.time() hitItems = daligner_against_ref( query_dazz_handler=runner.query_dazz_handler, target_dazz_handler=runner.target_dazz_handler, la4ice_filename=la4ice_filename, is_FL=False, sID_starts_with_c=True, qver_get_func=probqv.get_smoothed, qvmean_get_func=probqv.get_mean, ece_penalty=1, ece_min_len=20, same_strand_only=False, no_qv_or_aln_checking=no_qv_or_aln_checking) for h in hitItems: if h.ece_arr is not None: if h.cID not in partial_uc: partial_uc[h.cID] = set() partial_uc[h.cID].add(h.qID) seen.add(h.qID) logging.info("processing %s took %s sec", la4ice_filename, str(time.time() - start_t)) for k in partial_uc: partial_uc[k] = list(partial_uc[k]) allhits = set(r.name.split()[0] for r in ContigSetReaderWrapper(input_fasta)) logging.info("Counting reads with no hit.") nohit = allhits.difference(seen) logging.info("Dumping uc to a pickle: %s.", out_pickle) with open(out_pickle, 'w') as f: if out_pickle.endswith(".pickle"): dump({'partial_uc': partial_uc, 'nohit': nohit}, f) elif out_pickle.endswith(".json"): f.write(json.dumps({'partial_uc': partial_uc, 'nohit': nohit})) else: raise IOError("Unrecognized extension: %s" % out_pickle) done_filename = realpath(done_filename) if done_filename is not None \ else out_pickle + '.DONE' logging.debug("Creating %s.", done_filename) touch(done_filename) # remove all the .las and .las.out filenames runner.clean_run()
def _test_daligner_against_ref(self, test_name, use_sge, sge_opts, prob_model_from="fake"): """Test daligner_against_ref with and without using sge.""" copy_dir = op.join(self.dataDir, "test_daligner_against_ref") output_dir = op.join(self.outDir, test_name) mknewdir(output_dir) qname, tname = "test_daligner_query.fasta", "test_daligner_target.fasta" query_filename = op.join(output_dir, qname) target_filename = op.join(output_dir, tname) prob_model = None if prob_model_from == "fake": prob_model = ProbFromModel(0.01, 0.07, 0.06) elif prob_model_from == "fastq": fastq_fn = op.join(copy_dir, "test_daligner_reads.fastq") prob_model = ProbFromFastq(fastq_fn) else: self.assertTrue(False) qver_get_func = prob_model.get_smoothed qvmean_get_func = prob_model.get_mean dummy_o, c, dummy_m = backticks( "cp %s %s" % (op.join(copy_dir, qname), query_filename)) self.assertTrue(c == 0) dummy_o, c, dummy_m = backticks( "cp %s %s" % (op.join(copy_dir, tname), target_filename)) self.assertTrue(c == 0) old_dir = os.getcwd() os.chdir(output_dir) runner = DalignerRunner(query_filename=query_filename, target_filename=target_filename, is_FL=True, same_strand_only=True, use_sge=use_sge, sge_opts=sge_opts) runner.run(output_dir=op.join(self.outDir, test_name)) hits = [] for la4ice_filename in runner.la4ice_filenames: hits.extend( daligner_against_ref( query_dazz_handler=runner.query_dazz_handler, target_dazz_handler=runner.target_dazz_handler, la4ice_filename=la4ice_filename, is_FL=True, sID_starts_with_c=False, qver_get_func=qver_get_func, qvmean_get_func=qvmean_get_func)) # Num of hits may change when daligner or parameters change. self.assertTrue(len(hits), 706) self.assertEqual( str(hits[0]), "m54007_160109_025449/27984844/29_646_CCS/0_617 aligns to m54007_160109_025449/28836279/631_54_CCS" ) os.chdir(output_dir)