def print_intermediate_results(clusters, cluster_seq_origin, args, iter_nr):
path = args.outfolder + "/{0}".format(iter_nr)
help_functions.mkdir_p(path)
outfile = open(os.path.join(path, "pre_clusters.csv"), "w")
nontrivial_cluster_index = 0
for c_id, all_read_acc in sorted(clusters.items(),
key=lambda x: len(x[1]),
reverse=True):
for r_acc in all_read_acc:
outfile.write("{0}\t{1}\n".format(
c_id, "_".join([item for item in r_acc.split("_")[:-1]])))
if len(all_read_acc) > 1:
nontrivial_cluster_index += 1
print("Nr clusters larger than 1:", nontrivial_cluster_index
) #, "Non-clustered reads:", len(archived_reads))
print("Nr clusters (all):",
len(clusters)) #, "Non-clustered reads:", len(archived_reads))
origins_outfile = open(os.path.join(path, "cluster_origins.csv"), "w")
for cl_id, all_read_acc in sorted(clusters.items(),
key=lambda x: len(x[1]),
reverse=True):
read_cl_id, b_i, acc, c_seq, c_qual, score, error_rate = cluster_seq_origin[
cl_id]
origins_outfile.write("{0}\t{1}\t{2}\t{3}\t{4}\t{5}\n".format(
read_cl_id, acc, c_seq, c_qual, score, error_rate))
outfile.close()
origins_outfile.close()
def polish_sequences(centers, args):
print("Saving spoa references to files:", os.path.join(args.outfolder, "consensus_reference_X.fasta"))
# printing output from spoa and grouping reads
# to_polishing = []
if args.medaka:
polishing_pattern = os.path.join(args.outfolder, "medaka_cl_id_*")
elif args.racon:
polishing_pattern = os.path.join(args.outfolder, "racon_cl_id_*")
for folder in glob.glob(polishing_pattern):
shutil.rmtree(folder)
spoa_pattern = os.path.join(args.outfolder, "consensus_reference_*")
for file in glob.glob(spoa_pattern):
os.remove(file)
for i, (nr_reads_in_cluster, c_id, center, all_reads) in enumerate(centers):
# print('lol',c_id,center)
spoa_center_file = os.path.join(args.outfolder, "consensus_reference_{0}.fasta".format(c_id))
f = open(spoa_center_file, "w")
f.write(">{0}\n{1}\n".format("consensus_cl_id_{0}_total_supporting_reads_{1}".format(c_id, nr_reads_in_cluster), center))
f.close()
all_reads_file = os.path.join(args.outfolder, "reads_to_consensus_{0}.fastq".format(c_id))
f = open(all_reads_file, "w")
for fasta_file in all_reads:
reads = { acc : (seq, qual) for acc, (seq, qual) in help_functions.readfq(open(fasta_file, 'r'))}
for acc, (seq, qual) in reads.items():
f.write("@{0}\n{1}\n{2}\n{3}\n".format(acc, seq, "+", qual))
f.close()
# to_polishing.append( (nr_reads_in_cluster, c_id, spoa_center_file, all_reads_file) )
if args.medaka:
print("running medaka on spoa reference {0}.".format(c_id))
# for (nr_reads_in_cluster, c_id, spoa_center_file, all_reads_file) in to_polishing:
polishing_outfolder = os.path.join(args.outfolder, "medaka_cl_id_{0}".format(c_id))
help_functions.mkdir_p(polishing_outfolder)
run_medaka(all_reads_file, spoa_center_file, polishing_outfolder, "1", args.medaka_model)
print("Saving medaka reference to file:", os.path.join(args.outfolder, "medaka_cl_id_{0}/consensus.fasta".format(c_id)))
l = open(os.path.join(polishing_outfolder, "consensus.fasta"), 'r').readlines()
center_polished = l[1].strip()
centers[i][2] = center_polished
elif args.racon:
print("running racon on spoa reference {0}.".format(c_id))
# for (nr_reads_in_cluster, c_id, spoa_center_file, all_reads_file) in to_polishing:
polishing_outfolder = os.path.join(args.outfolder, "racon_cl_id_{0}".format(c_id))
help_functions.mkdir_p(polishing_outfolder)
run_racon(all_reads_file, spoa_center_file, polishing_outfolder, "1", args.racon_iter)
print("Saving racon reference to file:", os.path.join(args.outfolder, "racon_cl_id_{0}/consensus.fasta".format(c_id)))
l = open(os.path.join(polishing_outfolder, "consensus.fasta"), 'r').readlines()
center_polished = l[1].strip()
centers[i][2] = center_polished
f.close()
return centers
logfile.close()
print("Sorted all reads in {0} seconds.".format(time() - start) )
return reads_sorted_outfile.name
if __name__ == '__main__':
parser = argparse.ArgumentParser(description="Evaluate pacbio IsoSeq transcripts.")
parser.add_argument('--fastq', type=str, default=False, help='Path to consensus fastq file(s)')
parser.add_argument('--flnc', type=str, default=False, help='The flnc reads generated by the isoseq3 algorithm (BAM file)')
parser.add_argument('--ccs', type=str, default=False, help='Path to lima demultiplexed BAM file')
parser.add_argument('--outfile', type=str, default=None, help='A fasta file with transcripts that are shared between samples and have perfect illumina support.')
parser.add_argument('--k', type=int, default=15, help='kmer size')
args = parser.parse_args()
if (args.fastq and (args.flnc or args.ccs)):
print("Either (1) only a fastq file, or (2) a ccs and a flnc file should be specified. ")
sys.exit()
if (args.flnc != False and args.ccs == False ) or (args.flnc == False and args.ccs != False ):
print("qt-clust needs both the ccs.bam file produced by ccs and the flnc file produced by isoseq3 cluster. ")
sys.exit()
if len(sys.argv)==1:
parser.print_help()
sys.exit()
path_, file_prefix = os.path.split(args.outfile)
help_functions.mkdir_p(path_)
main(args)