timer['after_generate_ref'] = time.time()
timer['for_ref'] = timer['after_generate_ref'] - timer['after_sp']
if compare_ans:
curr_ref = sample_output_name+'algo_output/reference.fasta'
reconstr = sample_output_name+'algo_output/reconstructed.fasta'
all_seq = sample_output_name+'algo_output/all_sequences.fasta'
reconstr_per = sample_output_name+'algo_output/reconstr_per.txt'
reconstr_rev_per = sample_output_name+'algo_output/reconstr_rev_per.txt'
reconstr_log = sample_output_name+'algo_output/reconstr_log.txt'
reconstr_rev_log = sample_output_name+'algo_output/reconstr_rev_log.txt'
all_seq_per = sample_output_name+'algo_output/all_seq_per.txt'
self_repeats = sample_output_name+'algo_output/self_repeats.txt'
if not blat:
run_cmd('mummer -maxmatch -l 80 ' + reconstr + ' ' + curr_ref + ' > ' + reconstr_per)
tester.analyzer(reconstr_per,reconstr_log,exp_file,N)
run_cmd('mummer -maxmatch -l 80 ' + curr_ref + ' ' + reconstr + ' > ' + reconstr_rev_per)
tester.reverse_analyzer(reconstr_rev_per,reconstr_rev_log,reconstr,N)
else:
run_cmd(python_path + ' ' + shannon_dir + 'parallel_blat_python.py ' + reconstr + ' ' + curr_ref + ' ' + reconstr_per)
tester.analyzer_blat_noExp(reconstr_per,reconstr_log,exp_file,N)
if false_positive:
tester.false_positive(reconstr,reconstr_per,reconstr_rev_log)
if run_trinity or compare_trinity:
curr_ref = sample_output_name+'algo_output/reference.fasta'
def run_MB_SF(arguments,inMem=False,contigs=[],weights=[],rps=[]):
print(arguments)
inDisk = not inMem
arguments = arguments.strip().split()
L = 100
N = 8743351
sn = ''
sparsity = 0.5
start_loc = 1
stop_loc = 120000000
paired_end = 0
add_errors = 1
double_stranded = 0
sim = 0
to_set_exp = 0
generate_reads = 0
trimmomatic = 0 #currently not enabled
run_seecer =0
run_jellyfish =0 # runs jellyfish to get kmers
run_extension_corr =0 # runs contig based error correction to filter k1mers used to build kmer graph
run_cpp = 0 # builds condensed kmer graph
mb = 0 # runs multibridging
sparse_flow = 0
parallelize_sf = 0
generate_ref = 0
compare_ans = 0 # compares reconstructed transcripts to reference transcripts to measure performance of assembler
run_trinity = 0 # Runs a competing algorithm trinity
compare_trinity = 0
plots = 0
plots_express = 0
run_rsem_eval = 0
run_cuffinks = 0 # Runs a competing algorithm cufflinks
compare_cufflinks = 0
compare_soap =0
compare_oasis=0
compare_trans=0
false_positive=0
bowtie = 0
extract_bam = 0
oracle_set = 0
err_string = ' '
pairedend_string = ' '
mb_string = ' '
trinity_string = ' '
jellyfish_dir = ' jellyfish'
jellyfish_kmer_cutoff = 1
seecer_dir = ' /data/sreeramk/packages/SEECER-0.1.3/SEECER/bin/run_seecer.sh'
K_value = 24
blat = 1
# ----------------------------------------------------------------------------------
# Sets parameters from terminal
sample_name = None
filter_FP_flag = False
shannon_dir = ''
only_k1 = ' --only_k1 ' #Default: write only k1mers
only_reads = False #default: only_reads = false
nJobs = 1
python_path = 'python'
n_inp = arguments
if len(n_inp)>1:
sample_name = arguments[0]
if '--run_alg' in n_inp:
mb = 1
sparse_flow = 1
if '--ds' in n_inp:
double_stranded = 1
if '--paired_end' in n_inp:
paired_end = 1
if '--compare' in n_inp:
compare_ans = 1
if '--kmer_size' in n_inp:
K_value = int(n_inp[n_inp.index('--kmer_size')+1])
if '--only_reads' in n_inp:
only_reads = True
run_jellyfish = 1
run_extension_corr = 1
if '--nJobs' in n_inp:
nJobs = int(n_inp[n_inp.index('--nJobs')+1])
if '--both' in n_inp:
only_k1 == ' ' #Dont write only k1mers
#print(K_value)
if '--dir_name'in n_inp:
directory_name = n_inp[n_inp.index('--dir_name')+1]
if '--shannon_dir' in n_inp:
shannon_dir = n_inp[n_inp.index('--shannon_dir')+1]
if '--python_path' in n_inp:
python_path = n_inp[n_inp.index('--python_path')+1]
if '--filter_FP' in n_inp and paired_end:
filter_FP_flag = True
if paired_end:
F = 350 #Fragment size
F_sd = 0 #Fragment size Standard Deviation
sn = sn+'_F_'+str(F)
pairedend_string = ' -p ' + str(F) + ',' + str(F_sd) + ' '
else:
F=L
if add_errors:
error_rate = 0.01
err_string = ' -r ' + str(error_rate) + ' '
sn = sn + '_ERR'
mb_string += ' -e '
if double_stranded:
sn = sn + '_DS'
ds_string = ' '
#mb_string += ' -d '
else:
ds_string = ' --stranded '
trinity_string += ' --SS_lib_type FR '
def run_cmd(s1):
os.system(s1)
sample_output_name = sample_name
base_dir = ''
bed_file=' ./Genome/GSE51861_isoform.bed'
ref_file=' ./Genome/hg19.fa' # reference chromosome
exp_file= sample_name + 'algo_input/random_out.exp'
reads_file = sample_name + 'algo_input/reads'
if paired_end:
reads_string = reads_file + '_1.fasta '+reads_file + '_2.fasta '
else:
reads_string = reads_file + '.fasta '
timer = {}
timer['start'] = time.time()
if not os.path.exists(sample_name+'algo_input'):
os.makedirs(sample_name+'algo_input')
if not os.path.exists(sample_output_name+'algo_output'):
os.makedirs(sample_output_name+'algo_output')
if not os.path.exists(sample_output_name+'intermediate'):
os.makedirs(sample_output_name+'intermediate')
'''if mb or sparse_flow:
os.system('cp *.py ' + sample_output_name + 'algo_output/')'''
if trimmomatic:
run_cmd('java -jar /home/sreeramkannan/Packages/trinityrnaseq_r20131110/trinity-plugins/Trimmomatic-0.30/trimmomatic.jar SE -phred33 SRR453566_1.fastq reads_trimmomatic.fastq ILLUMINACLIP:/home/sreeramkannan/Packages/trinityrnaseq_r20131110/trinity-plugins/Trimmomatic-0.30/adapters/TruSeq2-SE.fa:2:30:10 LEADING:20 TRAILING:20 SLIDINGWINDOW:4:30 MINLEN:75 CROP:75 TOPHRED64')
run_cmd('java -jar /home/sreeramkannan/Packages/trinityrnaseq_r20131110/trinity-plugins/Trimmomatic-0.30/trimmomatic.jar PE -phred33 reads_1.fastq reads_2.fastq reads_trim_1.fastq reads_trim_UP1.fastq reads_trim_2.fastq reads_trim_UP2.fastq LEADING:20 TRAILING:20 SLIDINGWINDOW:4:30 MINLEN:50 CROP:50 TOPHRED64')
if run_jellyfish:
run_jfs = ' '
if double_stranded:
run_jfs += ' -C '
#run_cmd('rm '+sample_name+'algo_input/jelly*') #Remove old jellyfish files
run_cmd(jellyfish_dir+' count -m ' + str(K_value+1) + run_jfs+ ' -o ' + sample_name+'algo_input/jellyfish_p1_output -s 20000000 -c 4 -t ' + str(nJobs) + ' ' +reads_string)
'''if os.path.isfile(sample_name+'algo_input/jellyfish_p1_output_1'):
run_cmd(jellyfish_dir+' merge -o '+ sample_name+'algo_input/jellyfish_p1_output.jf ' + sample_name+'algo_input/jellyfish_p1_output\_*')
else:
run_cmd('mv ' + sample_name+'algo_input/jellyfish_p1_output_0 ' +sample_name+'algo_input/jellyfish_p1_output.jf')'''
run_cmd(jellyfish_dir+' dump -c -t -L ' + str(jellyfish_kmer_cutoff) + ' ' + sample_name+'algo_input/jellyfish_p1_output > ' + sample_name+'algo_input/k1mer.dict_org')
if (not run_extension_corr) and double_stranded:
tester.double_strandify(sample_name+'algo_input/k1mer.dict_org', sample_name+'algo_input/k1mer.dict')
if (not run_extension_corr) and (not double_stranded):
run_cmd('mv ' + sample_name+'algo_input/k1mer.dict_org ' + sample_name+'algo_input/k1mer.dict')
if run_extension_corr:
if double_stranded:
str_ec = ' -d '
else:
str_ec = ' '
run_cmd(python_path + ' ext_corr.py ' + str_ec + sample_name+'algo_input/k1mer.dict_org ' +sample_name+'algo_input/k1mer.dict 3 75')
'''if run_jellyfish or run_extension_corr:
run_cmd('python kp1mer_to_ kmer.py ' + sample_name+'algo_input/k1mer.dict ' + sample_name+'algo_input/kmer.dict')'''
if run_cpp:
run_cmd('tr \'\\t\' \'\\n\' <' + sample_name+'algo_input/kmer.dict > ' + sample_name+'algo_input/kmer.dict_2l ')
run_cmd('tr \'\\t\' \'\\n\' <' + sample_name+'algo_input/k1mer.dict > ' + sample_name+'algo_input/k1mer.dict_2l ')
run_cmd('./condenser ' + sample_name+'algo_input/kmer.dict_2l '+sample_name+'algo_input/k1mer.dict_2l ' + sample_name+'algo_input/' + ' ' + str(K_value) + ' | tee ' + sample_name + '_cpp_terminal_output.txt')
with open(sample_name + '_terminal_output.txt', 'w') as f7:
f7.write(" \n")
if inDisk and mb:
#run_cmd('rm '+sample_output_name+'intermediate/*')
jf_s = ' '; cpp_s = ' ';
use_jellyfish = 1; use_cpp = 0 #force set parameter for jellyfish
if use_jellyfish:
jf_s = ' '+ sample_name+'algo_input/kmer.dict '+sample_name+'algo_input/k1mer.dict '
if use_cpp:
cpp_s = '-c ' +sample_name+'algo_input/nodes.txt '+sample_name+'algo_input/edges.txt '
if not paired_end:
run_cmd(python_path + ' ' + shannon_dir + 'multibridging.py -f --kmer=' +str(K_value) + mb_string + only_k1 + jf_s + cpp_s + reads_file+'.fasta ' + sample_output_name + 'intermediate ' + ' | tee ' + sample_name + '_terminal_output.txt') # ' 2>&1 | tee ./' + sample_name + 'algo_input/log.txt')
else:
run_cmd(python_path + ' ' + shannon_dir + 'multibridging.py -f --kmer='+ str(K_value) + mb_string + only_k1 + jf_s + cpp_s + reads_file+'_1.fasta '+reads_file+'_2.fasta ' + sample_output_name+ 'intermediate ' + ' | tee ' + sample_name + '_terminal_output.txt') # 2>&1 | tee ./' + sample_name + 'algo_input/log.txt')
elif inMem and mb:
jf_s = ''; cpp_s = ''
#In Memory
if paired_end:
multibridging.main('-f --kmer='+ str(K_value) + mb_string + only_k1 + jf_s + cpp_s + reads_file+'_1.fasta '+reads_file+'_2.fasta ' + sample_output_name+ 'intermediate ', inMem, contigs, weights, rps)
else:
multibridging.main('-f --kmer='+ str(K_value) + mb_string + only_k1 + jf_s + cpp_s + reads_file+'.fasta ' + sample_output_name+ 'intermediate ', inMem, contigs, weights, rps)
timer['after_mb'] = time.time()
#timer['for_mb'] = timer['after_mb'] - timer['after_gen_reads']
if sparse_flow:
reconstr_file = sample_output_name+'algo_output/reconstructed.fasta'
#run_cmd('rm '+sample_output_name+'algo_output/reconstructed_comp_*.fasta')
#run_cmd('rm '+sample_output_name+'algo_output/reconstructed.fasta')
run_cmd(python_path + ' ' + shannon_dir + 'algorithm_SF.py -1 '+ sample_output_name)
ncomp = 0
iteration_string = " "
while os.path.isfile(sample_output_name + 'intermediate/nodes'+str(ncomp)+'.txt'):
if 0: #ncomp==0: and ncomp!=2: #testing purpose
ncomp +=1
continue
print('Component:',ncomp)
if not parallelize_sf:
os.system(python_path + ' ' + shannon_dir + 'algorithm_SF.py ' + str(ncomp) + ' '+ sample_output_name) # + ' | tee ' + sample_name + '_' + str(ncomp) + '_terminal_output.txt')
iteration_string += str(ncomp) + " "
ncomp=ncomp+1
if parallelize_sf:
os.system('parallel ' + python_path + ' ' + shannon_dir + 'algorithm_SF.py {} ' + sample_output_name+ " ::: " + iteration_string)
os.system("cat " + sample_output_name+'algo_output/reconstructed_comp_*.fasta' + " >> " + reconstr_file)
#filter_trans(sample_output_name+'algo_output/reconstructed.fasta', sample_output_name+'algo_output/reconstructed_short.fasta', 200)
if sparse_flow:
if os.path.exists(directory_name+"/before_sp_log.txt"):
f_log = open(directory_name+"/before_sp_log.txt", 'a')
else:
f_log = open(directory_name+"/before_sp_log.txt", 'w')
num_transcripts = 0
with open(sample_output_name+"algo_output/reconstructed.fasta", 'r') as reconstructed_transcripts:
num_transcripts = len(reconstructed_transcripts.readlines())
f_log.write(str(time.asctime()) + ": " +sample_output_name + " has completed: " + str(num_transcripts) + " transcripts" + "\n")
print(str(time.asctime()) + ": " +sample_output_name + " has completed: " + str(num_transcripts) + " transcripts")
f_log.close()
if filter_FP_flag:
reads_1 = sample_name+'algo_input/reads_1.fasta'
reads_2 = sample_name+'algo_input/reads_2.fasta'
rec_fasta = sample_name+"algo_output/reconstructed.fasta"
out_dir = sample_name+"algo_output/"
filter_FP.filter_FP(rec_fasta, reads_1, reads_2, out_dir)
timer['after_sp'] = time.time()
#timer['for_sp'] = timer['after_sp'] - timer['after_mb']
if compare_ans:
curr_ref = sample_output_name+'algo_output/reference.fasta'
reconstr = sample_output_name+'algo_output/reconstructed.fasta'
all_seq = sample_output_name+'algo_output/all_sequences.fasta'
reconstr_per = sample_output_name+'algo_output/reconstr_per.txt'
reconstr_rev_per = sample_output_name+'algo_output/reconstr_rev_per.txt'
reconstr_log = sample_output_name+'algo_output/reconstr_log.txt'
reconstr_rev_log = sample_output_name+'algo_output/reconstr_rev_log.txt'
all_seq_per = sample_output_name+'algo_output/all_seq_per.txt'
self_repeats = sample_output_name+'algo_output/self_repeats.txt'
if not blat:
run_cmd('mummer -maxmatch -l 80 ' + reconstr + ' ' + curr_ref + ' > ' + reconstr_per)
tester.analyzer(reconstr_per,reconstr_log,exp_file,N)
run_cmd('mummer -maxmatch -l 80 ' + curr_ref + ' ' + reconstr + ' > ' + reconstr_rev_per)
tester.reverse_analyzer(reconstr_rev_per,reconstr_rev_log,reconstr,N)
else:
run_cmd(python_path + ' ' + shannon_dir + 'parallel_blat_python.py ' + reconstr + ' ' + curr_ref + ' ' + reconstr_per)
tester.analyzer_blat_noExp(reconstr_per,reconstr_log,exp_file,N)
if false_positive:
tester.false_positive(reconstr,reconstr_per,reconstr_rev_log)
def run_MB_SF(arguments, inMem=False, contigs=[], weights=[], rps=[]):
print(arguments)
inDisk = not inMem
arguments = arguments.strip().split()
L = 100
N = 8743351
sn = ''
sparsity = 0.5
start_loc = 1
stop_loc = 120000000
paired_end = 0
add_errors = 1
double_stranded = 0
sim = 0
to_set_exp = 0
generate_reads = 0
trimmomatic = 0 #currently not enabled
run_seecer = 0
run_jellyfish = 0 # runs jellyfish to get kmers
run_extension_corr = 0 # runs contig based error correction to filter k1mers used to build kmer graph
run_cpp = 0 # builds condensed kmer graph
mb = 0 # runs multibridging
sparse_flow = 0
parallelize_sf = 0
generate_ref = 0
compare_ans = 0 # compares reconstructed transcripts to reference transcripts to measure performance of assembler
run_trinity = 0 # Runs a competing algorithm trinity
compare_trinity = 0
plots = 0
plots_express = 0
run_rsem_eval = 0
run_cuffinks = 0 # Runs a competing algorithm cufflinks
compare_cufflinks = 0
compare_soap = 0
compare_oasis = 0
compare_trans = 0
false_positive = 0
bowtie = 0
extract_bam = 0
oracle_set = 0
err_string = ' '
pairedend_string = ' '
mb_string = ' '
trinity_string = ' '
jellyfish_dir = ' jellyfish'
jellyfish_kmer_cutoff = 1
seecer_dir = ' /data/sreeramk/packages/SEECER-0.1.3/SEECER/bin/run_seecer.sh'
K_value = 24
blat = 1
# ----------------------------------------------------------------------------------
# Sets parameters from terminal
sample_name = None
filter_FP_flag = False
shannon_dir = ''
only_k1 = ' --only_k1 ' #Default: write only k1mers
only_reads = False #default: only_reads = false
nJobs = 1
python_path = 'python'
n_inp = arguments
if len(n_inp) > 1:
sample_name = arguments[0]
if '--run_alg' in n_inp:
mb = 1
sparse_flow = 1
if '--ds' in n_inp:
double_stranded = 1
if '--paired_end' in n_inp:
paired_end = 1
if '--compare' in n_inp:
compare_ans = 1
if '--kmer_size' in n_inp:
K_value = int(n_inp[n_inp.index('--kmer_size') + 1])
if '--only_reads' in n_inp:
only_reads = True
run_jellyfish = 1
run_extension_corr = 1
if '--nJobs' in n_inp:
nJobs = int(n_inp[n_inp.index('--nJobs') + 1])
if '--both' in n_inp:
only_k1 == ' ' #Dont write only k1mers
#print(K_value)
if '--dir_name' in n_inp:
directory_name = n_inp[n_inp.index('--dir_name') + 1]
if '--shannon_dir' in n_inp:
shannon_dir = n_inp[n_inp.index('--shannon_dir') + 1]
if '--python_path' in n_inp:
python_path = n_inp[n_inp.index('--python_path') + 1]
if '--filter_FP' in n_inp and paired_end:
filter_FP_flag = True
if paired_end:
F = 350 #Fragment size
F_sd = 0 #Fragment size Standard Deviation
sn = sn + '_F_' + str(F)
pairedend_string = ' -p ' + str(F) + ',' + str(F_sd) + ' '
else:
F = L
if add_errors:
error_rate = 0.01
err_string = ' -r ' + str(error_rate) + ' '
sn = sn + '_ERR'
mb_string += ' -e '
if double_stranded:
sn = sn + '_DS'
ds_string = ' '
#mb_string += ' -d '
else:
ds_string = ' --stranded '
trinity_string += ' --SS_lib_type FR '
def run_cmd(s1):
os.system(s1)
sample_output_name = sample_name
base_dir = ''
bed_file = ' ./Genome/GSE51861_isoform.bed'
ref_file = ' ./Genome/hg19.fa' # reference chromosome
exp_file = sample_name + 'algo_input/random_out.exp'
reads_file = sample_name + 'algo_input/reads'
if paired_end:
reads_string = reads_file + '_1.fasta ' + reads_file + '_2.fasta '
else:
reads_string = reads_file + '.fasta '
timer = {}
timer['start'] = time.time()
if not os.path.exists(sample_name + 'algo_input'):
os.makedirs(sample_name + 'algo_input')
if not os.path.exists(sample_output_name + 'algo_output'):
os.makedirs(sample_output_name + 'algo_output')
if not os.path.exists(sample_output_name + 'intermediate'):
os.makedirs(sample_output_name + 'intermediate')
'''if mb or sparse_flow:
os.system('cp *.py ' + sample_output_name + 'algo_output/')'''
if trimmomatic:
run_cmd(
'java -jar /home/sreeramkannan/Packages/trinityrnaseq_r20131110/trinity-plugins/Trimmomatic-0.30/trimmomatic.jar SE -phred33 SRR453566_1.fastq reads_trimmomatic.fastq ILLUMINACLIP:/home/sreeramkannan/Packages/trinityrnaseq_r20131110/trinity-plugins/Trimmomatic-0.30/adapters/TruSeq2-SE.fa:2:30:10 LEADING:20 TRAILING:20 SLIDINGWINDOW:4:30 MINLEN:75 CROP:75 TOPHRED64'
)
run_cmd(
'java -jar /home/sreeramkannan/Packages/trinityrnaseq_r20131110/trinity-plugins/Trimmomatic-0.30/trimmomatic.jar PE -phred33 reads_1.fastq reads_2.fastq reads_trim_1.fastq reads_trim_UP1.fastq reads_trim_2.fastq reads_trim_UP2.fastq LEADING:20 TRAILING:20 SLIDINGWINDOW:4:30 MINLEN:50 CROP:50 TOPHRED64'
)
if run_jellyfish:
run_jfs = ' '
if double_stranded:
run_jfs += ' -C '
#run_cmd('rm '+sample_name+'algo_input/jelly*') #Remove old jellyfish files
run_cmd(jellyfish_dir + ' count -m ' + str(K_value + 1) + run_jfs +
' -o ' + sample_name +
'algo_input/jellyfish_p1_output -s 20000000 -c 4 -t ' +
str(nJobs) + ' ' + reads_string)
'''if os.path.isfile(sample_name+'algo_input/jellyfish_p1_output_1'):
run_cmd(jellyfish_dir+' merge -o '+ sample_name+'algo_input/jellyfish_p1_output.jf ' + sample_name+'algo_input/jellyfish_p1_output\_*')
else:
run_cmd('mv ' + sample_name+'algo_input/jellyfish_p1_output_0 ' +sample_name+'algo_input/jellyfish_p1_output.jf')'''
run_cmd(jellyfish_dir + ' dump -c -t -L ' +
str(jellyfish_kmer_cutoff) + ' ' + sample_name +
'algo_input/jellyfish_p1_output > ' + sample_name +
'algo_input/k1mer.dict_org')
if (not run_extension_corr) and double_stranded:
tester.double_strandify(sample_name + 'algo_input/k1mer.dict_org',
sample_name + 'algo_input/k1mer.dict')
if (not run_extension_corr) and (not double_stranded):
run_cmd('mv ' + sample_name + 'algo_input/k1mer.dict_org ' +
sample_name + 'algo_input/k1mer.dict')
if run_extension_corr:
if double_stranded:
str_ec = ' -d '
else:
str_ec = ' '
run_cmd(python_path + ' ext_corr.py ' + str_ec + sample_name +
'algo_input/k1mer.dict_org ' + sample_name +
'algo_input/k1mer.dict 3 75')
'''if run_jellyfish or run_extension_corr:
run_cmd('python kp1mer_to_ kmer.py ' + sample_name+'algo_input/k1mer.dict ' + sample_name+'algo_input/kmer.dict')'''
if run_cpp:
run_cmd('tr \'\\t\' \'\\n\' <' + sample_name +
'algo_input/kmer.dict > ' + sample_name +
'algo_input/kmer.dict_2l ')
run_cmd('tr \'\\t\' \'\\n\' <' + sample_name +
'algo_input/k1mer.dict > ' + sample_name +
'algo_input/k1mer.dict_2l ')
run_cmd('./condenser ' + sample_name + 'algo_input/kmer.dict_2l ' +
sample_name + 'algo_input/k1mer.dict_2l ' + sample_name +
'algo_input/' + ' ' + str(K_value) + ' | tee ' + sample_name +
'_cpp_terminal_output.txt')
with open(sample_name + '_terminal_output.txt', 'w') as f7:
f7.write(" \n")
if inDisk and mb:
#run_cmd('rm '+sample_output_name+'intermediate/*')
jf_s = ' '
cpp_s = ' '
use_jellyfish = 1
use_cpp = 0 #force set parameter for jellyfish
if use_jellyfish:
jf_s = ' ' + sample_name + 'algo_input/kmer.dict ' + sample_name + 'algo_input/k1mer.dict '
if use_cpp:
cpp_s = '-c ' + sample_name + 'algo_input/nodes.txt ' + sample_name + 'algo_input/edges.txt '
if not paired_end:
run_cmd(python_path + ' ' + shannon_dir +
'multibridging.py -f --kmer=' + str(K_value) + mb_string +
only_k1 + jf_s + cpp_s + reads_file + '.fasta ' +
sample_output_name + 'intermediate ' + ' | tee ' +
sample_name + '_terminal_output.txt'
) # ' 2>&1 | tee ./' + sample_name + 'algo_input/log.txt')
else:
run_cmd(python_path + ' ' + shannon_dir +
'multibridging.py -f --kmer=' + str(K_value) + mb_string +
only_k1 + jf_s + cpp_s + reads_file + '_1.fasta ' +
reads_file + '_2.fasta ' + sample_output_name +
'intermediate ' + ' | tee ' + sample_name +
'_terminal_output.txt'
) # 2>&1 | tee ./' + sample_name + 'algo_input/log.txt')
elif inMem and mb:
jf_s = ''
cpp_s = ''
#In Memory
if paired_end:
multibridging.main(
'-f --kmer=' + str(K_value) + mb_string + only_k1 + jf_s +
cpp_s + reads_file + '_1.fasta ' + reads_file + '_2.fasta ' +
sample_output_name + 'intermediate ', inMem, contigs, weights,
rps)
else:
multibridging.main(
'-f --kmer=' + str(K_value) + mb_string + only_k1 + jf_s +
cpp_s + reads_file + '.fasta ' + sample_output_name +
'intermediate ', inMem, contigs, weights, rps)
timer['after_mb'] = time.time()
#timer['for_mb'] = timer['after_mb'] - timer['after_gen_reads']
if sparse_flow:
reconstr_file = sample_output_name + 'algo_output/reconstructed.fasta'
#run_cmd('rm '+sample_output_name+'algo_output/reconstructed_comp_*.fasta')
#run_cmd('rm '+sample_output_name+'algo_output/reconstructed.fasta')
run_cmd(python_path + ' ' + shannon_dir + 'algorithm_SF.py -1 ' +
sample_output_name)
ncomp = 0
iteration_string = " "
while os.path.isfile(sample_output_name + 'intermediate/nodes' +
str(ncomp) + '.txt'):
if 0: #ncomp==0: and ncomp!=2: #testing purpose
ncomp += 1
continue
print('Component:', ncomp)
if not parallelize_sf:
os.system(
python_path + ' ' + shannon_dir + 'algorithm_SF.py ' +
str(ncomp) + ' ' + sample_output_name
) # + ' | tee ' + sample_name + '_' + str(ncomp) + '_terminal_output.txt')
iteration_string += str(ncomp) + " "
ncomp = ncomp + 1
if parallelize_sf:
os.system('parallel ' + python_path + ' ' + shannon_dir +
'algorithm_SF.py {} ' + sample_output_name + " ::: " +
iteration_string)
os.system("cat " + sample_output_name +
'algo_output/reconstructed_comp_*.fasta' + " >> " +
reconstr_file)
#filter_trans(sample_output_name+'algo_output/reconstructed.fasta', sample_output_name+'algo_output/reconstructed_short.fasta', 200)
if sparse_flow:
if os.path.exists(directory_name + "/before_sp_log.txt"):
f_log = open(directory_name + "/before_sp_log.txt", 'a')
else:
f_log = open(directory_name + "/before_sp_log.txt", 'w')
num_transcripts = 0
with open(sample_output_name + "algo_output/reconstructed.fasta",
'r') as reconstructed_transcripts:
num_transcripts = len(reconstructed_transcripts.readlines())
f_log.write(
str(time.asctime()) + ": " + sample_output_name +
" has completed: " + str(num_transcripts) + " transcripts" + "\n")
print(
str(time.asctime()) + ": " + sample_output_name +
" has completed: " + str(num_transcripts) + " transcripts")
f_log.close()
if filter_FP_flag:
reads_1 = sample_name + 'algo_input/reads_1.fasta'
reads_2 = sample_name + 'algo_input/reads_2.fasta'
rec_fasta = sample_name + "algo_output/reconstructed.fasta"
out_dir = sample_name + "algo_output/"
filter_FP.filter_FP(rec_fasta, reads_1, reads_2, out_dir)
timer['after_sp'] = time.time()
#timer['for_sp'] = timer['after_sp'] - timer['after_mb']
if compare_ans:
curr_ref = sample_output_name + 'algo_output/reference.fasta'
reconstr = sample_output_name + 'algo_output/reconstructed.fasta'
all_seq = sample_output_name + 'algo_output/all_sequences.fasta'
reconstr_per = sample_output_name + 'algo_output/reconstr_per.txt'
reconstr_rev_per = sample_output_name + 'algo_output/reconstr_rev_per.txt'
reconstr_log = sample_output_name + 'algo_output/reconstr_log.txt'
reconstr_rev_log = sample_output_name + 'algo_output/reconstr_rev_log.txt'
all_seq_per = sample_output_name + 'algo_output/all_seq_per.txt'
self_repeats = sample_output_name + 'algo_output/self_repeats.txt'
if not blat:
run_cmd('mummer -maxmatch -l 80 ' + reconstr + ' ' + curr_ref +
' > ' + reconstr_per)
tester.analyzer(reconstr_per, reconstr_log, exp_file, N)
run_cmd('mummer -maxmatch -l 80 ' + curr_ref + ' ' + reconstr +
' > ' + reconstr_rev_per)
tester.reverse_analyzer(reconstr_rev_per, reconstr_rev_log,
reconstr, N)
else:
run_cmd(python_path + ' ' + shannon_dir +
'parallel_blat_python.py ' + reconstr + ' ' + curr_ref +
' ' + reconstr_per)
tester.analyzer_blat_noExp(reconstr_per, reconstr_log, exp_file, N)
if false_positive:
tester.false_positive(reconstr, reconstr_per, reconstr_rev_log)
timer['for_ref'] = timer['after_generate_ref'] - timer['after_sp']
if compare_ans:
curr_ref = sample_output_name + 'algo_output/reference.fasta'
reconstr = sample_output_name + 'algo_output/reconstructed.fasta'
all_seq = sample_output_name + 'algo_output/all_sequences.fasta'
reconstr_per = sample_output_name + 'algo_output/reconstr_per.txt'
reconstr_rev_per = sample_output_name + 'algo_output/reconstr_rev_per.txt'
reconstr_log = sample_output_name + 'algo_output/reconstr_log.txt'
reconstr_rev_log = sample_output_name + 'algo_output/reconstr_rev_log.txt'
all_seq_per = sample_output_name + 'algo_output/all_seq_per.txt'
self_repeats = sample_output_name + 'algo_output/self_repeats.txt'
if not blat:
run_cmd('mummer -maxmatch -l 80 ' + reconstr + ' ' + curr_ref + ' > ' +
reconstr_per)
tester.analyzer(reconstr_per, reconstr_log, exp_file, N)
run_cmd('mummer -maxmatch -l 80 ' + curr_ref + ' ' + reconstr + ' > ' +
reconstr_rev_per)
tester.reverse_analyzer(reconstr_rev_per, reconstr_rev_log, reconstr,
N)
else:
run_cmd(python_path + ' ' + shannon_dir + 'parallel_blat_python.py ' +
reconstr + ' ' + curr_ref + ' ' + reconstr_per)
tester.analyzer_blat_noExp(reconstr_per, reconstr_log, exp_file, N)
if false_positive:
tester.false_positive(reconstr, reconstr_per, reconstr_rev_log)
if run_trinity or compare_trinity:
curr_ref = sample_output_name + 'algo_output/reference.fasta'
run_cmd('mkdir ' + sample_output_name + 'algo_output/Trinity/')
trinity_per = sample_output_name + 'algo_output/Trinity/trinity_per.txt'