def main(args):
ref = args.ref
r1 = args.r1
r2 = args.r2
prefix = args.prefix
threads = args.threads
stats = {}
fastqqc = ps.qc_fastq(prefix,r1,r2)
stats["fastq_mean_read_len"] = fastqqc.mean_read_len
stats["fastq_read_num"] = fastqqc.read_num
fastq = ps.fastq(prefix,ref,r1,r2,threads=threads)
fastq.illumina(mapper="bowtie2")
bam_file = "%s.bam" % prefix
bam = ps.bam(bam_file,prefix,ref)
bam.gbcf(vtype="snps",threads=threads,call_method=args.call_method)
bamqc = bam.get_bam_qc()
cov_plot = "%s.cov.png" % (prefix)
bamqc.plot_cov("Chromosome",cov_plot)
stats["bam_pct_reads_mapped"] = bamqc.pct_reads_mapped
stats["bam_med_dp"] = bamqc.med_dp
stats["bam_depth_10"] = bamqc.genome_cov[10]
stats["bam_depth_5"] = bamqc.genome_cov[5]
json.dump(stats,open("%s.stats.json" % prefix,"w"))
O = open("%s.log"%prefix,"w")
for x in ["fastq_mean_read_len","fastq_read_num","bam_pct_reads_mapped","bam_med_dp","bam_depth_5","bam_depth_10"]:
O.write("%s\t%s\n" % (x,stats[x]))
O.close()
def main(args): bam = ps.bam(bam_file=args.bam,ref_file=args.ref,prefix=args.prefix,threads=args.threads) if args.high_cov_as_missing: bamqc = bam.get_bam_qc() max_dp = bamqc.med_dp*3 else: max_dp = None bam.gbcf(threads=args.threads,max_dp=max_dp,platform=args.platform,primers=args.primers,call_method=args.method,vtype=args.vtype,min_dp=args.min_dp,mpileup_options=args.mpileup_options)
def main(args):
bam = ps.bam(bam_file=args.bam,
ref_file=args.ref,
prefix=args.prefix,
threads=args.threads)
bam.gbcf(threads=args.threads,
platform=args.platform,
primers=args.primers,
call_method=args.method,
vtype=args.vtype,
min_dp=args.min_dp)
def main(args):
bam = ps.bam(args.bam, args.prefix, args.ref, threads=args.threads)
bcf = bam.call_variants(call_method=args.call_method,
gff_file=args.gff,
bed_file=args.bed,
mixed_as_missing=True,
threads=args.threads,
min_dp=args.min_depth)
csq = bcf.load_csq(ann_file=args.ann, changes=True)
tmp_bcf = "%s.missing.bcf" % args.prefix
missing_pos = ps.get_missing_positions(tmp_bcf)
outfile = "%s.results.json" % args.prefix
results = {"variants": {}, "missing": missing_pos}
for gene in csq:
results["variants"][gene] = []
for var in csq[gene]:
results["variants"][gene].append(var.values()[0])
json.dump(results, open(outfile, "w"))
def main(args):
bam = ps.bam(args.bam,args.prefix,args.ref,threads=args.threads)
bcf = bam.call_variants(call_method=args.call_method,gff_file=args.gff,bed_file=args.bed,mixed_as_missing=False,threads=args.threads,min_dp=args.min_depth)
csq = bcf.load_csq_alt(ann_file=args.ann,changes=True)
tmp_bcf = "%s.missing.bcf" % args.prefix
missing_pos = ps.get_missing_positions(tmp_bcf)
outfile = "%s.results.json" % args.prefix
results = {"variants":[],"missing":missing_pos}
for sample in csq:
results["variants"] = csq[sample]
if args.barcode:
mutations = bam.get_bed_gt(args.barcode)
barcode = ps.barcode(mutations,"lineages.bed")
results["barcode"] = barcode
bcf.bed_consensus(args.bed,args.ref)
json.dump(results,open(outfile,"w"))
def main(args):
bam = ps.bam(bam_file=args.bam,
ref_file=args.ref,
prefix=args.prefix,
threads=args.threads)
if args.high_cov_as_missing:
bamqc = bam.get_bam_qc()
max_dp = bamqc.med_dp * 3
else:
max_dp = None
bam.gbcf(threads=args.threads,
max_dp=max_dp,
platform=args.platform,
primers=args.primers,
call_method=args.method,
vtype=args.vtype,
min_dp=args.min_dp,
mpileup_options=args.mpileup_options)
def main(args):
bam = ps.bam(args.bam, args.prefix, args.ref, threads=args.threads)
bcf = bam.call_variants(call_method=args.call_method,
gff_file=args.gff,
bed_file=args.bed,
mixed_as_missing=False,
threads=args.threads,
min_dp=args.min_depth)
csq = bcf.load_csq_alt(ann_file=args.ann, changes=True)
tmp_bcf = "%s.missing.bcf" % args.prefix
missing_pos = ps.get_missing_positions(tmp_bcf)
outfile = "%s.results.json" % args.prefix
results = {"variants": [], "missing": missing_pos}
for sample in csq:
results["variants"] = csq[sample]
if args.barcode:
mutations = bam.get_bed_gt(args.barcode)
barcode = ps.barcode(mutations, "lineages.bed")
results["barcode"] = barcode
if args.seq:
bcf.bed_consensus(args.bed, args.ref)
json.dump(results, open(outfile, "w"))
prefix = sys.argv[4]
threads = sys.argv[5]
stats = {}
fastqqc = ps.qc_fastq(prefix,r1,r2)
stats["fastq_mean_read_len"] = fastqqc.mean_read_len
stats["fastq_read_num"] = fastqqc.read_num
fastq = ps.fastq(prefix,ref,r1,r2,threads=threads)
fastq.illumina(mapper="minimap2")
bam_file = "%s.bam" % prefix
bam = ps.bam(bam_file,prefix,ref)
bam.gbcf(vtype="snps",threads=threads)
bamqc = bam.get_bam_qc()
cov_plot = "%s.cov.png" % (prefix)
bamqc.plot_cov("Chromosome",cov_plot)
stats["bam_pct_reads_mapped"] = bamqc.pct_reads_mapped
stats["bam_med_dp"] = bamqc.med_dp
stats["bam_depth_10"] = bamqc.genome_cov[10]
stats["bam_depth_5"] = bamqc.genome_cov[5]
json.dump(stats,open("%s.stats.json" % prefix,"w"))
O = open("%s.log"%prefix,"w")
for x in ["fastq_mean_read_len","fastq_read_num","bam_pct_reads_mapped","bam_med_dp","bam_depth_5","bam_depth_10"]:
O.write("%s\t%s\n" % (x,stats[x]))
O.close()
stats["fastq_read_num"] = fastqqc.read_num
fr1, fr2, tmp = fastqqc.run_centrifuge("/opt/storage2/jody/software/p+h+v",
mtb_tax, threads)
stats["centrifuge_top_hit"] = tmp[0]
stats["centrifuge_pct_reads"] = tmp[1]
newfastqqc = ps.qc_fastq(prefix, fr1, fr2, threads=threads)
fastq = ps.fastq(prefix, ref, fr1, fr2, threads=threads)
fastq.illumina(mapper="bowtie2")
bam_file = "%s.bam" % prefix
bam = ps.bam(bam_file, prefix, ref, threads=threads)
bam.gbcf(vtype="snps", threads=threads, call_method="low")
bamqc = bam.get_bam_qc()
cov_plot = "%s.cov.png" % (prefix)
bamqc.plot_cov("Chromosome", cov_plot)
stats["bam_pct_reads_mapped"] = bamqc.pct_reads_mapped
stats["bam_med_dp"] = bamqc.med_dp
stats["bam_depth_10"] = bamqc.genome_cov[10]
stats["bam_depth_5"] = bamqc.genome_cov[5]
json.dump(stats, open("%s.stats.json" % prefix, "w"))
O = open("%s.log" % prefix, "w")
for x in [
"fastq_mean_read_len", "fastq_read_num", "centrifuge_top_hit",
"centrifuge_pct_reads", "bam_pct_reads_mapped", "bam_med_dp",
fr1,fr2,tmp = fastqqc.run_centrifuge("/opt/storage2/jody/software/p+h+v",mtb_tax,threads)
stats["centrifuge_top_hit"] = tmp[0]
stats["centrifuge_pct_reads"] = tmp[1]
newfastqqc = ps.qc_fastq(prefix,fr1,fr2,threads=threads)
fastq = ps.fastq(prefix,ref,fr1,fr2,threads=threads)
fastq.illumina(mapper="bowtie2")
bam_file = "%s.bam" % prefix
bam = ps.bam(bam_file,prefix,ref,threads=threads)
bam.gbcf(vtype="snps",threads=threads,call_method="low")
bamqc = bam.get_bam_qc()
cov_plot = "%s.cov.png" % (prefix)
bamqc.plot_cov("Chromosome",cov_plot)
stats["bam_pct_reads_mapped"] = bamqc.pct_reads_mapped
stats["bam_med_dp"] = bamqc.med_dp
stats["bam_depth_10"] = bamqc.genome_cov[10]
stats["bam_depth_5"] = bamqc.genome_cov[5]
json.dump(stats,open("%s.stats.json" % prefix,"w"))
O = open("%s.log"%prefix,"w")
for x in ["fastq_mean_read_len","fastq_read_num","centrifuge_top_hit","centrifuge_pct_reads","bam_pct_reads_mapped","bam_med_dp","bam_depth_5","bam_depth_10"]:
O.write("%s\t%s\n" % (x,stats[x]))
O.close()
