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Snakefile
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Snakefile
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def cfg_default( key, val):
if key not in config:
config[key] = val
def cfg_mandatory( key):
assert key in config, "{} is a mandatory field in config".format(key)
def cfg_optional( key):
pass
def cfg_internal( key):
assert key not in config, "{} is an internal parameter! Do not use.".format(key)
if "DEBUG" in config:
def temp(st):
return st
new_prep = True
assembler_binaries = {"minia":"minia","abyss":"abyss-pe","spades":"spades.py", "present":"ls"}
cfg_mandatory("path")
cfg_mandatory("reference")
cfg_mandatory("raw-data")
cfg_mandatory("input")
cfg_mandatory("population")
cfg_default("pamir_partition_per_thread",1000)
cfg_default("analysis-base","/analysis")
cfg_default("results-base","/results")
cfg_default("analysis","{}{}/{}".format(config["path"],config["analysis-base"],config["population"]))
cfg_default("results","{}{}/{}".format(config["path"],config["results-base"],config["population"]))
cfg_default("genotyping_flank_size",1000)
cfg_default("assembler","minia")
cfg_default("assembler_k", 64)
cfg_default("assembly_threads",62)
cfg_default("aligner_threads", 16)
cfg_default("other_threads",16)
cfg_default("repeatmasker_threads",63)
cfg_default("minia_min_abundance",5)
cfg_default("n_std_dev",3)
cfg_default("seq_ext", "fq.gz")
cfg_optional("pamir_min_contig_len")
cfg_optional("blastdb")
cfg_optional("DEBUG")
cfg_optional("centromeres")
sext = config["seq_ext"]
mrsfast_comp_param = "" if ".gz" not in sext else " --seqcomp "
path_names = {
"linkeddata" : "linked-data",
"remcor" : "pamir-remove-concordants",
"extass" : config["assembler"],
"blast" : "blast-filtering",
"lenfilter" : "length-filtering",
"pamoea" : "pamir-oea-processing",
"partition" : "pamir-partition",
"pamass" : "pamir-assembly",
"pamann" : "pamir-filtering",
"pamscv" : "pamir-setcover",
"pamref" : "pamir-flank-reference",
"pamgen" : "pamir-genotyping",
}
if "SCPA" in config:
SCPA = config["SCPA"]
else:
SCPA = "."
index = 0
for k,v in path_names.items():
path_names[k] = config["analysis"] + "/{:0>3d}-{}".format(index,v)
index+=1
def tool_exists(name):
from shutil import which
return which(name) is not None
def assert_tool(tool):
assert tool_exists(tool), tool + " not found in the PATH"
assert_tool(assembler_binaries[config["assembler"]])
def get_cram_name(wildcards):
orig_cram_name = config["input"][wildcards.sample][0]
extension = os.path.splitext(orig_cram_name)[1]
if extension not in [".bam", ".cram"]:
print("Input should be in bam or cram format.", file=sys.stderr)
sys.exit(1)
return path_names["linkeddata"] +"/"+ wildcards.sample + extension
def get_cram_index(wildcards):
cram_name = get_cram_name(wildcards)
extension = os.path.splitext(cram_name)[1]
extension = {".bam":".bai",".cram":".crai"}[extension]
return "{}{}".format(cram_name,extension)
rule make_results:
input:
html=config["results"]+"/index.html",
data_js=config["results"]+"/data.js",
summary_js=config["results"]+"/summary.js",
bams=expand("{results}/ind/{sample}/events.bam",results=config["results"],sample=config["input"].keys()),
bais=expand("{results}/ind/{sample}/events.bam.bai",results=config["results"],sample=config["input"].keys()),
bed=expand("{results}/ind/{sample}/events.bed",results=config["results"],sample=config["input"].keys()),
vcf=expand("{results}/ind/{sample}/events.vcf",results=config["results"],sample=config["input"].keys()),
fa=expand("{results}/events.fa",results=config["results"]),
fai=expand("{results}/events.fa.fai",results=config["results"]),
rm=expand("{results}/events.repeat.bed",results=config["results"]),
seq_stats=config["results"]+"/stats.js"
rule print_event_xml:
input:
bam=path_names["pamgen"]+"/{sample}/final.bam",
fasta=path_names["pamref"]+"/events_ref.fa",
bed =path_names["pamgen"]+"/{sample}/events_ins_pos.bed",
output:
dne =path_names["pamgen"]+"/{sample}/cfg.xml"
run:
with open(output.dne,'w') as out_hand:
genome_str = '<Global genome="{}" version="3">'
bam_str='<Resource name="Reads" path="{}"/>'
bed_str='<Resource name="Insertion Coordinates" path="{}"/>'
covtrack_str='<Track autoScale="true" clazz="org.broad.igv.sam.CoverageTrack" color="175,175,175" colorScale="ContinuousColorScale;0.0;19.0;255,255,255;175,175,175" fontSize="10" id="{}_coverage" name="Reads Coverage" snpThreshold="0.2" visible="true">'
seqtrack_str='<Track clazz="org.broad.igv.sam.AlignmentTrack" id="{}" name="Reads" visible="true" displayMode="SQUISHED" >'
bedtrack_str='<Track clazz="org.broad.igv.track.FeatureTrack" color="0,0,178" colorScale="ContinuousColorScale;0.0;1.0;255,255,255;0,0,178" fontSize="10" id="{}" name="Insertion Coordinates" visible="true"/>'
xml_lines = [
'<?xml version="1.0" encoding="UTF-8"?>',
genome_str.format(input.fasta),
'<Resources>',
bam_str.format(input.bam),
bed_str.format(input.bed),
'</Resources>',
'<Panel name="SeqPanel">',
covtrack_str.format(input.bam),
'<DataRange baseline="0.0" drawBaseline="true" flipAxis="false" maximum="20.0" minimum="0.0" type="LINEAR"/>',
'</Track>',
seqtrack_str.format(input.bam),
'<RenderOptions viewPairs="true"/>',
'</Track>',
bedtrack_str.format(input.bed),
'</Panel>',
# '<Panel name="RefPanel">',
# '<Track clazz="org.broad.igv.track.SequenceTrack" fontSize="10" id="Reference sequence" name="Reference sequence" visible="true"/>',
# bedtrack_str.format(input.bed),
# '</Panel>',
'<PanelLayout dividerFractions="0.006984866123399301,0.7558323632130385"/>',
'</Global>'
]
tabc=0;
tab="\t";
for line in xml_lines:
if "</" in line:
tabc-=1
print(tab*tabc,end="",file=out_hand)
print(line,file=out_hand)
if "<?" in line:
pass
else:
if "<" in line and "/>" not in line and "</" not in line:
tabc+=1
rule make_html:
output:
config["results"]+"/index.html",
params:
scpa=SCPA,
shell:
"cp {params.scpa}/scripts/index.html {output}"
rule move_bams:
input:
path_names["pamgen"]+"/{sample}/final.bam"
output:
config["results"]+"/ind/{sample}/events.bam"
shell:
"cp {input} {output}"
rule move_vcf:
input:
rem=config["results"] + "/rem.done",
vcf=path_names["pamgen"]+"/{sample}/final.vcf"
output:
config["results"]+"/ind/{sample}/events.vcf"
shell:
"cp {input.vcf} {output}"
rule move_bed:
input:
path_names["pamref"]+"/ind/{sample}/events_ins_pos.bed"
output:
config["results"]+"/ind/{sample}/events.bed"
shell:
"cp {input} {output}"
rule move_fa:
input:
path_names["pamref"]+"/events_ref.fa"
output:
config["results"]+"/events.fa"
shell:
"cp {input} {output}"
rule move_fai:
input:
path_names["pamref"]+"/events_ref.fa.fai"
output:
config["results"]+"/events.fa.fai"
shell:
"cp {input} {output}"
rule move_repeat_bed:
input:
path_names["pamref"]+"/events_ref.repeat.bed",
output:
config["results"]+"/events.repeat.bed"
shell:
"cp {input} {output}"
#chr13-69551766-747f 1000 1050 Cluster=1087545;Support=4;FLSUP=6;FRSUP=8;FSUP=14 chr13-69551766-747f 1006 1084 (TA)n::Simple_repeat 0 +
rule merge_repeat_beds:
input:
uniq=path_names["pamref"]+"/ind/{sample}/uniq_seq_ins.bed",
rep=path_names["pamref"]+"/ind/{sample}/repeat_overlap_ins.bed",
output:
temp(path_names["pamref"]+"/ind/{sample}/events_ins_pos_and_repeat.bed"),
shell:
"cat {input.uniq} {input.rep} | bedtools sort -i stdin > {output}"
rule non_repeat_bed:
input:
bed=path_names["pamref"]+"/ind/{sample}/events_ins_pos.bed",
rpt=path_names["pamref"]+"/events_ref.repeat.bed",
output:
temp(path_names["pamref"]+"/ind/{sample}/uniq_seq_ins.bed"),
params:
scpa=SCPA,
shell:
"bedtools intersect -b {input.rpt} -a {input.bed} -v | python {params.scpa}/scripts/process_unique.py > {output}"
rule repeat_bed:
input:
bed=path_names["pamref"]+"/ind/{sample}/events_ins_pos.bed",
rpt=path_names["pamref"]+"/events_ref.repeat.bed",
output:
temp(path_names["pamref"]+"/ind/{sample}/repeat_overlap_ins.bed"),
params:
scpa=SCPA,
shell:
"bedtools intersect -a {input.rpt} -b {input.bed} -wb | python {params.scpa}/scripts/process_repeats.py > {output}"
rule make_unique_repeats:
input:
path_names["pamref"]+"/events_ref.repeat.bed"
output:
path_names["pamref"]+"/unique_repeats.tsv"
shell:
"cat {input} | cut -f 4 | sed 's/::/\\t/g' | cut -f 2 | sort | uniq -c > {output}"
rule format_repeat_masking:
input:
"{sample}.fa.out"
output:
"{sample}.repeat.bed"
shell:
"cat {input} | awk 'BEGIN{{OFS=\"\\t\";}}NR>3{{gsub(\"C\",\"-\",$9);print $5,$6-1,$7,$10\"::\"$11,0,$9;}}' > {output}"
rule make_repeat_mask_gff:
input:
path_names["pamref"]+"/events_ref.fa"
#config["results"]+"/events.fa"
output:
path_names["pamref"]+"/events_ref.fa.out"
#config["results"]+"/events.fa.out"
threads:
config["repeatmasker_threads"]
shell:
"RepeatMasker -species human -pa {threads} {input}"
"""
{
"# of Primary Mappings": "1783597",
"# of Supp. Mappings": "2",
"Chimeric": "0",
"Concordant": "1749040",
"Discordant": "609",
"Mean": "499.50",
"OEA": "9509",
"Orphan": "24439",
"Range": "[454, 545]",
"Read Length Range": "[100, 100]",
"Std": "26.56",
"Total Number of Reads": "1783597"
}
"""
rule make_stats_js:
input:
expand(path_names["remcor"] + "/{sample}/{sample}.json",sample=config["input"].keys()),
output:
config["results"]+"/stats.js"
run:
import json
import sys
buff= []
short = {
"# of Primary Mappings": "p",
"# of Supp. Mappings": "s",
"Chimeric": "c",
"Concordant": "C",
"Discordant": "D",
"Mean": "m",
"OEA": "E",
"Orphan": "O",
"Range": "r",
"Read Length Range": "l",
"Std": "v",
"Total Number of Reads": "t"
}
for f in input:
with open( f , 'r') as hand:
end = f.rfind(".json")
start = f.rfind("/") + 1
sample = f[start:end]
jsn = json.load(hand)
parts = []
for k,v in jsn.items():
if k not in short:
continue
parts.append('"{}":"{}"'.format(short[k],v))
buff.append('"{}":{}'.format(sample,"{"+ ",".join(parts) + "}"))
with open(output[0], 'w') as hand:
print("/*{}*/".format(",".join([":".join([k,v]) for k,v in short.items()])),file=hand) # Short to proper comment
print("stats = ",end="",file=hand) # variable
print("{" + ",".join(buff) + "}",file=hand) # fields
rule make_data_js:
input:
expand(path_names["pamgen"]+"/{sample}/final.vcf",sample=config["input"].keys()),
output:
config["results"]+"/data.js"
run:
import json
import sys
populations = {}
cohort = config["population"]
sn = {"uuid" :"id","qual" :"q","genotype" :"g","Cluster" :"c","Support" :"p","FLSUP" :"flp","FRSUP" :"frp","FSUP" :"fsp","GLeft" :"L","GRight" :"T","GRef" :"R","GLRatio" :"glr","GRRatio" :"gtr","Sample" :"s", "unique_content": "u", "repeat_ranges": "r" }
unwanted_tag_list=["FLSUP","FRSUP","FSUP","GLRatio","GRRatio", "repeat_ranges", "unique_content"]
with open(output[0], 'w') as ohand:
print("/*\nid uuid\nq qual\ng genotype\nc Cluster\np Support\nL GLeft\nT GRight\nR GRef\ns Sample\n*/",file=ohand)
print("var mut_data = ",file=ohand)
for invcf in input:
sampleid = invcf.split("/")[-2]
if cohort not in populations:
populations[cohort] = {"individuals" : {}}
if sampleid not in populations[cohort]["individuals"]:
populations[cohort]["individuals"][sampleid] = {'events' : None}
variants = []
with open(invcf,'r') as ihand:
for line in ihand:
if line[0] == "#":
continue
fields = line.rstrip().split("\t")
variant = {}
variant["id"] = fields[2]
variant["q"] = "{:.1f}".format(float(fields[5]))
variant["g"] = fields[10]
info = fields[7].split(";")
for i in info:
parts = i.split("=")
if len(parts) == 2:
if parts[0] in unwanted_tag_list:
continue
else:
variant[sn[parts[0]]] = parts[1]
else:
variant[parts[0]] = ""
variants.append(variant)
populations[cohort]["individuals"][sampleid]["events"] = variants
ohand.write(json.dumps(populations))
ohand.write(";")
rule all_rem_temp_vcfs:
input:
vcf=expand(path_names["pamass"] +"/{sample}/all.vcf",sample=config["input"].keys())
output:
temp(config["results"] + "/rem.done"),
shell:
"rm -f " + path_names["pamass"] + "/*/T*; touch {output}"
rule make_summary_js:
input:
table=path_names["pamgen"]+"/table.tsv",
output:
config["results"]+"/summary.js"
run:
def sumall(l):
sm = 0
for i in l:
sm+=i
return sm
import sys
import json
length2counts = {}
repeats = {}
with open(output[0],'w') as ohand, open(input.table,'r') as ihand:
print("/*event\te\ncount\tc\nlength\tl\nrepeat_type\tr\nunique_content_percentage\tu\n*/",file=ohand)
print("var cohort_request=\"{}\"".format(config["population"]),file=ohand)
print("var cohort_size={}".format(len(config["input"].keys())),file=ohand)
print("var table_summary_file =[",file=ohand)
for line in ihand:
fields=line.rstrip().split("\t")
print(json.dumps({"e" : fields[1], "c" : str(int(float(fields[0]))), "l":len(fields[2]), "r":fields[3], "u":fields[4]}),file=ohand,end=",")
if fields[3] not in repeats:
repeats[fields[3]] = 1
length = int(len(fields[2])/5)*5
count = int(float(fields[0]))
if length not in length2counts:
length2counts[length] = []
length2counts[length].append(count)
print("];",file=ohand)
sorted_lens = sorted(length2counts.keys())
print("var length_labels = [",file=ohand)
print( ", ".join([str(x) for x in sorted_lens]),file=ohand,end=",")
print("];",file=ohand)
print("var unique_counts = [",file=ohand)
print( ", ".join([ str(len(length2counts[x])) for x in sorted_lens]),file=ohand,end=",")
print("];",file=ohand)
print("var total_counts = [",file=ohand)
print( ", ".join([ str(sumall(length2counts[x])) for x in sorted_lens]),file=ohand,end=",")
print("];",file=ohand)
print("var repeat_types = [",file=ohand)
reps = []
for line in repeats.keys():
reps.append("\"{}\"".format(line))
print(", ".join(reps),end="",file=ohand)
print("];",file=ohand)
rule annotate_repeats_in_vcf:
input:
bed=path_names["pamref"]+"/ind/{sample}/events_ins_pos_and_repeat.bed",
vcf=path_names["pamgen"]+"/{sample}/genotyped.vcf",
output:
vcf=path_names["pamgen"]+"/{sample}/final.vcf",
run:
bedl = []
vcfl = []
with open(input.vcf , 'r') as vhand, open(input.bed, 'r') as bhand, open(output.vcf, 'w') as ohand:
bedln = bhand.readline()
vcfln = vhand.readline()
while(bedln and vcfln):
while(vcfln[0] == "#"):
print(vcfln,end="",file=ohand)
vcfln = vhand.readline()
vcffields = vcfln.rstrip().split("\t")
bedfields = bedln.rstrip().split("\t")
bedl.append(bedfields)
vcfl.append(vcffields)
bedln = bhand.readline()
vcfln = vhand.readline()
bedl = sorted(bedl, key=lambda x: x[0])
vcfl = sorted(vcfl, key=lambda x: x[2])
for b,v in zip(bedl,vcfl):
print("\t".join(v[:8]),end=";",file=ohand)
bb = b[3].split(";")
print(bb[-2],bb[-1],sep=";",file=ohand,end="\t")
print("\t".join(v[8:]),file=ohand)
rule all_vis_table:
input:
expand(path_names["pamgen"]+"/{sample}/final.vcf",sample=config["input"].keys())
output:
path_names["pamgen"]+"/table.tsv"
run:
event_details = {}
events = {}
total_count = len(input)
for vcf in input:
my_id = vcf.split("/")[-2]
with open( vcf , 'r') as hand:
for line in hand:
if line[0] == "#":
continue
fields = line.rstrip().split("\t")
infocol = fields[7].split(";")
info = {}
for fi in infocol:
parts = fi.split("=")
if len(parts) == 1:
info[parts[0]] = ""
else:
info[parts[0]] = parts[1]
#print(info)
event_id = fields[2]
if event_id not in events:
events[event_id] = []
event_details[event_id] = (fields[2],fields[4][1:],",".join([x.split("(")[0] for x in info["repeat_ranges"].split(":")]), info["unique_content"])
if fields[-1] != "0/0" and fields[6] == "PASS":
events[event_id].append((my_id,fields[-1]))
with open( output[0], 'w') as hand:
for event,patients in events.items():
details = event_details[event]
cnt = float(len(patients))
if cnt < 1:
continue
print( "{}\t{}".format(cnt,"\t".join(details)), file=hand)
rule get_final_bam:
input:
bam=path_names["pamgen"]+"/{sample}/{sample}.bam",
orphan_bam=path_names["pamgen"]+"/{sample}/orphans.bam",
output:
orphan_bam=path_names["pamgen"]+"/{sample}/final.bam",
threads:
config["other_threads"]
shell:
"samtools merge {output} {input.bam} {input.orphan_bam} -c -@ {threads} && samtools index -@ {threads} {output}"
rule convert_vis_sam_to_bam:
input:
sam=path_names["pamgen"]+"/{sample}/{sample}.sam",
header=path_names["pamgen"]+"/{sample}/header.sam",
output:
temp(path_names["pamgen"]+"/{sample}/{sample}.bam"),
threads:
16
shell:
"cat {input.header} {input.sam} | samtools sort -m6G -@ {threads} > {output}"
rule make_rg_lines_for_header:
output:
temp(path_names["pamgen"]+"/rg.head"),
run:
with open(output[0], 'w') as hand:
categories = ["BreakPointSupport",
"BreakPointSupportOEA",
"BreakPointSupportOrphan",
"ReferenceSupport",
"FalseSupport",
"NoSupport"]
categories = categories + [ "DIS-{}".format(x) for x in categories]
for cat in categories:
print("@RG\tID:{0}\tLB:{0}".format(cat),file=hand)
rule genotype_vis:
input:
cram=get_cram_name,
cram_index=get_cram_index,
vcf=path_names["pamscv"]+"/{sample}/setcover-filtered.named.no-centro.vcf",
fasta=path_names["pamref"]+"/events_ref.fa",
read_stats=path_names["remcor"] +"/{sample}/{sample}.stats.json",
output:
sam=temp(path_names["pamgen"]+"/{sample}/{sample}.sam"),
vcf=temp(path_names["pamgen"]+"/{sample}/genotyped.vcf"),
head=temp(path_names["pamgen"]+"/{sample}/{sample}.header"),
bed =temp(path_names["pamref"]+"/ind/{sample}/events_ins_pos.bed"),
params:
ref=config["reference"],
rang=config["genotyping_flank_size"],
threads:
config["other_threads"]
run:
import json
with open(input.read_stats, 'r') as jhand:
read_stats =json.load(jhand)
rl = read_stats["read_len"]
min_frag = read_stats["tlen_min"]
max_frag = read_stats["tlen_max"]
genotype_dic = { 0 : "0/0", 1 : "1/0", 2 : "1/1"}
cmd="samtools view -H {} > {}".format(input.cram,output.head)
process = subprocess.Popen(cmd,shell=True);
process.communicate()
view_cmd="samtools view -T {} {}".format(params.ref,input.cram)
sort_cmd = "samtools sort -n | samtools view"
in_house_cmd = SCPA + "/pamir process_range {} {} {} {} {} {} {}"
id2seq = {}
with open(input.fasta,"r") as hand:
line = hand.readline()
while line:
fields = line.rstrip().split()
name = fields[0][1:]
line = hand.readline()
id2seq[name] = (line.rstrip(),fields[1],fields[2])
line = hand.readline()
with open(input.vcf,"r") as hand , open( output.sam, "w") as samhand, open(output.vcf, "w") as vcfhand, open(output.bed, "w") as bedhand:
line = hand.readline()
while line:
while line[0] == "#":
print(line.rstrip(),file=vcfhand)
line = hand.readline()
fields = line.rstrip().split("\t")
processes= []
ps = []
pm = []
vcfs = []
beds = []
for tid in range(threads):
while line and fields[6] != "PASS":
line = hand.readline()
fields = line.rstrip().split("\t")
if not line:
break
pos = int(fields[1])
start = pos - params.rang + 1
end = pos + params.rang - 1
seq = fields[4][1:]
vcfs.append(fields)
#fasta_cmd="cat {} | grep {} -A1".format(input.fasta, fields[2])
#ps.append( subprocess.Popen(fasta_cmd, shell=True, stdout=subprocess.PIPE))
ps.append(fields[2])
pm.append(view_cmd + " {}:{}-{}".format(fields[0],start+rl,end-rl) + "|" + in_house_cmd.format(pos,len(seq),params.rang,min_frag,max_frag,fields[2],"{}"))
line = hand.readline()
fields = line.rstrip().split("\t")
pf = []
for name,m in zip(ps,pm):
if name not in id2seq:
continue
tup = id2seq[name]
fasta = tup[0]
bedinfo = tup[1:]
beds.append("{}\t{}\t{}".format(name,bedinfo[0],int(bedinfo[0]) + int(bedinfo[1])))
pf.append(m.format(fasta))
for f in pf:
processes.append(subprocess.Popen(f, shell=True,stdout=subprocess.PIPE))
for bed,v,process in zip(beds,vcfs,processes):
stdout,stderr = process.communicate()
samlines = stdout.decode('utf-8').splitlines()
for l in samlines[1:]:
print(l,file=samhand)
print("\t".join(v[:8]),end=";",file=vcfhand)
#print(samlines[0])
left,right,ref = [int(x) for x in samlines[0].split("\t")]
if ref + left == 0:
left_ratio = -1
else:
left_ratio = (left - ref) / (left + ref)
if ref + right == 0:
right_ratio = -1
else:
right_ratio = (right - ref) / (right + ref)
lg = []
for ratio in [left_ratio, right_ratio]:
if ratio >= 0.3:
lg.append(2)
elif ratio <= -0.3:
lg.append(0)
else:
lg.append(1)
genotype = genotype_dic[min(lg)]
infoformat="GLeft={};GRight={};GRef={};GLRatio={:.2f};GRRatio={:.2f};Sample={}"
print( infoformat.format(left,right,ref,left_ratio,right_ratio,wildcards.sample),end="\t",file=vcfhand)
print( bed,end="\t",file=bedhand)
print( infoformat.format(left,right,ref,left_ratio,right_ratio,wildcards.sample),end="\n",file=bedhand)
print("\t".join(v[8:]),file=vcfhand,end="\t")
print("GT\t{}".format(genotype),file=vcfhand)
if not line:
break
rule get_insertions_sam_header:
input:
bam=path_names["pamgen"]+"/{sample}/orphans.bam",
output:
temp(path_names["pamgen"]+"/{sample}/header.sam"),
shell:
"samtools view {input} -H > {output}"
rule convert_orphans_to_bam:
input:
sam=path_names["pamgen"]+"/{sample}/orphans.sam",
rgs=path_names["pamgen"]+"/rg.head",
output:
bam=temp(path_names["pamgen"]+"/{sample}/orphans.bam"),
threads:
16
shell:
"cat <(samtools view -H {input.sam}) {input.rgs} <(samtools view {input.sam}) | samtools view -Shb | samtools sort -m4G -@ {threads} -o {output.bam}"
rule map_orphans_to_vis_fasta:
input:
fasta=path_names["pamref"]+"/events_ref.fa",
fasta_index=path_names["pamref"]+"/events_ref.fa.bwt",
fastq=path_names["remcor"] + "/{sample}/{sample}.orphan.canonical."+sext,
output:
sam=temp(path_names["pamgen"]+"/{sample}/orphans.sam"),
threads:
config["aligner_threads"]
params:
scpa=SCPA
shell:
"bwa mem -t {threads} {input.fasta} {input.fastq} -p | {params.scpa}/pamir process_orphan > {output}"
rule bwa_index:
input:
fasta="{any}.fa",
output:
index="{any}.fa.bwt",
shell:
"bwa index {input}"
rule merge_fastas:
input:
expand(path_names["pamref"]+"/ind/{sample}/events_ref.fa",sample=config["input"].keys())
output:
fasta=path_names["pamref"]+"/events_ref.fa",
fasta_index=path_names["pamref"]+"/events_ref.fa.fai",
fasta_lookup=path_names["pamref"]+"/events_ref.fa.lookup",
params:
scpa=SCPA,
shell:
"printf \"{input}\n\" | tr ' ' '\n' | python {params.scpa}/scripts/merge_refs.py {output.fasta_lookup} > {output.fasta} && samtools faidx {output.fasta}"
rule make_vis_fasta:
input:
vcf=path_names["pamscv"]+"/{sample}/setcover-filtered.named.no-centro.vcf",
output:
fasta=temp(path_names["pamref"]+"/ind/{sample}/events_ref.fa"),
params:
ref=config["reference"],
flank=config["genotyping_flank_size"],
run:
import subprocess
contig_sizes = {}
with open("{}.fai".format(params.ref), 'r') as fasta_index:
for line in fasta_index:
fields = line.split("\t")
contig_sizes[fields[0]] = int(fields[1])
with open(input['vcf'],'r') as hand, open(output["fasta"],"w+") as fast_hand:
for line in hand:
if line[0] == "#":
continue
fields = line.rstrip().split("\t")
if fields[6] != "PASS":
continue
# if fields[9] == "0/0":
# continue
ins_id = fields[2]
ch = fields[0]
pos = int(fields[1])
mid = params.flank
start = pos - params.flank
end = pos + params.flank
if start < 0:
mid = mid + start
start = 0
if end > contig_sizes[ch]:
end = contig_sizes[ch] - 1
cmd = "printf \"{}\\t{}\\t{}\\n\" | bedtools getfasta -fi {} -bed stdin".format(ch,start,end,params["ref"])
ins = fields[4][1:]
process = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE)
stdout,stderr = process.communicate()
stdout = stdout.decode('utf-8').splitlines()
#print("{}\t{}".format(cmd,fields[2]))
seq = stdout[-1]
seq = seq[:mid] + ins + seq[mid:]
print(">{} {} {}\n{}".format(ins_id, mid, len(ins),seq.rstrip()),file=fast_hand)
rule all_filtered_vcf:
input:
expand(path_names["pamscv"]+"/{sample}/setcover-filtered.vcf",sample=config["input"].keys())
output:
path_names["pamann"]+"/done"
shell:
"touch {output}"
if "centromeres" in config:
rule remove_centromeres_from_vcf:
input:
"{sample}.vcf",
output:
"{sample}.no-centro.vcf",
params:
centromeres=config["centromeres"],
shell:
"bedtools intersect -a {input} -b <(cat {params.centromeres} | sed 's/chr//') -v -header > {output}"
else:
rule mock_remove_centromeres_from_vcf:
input:
"{sample}.vcf",
output:
"{sample}.no-centro.vcf",
shell:
"cp {input} {output}"
rule rename_events:
input:
"{sample}.vcf"
output:
temp("{sample}.named.vcf")
run:
import hashlib
with open(input[0], 'r') as ihand, open(output[0], 'w') as ohand:
for line in ihand:
if( line[0] == "#"):
print(line.rstrip(), file=ohand)
continue
fields = line.rstrip().split("\t")
ho = hashlib.md5(fields[4].encode())
fields[2] = "-".join([fields[0],fields[1],ho.hexdigest()[:11]])
print( "\t".join(fields), file=ohand)
rule filter_by_setcover:
input:
smooth=path_names["pamscv"]+"/{sample}/smooth",
fvcf=path_names["pamann"]+"/{sample}/filtered.vcf",
output:
temp(path_names["pamscv"]+"/{sample}/setcover-filtered.vcf"),
params:
scpa=SCPA,
shell:
"python {params.scpa}/scripts/filter_by_setcover.py {input.smooth} {input.fvcf} {output}"
rule smoother:
input:
path_names["pamscv"]+"/{sample}/prep",
output:
temp(path_names["pamscv"]+"/{sample}/smooth"),
params:
scpa=SCPA
shell:
"{params.scpa}/pamir smoother {input} > {output}"
if new_prep:
rule prep_for_set_cover:
input:
fsc=path_names["pamann"] +"/{sample}/filtered.vcf",
sam=path_names["pamann"]+"/{sample}/seq.mrsfast.recalsorted.sam",
output:
temp(path_names["pamscv"]+"/{sample}/prep"),
params:
scpa=SCPA,
shell:
"python {params.scpa}/scripts/new_generate_setcover.py {input.sam} {input.fsc} {output}"
else:
rule prep_for_set_cover:
input:
fsc=path_names["pamann"] +"/{sample}/all.sorted.vcf_filtered_for_setcov.sorted",
sam=path_names["pamann"]+"/{sample}/seq.mrsfast.recalsorted.sam",
output:
temp(path_names["pamscv"]+"/{sample}/prep"),
params:
scpa=SCPA,
shell:
"python {params.scpa}/scripts/generate_setcover_input.py {input.fsc} {input.sam} {output}"
rule filter_vcf:
input:
vcf=path_names["pamass"] +"/{sample}/all.sorted.vcf",
fq=path_names["remcor"]+"/{sample}/{sample}.all_interleaved."+sext,
header=path_names["pamann"]+"/header.vcf",
statfile=path_names["remcor"]+"/{sample}/{sample}.stats.json",
output:
vcf=path_names["pamann"]+"/{sample}/filtered.vcf",
vcf_nh=temp(path_names["pamann"]+"/{sample}/filtered.vcf_nohead"),
sam=path_names["pamann"]+"/{sample}/seq.mrsfast.recalsorted.sam",
params:
ref=config["reference"],
tlen=1000,
wd=path_names["pamann"],
scpa=SCPA,
threads:
config["aligner_threads"]
shell:
"python {params.scpa}/scripts/filtering.py {input.vcf} {params.ref} {params.wd}/{wildcards.sample}/ {params.tlen} {threads} {input.fq} {input.statfile} {output.vcf_nh} {output.sam} && cat {input.header} {output.vcf_nh} > {output.vcf}"
rule sort_vcf:
input:
"{sample}.vcf"
output:
"{sample}.sorted.vcf"
params:
scpa=SCPA,
dupc=1,
shell:
"python {params.scpa}/scripts/sort_vcf.py {input} {output} {params.dupc}"
rule generate_vcf_header:
output:
path_names["pamann"]+"/header.vcf",
params:
ref=config["reference"],
run:
header_info = "".join(["##fileformat=VCFv4.2\n##FILTER=<ID=PASS,Description=\"All filters passed\">\n##reference={}\n##source=Pamir\n".format(params.ref),
"##INFO=<ID=Cluster,Number=1,Type=Integer,Description=\"ID of the cluster the variant is extracted from\">\n",
"##INFO=<ID=Support,Number=1,Type=Integer,Description=\"Number of reads/contigs supporting the contig\">\n",
"##INFO=<ID=SEQ,Number=1,Type=String,Description=\"Variant sequence\">\n",
"##INFO=<ID=FLSUP,Number=1,Type=Integer,Description=\"Number of left supporting reads in filtering\">\n",
"##INFO=<ID=FLRSUP,Number=1,Type=Integer,Description=\"Number of right supporting reads in filtering\">\n",
"##INFO=<ID=FSUP,Number=1,Type=Integer,Description=\"Number of total supporting reads in filtering\">\n",
"##INFO=<ID=GLeft,Number=1,Type=Integer,Description=\"Number of reads passing through the left breakpoint on template INS sequence\">\n",
"##INFO=<ID=GRight,Number=1,Type=Integer,Description=\"Number of reads passing through the right breakpoint on template INS sequence)\">\n",
"##INFO=<ID=GRef,Number=1,Type=Integer,Description=\"Number of reads passing through the breakpoint on template REF sequence)\">\n",
"##INFO=<ID=GRRatio,Number=1,Type=Float,Description=\"Ratio between GRight and GRef\">\n",
"##INFO=<ID=GLRatio,Number=1,Type=Float,Description=\"Ratio between GLeft and GRef \">\n",
"##INFO=<ID=RMContent,Number=1,Type=String,Description=\"Repeat content overlapping with the eveRepeat content overlapping with the event\">\n",##FORMAT=<ID=GT,Number=1,Type=String,Description=\"Genotype\">\n",
"#CHROM\tPOS\tID\tREF\tALT\tQUAL\tFILTER\tINFO\tFORMAT\tGENOTYPE\n"])
with open(output[0],'w') as hand:
print(header_info, file=hand, end="")
rule all_vcf:
input:
expand(path_names["pamass"] +"/{sample}/all.vcf",sample=config["input"].keys())
output:
path_names["pamass"] +"/merged.vcf"
shell:
"cat {input} > {output}"
rule all_cc:
input:
expand(path_names["partition"] +"/{sample}/cc",sample=config["input"].keys())
output:
path_names["partition"] +"/done"
shell:
"touch {output}"
#print(sext)
def get_assembly_input():
return expand( "{Path}/{sample}/{sample}.orphan.{typ}."+sext, Path=path_names["remcor"], sample=config["input"].keys(),typ=["canonical","almost"])