def Main():
global args,out
CellLine=["H1"]
HM=("input","H3K27ac","H3K27me3","H3K36me3","H3K4me1","H3K4me3","H3K9me3")
marks=[]
dbi={}
args=ParseArg()
if args.output=="stdout":
out=sys.stdout
else:
try:
out=open(args.output,"w")
except IOError:
print >>sys.stderr,"can't open file ",args.output,"to write. Using stdout instead"
out=sys.stdout
for cell in CellLine:
for hm in HM:
mark=cell+"_"+hm
marks.append(mark)
dbi[mark]=DBI.init("/data/zhuxp/bam2x/data/bamlist/"+mark+".bamlist","bamlist")
for i,x in enumerate(TableIO.parse(args.input,args.input_format)):
print >>out,"QR\t",x
if i%100==0: print >>sys.stderr,"query %d entries\r"%i,
for mark in marks:
print >>out,mark,"\t"
for j in DBI.query(x,dbi[mark]):
print >>out,"HT\t",j
def Main():
global args,out
args=ParseArg()
if args.output=="stdout":
out=sys.stdout
else:
try:
out=open(args.output,"w")
except IOError:
print >>sys.stderr,"can't open file ",args.output,"to write. Using stdout instead"
out=sys.stdout
count={}
dbi1=DBI.init(args.db,"bed") # the DBI init file for bed6 file of all kinds of RNA
dbi2=DBI.init(args.db_detail,"bed") # the DBI init file for bed12 file of lincRNA and mRNA with intron, exon, UTR
genome=Genome('mouse', Release=67, account=None)
for bed in TableIO.parse(args.input,args.format):
[typ,name,subtype]=annotation(bed,dbi1,dbi2,genome)
if count.has_key(typ):
count[typ]+=1
else:
count[typ]=1
print >>out, "\t".join (str(f) for f in [bed.chr,bed.start,bed.stop,bed.id,name,bed.strand,typ, subtype])
print >>out, "\n".join ("#"+typ+"\t%d"%(count[typ]) for typ in count.keys())
def Main():
'''
IO TEMPLATE
'''
global args, out
args = ParseArg()
if args.output == "stdout":
out = sys.stdout
else:
try:
out = open(args.output, "w")
except IOError:
print >> sys.stderr, "can't open file ", args.output, "to write. Using stdout instead"
out = sys.stdout
if args.input == "stdin":
fin = sys.stdin
else:
try:
x = args.input.split(".")
if x[-1] == "gz":
fin = gzip.open(args.input, "r")
else:
fin = open(args.input, "r")
except IOError:
print >> sys.stderr, "can't read file", args.input
fin = sys.stdin
'''
END OF IO TEMPLATE
'''
print >> out, "# This data was generated by program ", sys.argv[
0], " (version: %s)" % VERSION,
print >> out, "in bam2x ( https://github.com/nimezhu/bam2x )"
print >> out, "# Date: ", time.asctime()
print >> out, "# The command line is :"
print >> out, "#\t", " ".join(sys.argv)
enhancer_dbi = DBI.init(args.enhancer_tabix,
"tabix",
tabix="metabed",
header=re.sub(".gz$", ".header",
args.enhancer_tabix))
promoter_dbi = DBI.init(args.promoter_tabix,
"tabix",
tabix="metabed",
header=re.sub(".gz$", ".header",
args.promoter_tabix))
for i in TableIO.parse(fin, args.format):
tss = i.tss()
tss.start -= args.size
tss.stop += args.size
if tss.start < 0: tss.start = 0
tss.id += "_near" + str(args.size)
print "QR\t", tss
for e in enhancer_dbi.query(tss):
print "EH\t", e
for p in promoter_dbi.query(tss):
print "PM\t", p
def Main():
'''
IO TEMPLATE
'''
global args,out
args=ParseArg()
if args.output=="stdout":
out=sys.stdout
else:
try:
out=open(args.output,"w")
except IOError:
print >>sys.stderr,"can't open file ",args.output,"to write. Using stdout instead"
out=sys.stdout
if args.input=="stdin":
fin=sys.stdin
else:
try:
x=args.input.split(".")
if x[-1]=="gz":
fin=gzip.open(args.input,"r")
else:
fin=open(args.input,"r")
except IOError:
print >>sys.stderr,"can't read file",args.input
fin=sys.stdin
'''
END OF IO TEMPLATE
'''
print >>out,"# This data was generated by program ",sys.argv[0]," (version: %s)"%VERSION,
print >>out,"in bam2x ( https://github.com/nimezhu/bam2x )"
print >>out,"# Date: ",time.asctime()
print >>out,"# The command line is :"
print >>out,"#\t"," ".join(sys.argv)
enhancer_dbi=DBI.init(args.enhancer_tabix,"tabix",tabix="metabed",header=re.sub(".gz$",".header",args.enhancer_tabix))
promoter_dbi=DBI.init(args.promoter_tabix,"tabix",tabix="metabed",header=re.sub(".gz$",".header",args.promoter_tabix))
for i in TableIO.parse(fin,args.format):
tss=i.tss()
tss.start-=args.size
tss.stop+=args.size
if tss.start<0: tss.start=0
tss.id+="_near"+str(args.size)
print "QR\t",tss
for e in enhancer_dbi.query(tss):
print "EH\t",e
for p in promoter_dbi.query(tss):
print "PM\t",p
def Main():
'''
IO TEMPLATE
'''
global args,out
args=ParseArg()
fin=IO.fopen(args.input,"r")
out=IO.fopen(args.output,"w")
'''
END OF IO TEMPLATE
'''
print >>out,"# This data was generated by program ",sys.argv[0]," (version: %s)"%VERSION,
print >>out,"in bam2x ( https://github.com/nimezhu/bam2x )"
print >>out,"# Date: ",time.asctime()
print >>out,"# The command line is :"
print >>out,"#\t"," ".join(sys.argv)
dbi=DBI.init(args.db,Tools.guess_format(args.db))
references=dbi.bamfiles[0].references
for i in TableIO.parse(fin,args.format):
print i
n=0
c_count=0
reads=dbi.query(i,args.method)
for read in reads:
compatible=Tools.compatible_with_transcript(read,i,references=references,strand=args.strand)
print "HT:"
for i0,r in enumerate(TableIO.parse(read.reads,"bam2bed12",references=references)):
print "READ"+str(i0)+"\t",r
print "COMPATIBLE:",compatible,"\n\n"
if compatible: c_count+=1
n+=1
print "COMPATIBLE / ALL OVERLAP READS = ",c_count,"/",n
print "RATIO\t%.4f"%float(c_count)/n
def Main():
'''
IO TEMPLATE
'''
global args,out
args=ParseArg()
fin=IO.fopen(args.input,"r")
out=IO.fopen(args.output,"w")
'''
END OF IO TEMPLATE
'''
print >>out,"# This data was generated by program ",sys.argv[0]," (version: %s)"%VERSION,
print >>out,"in bam2x ( https://github.com/nimezhu/bam2x )"
print >>out,"# Date: ",time.asctime()
print >>out,"# The command line is :"
print >>out,"#\t"," ".join(sys.argv)
dbi=[];
for i,bam in enumerate(args.bams):
print >>out,"# SAMPLE_"+str(i+1)+" BAM File:",bam
dbi.append(DBI.init(bam,"bam"))
print >>out,"#",VCF.header(),
for i,bam in enumerate(args.bams):
print >>out,"\t","Sample_"+str(i+1),
print >>out,""
for i,vcf in enumerate(TableIO.parse(fin,"vcf")):
vcf.chr=args.chr_prefix+vcf.chr
if(i%100==0):
print >>sys.stderr,"processing",i,"vcf\r",
print >>out,vcf,
for d in dbi:
print >>out,"\t",
for r in d.query(vcf):
print >>out,format(r),
print >>out,""
def Main():
args = ParseArg()
if len(args.data) != len(args.name):
print >> sys.stderr, "ERROR: Number of data is not the same as number of names!"
sys.exit(0)
# store data information
data = {}
total_reads = {}
for i in range(len(args.data)):
temp_name = args.name[i]
print >> sys.stderr, "\n Reading data file:" + temp_name + "..."
total_reads[temp_name] = 0
if args.format[i] == "bam":
total_reads[temp_name] = reduce(lambda x, y: x + y, [
int(l.rstrip('\n').split('\t')[2])
for l in pysam.idxstats(args.data[i])
])
else:
Format = "bed"
for b in TableIO.parse(args.data[i], Format):
total_reads[temp_name] += 1
if total_reads[temp_name] % 50000 == 0:
print >> sys.stderr, " reading %d reads..\r" % (
total_reads[temp_name]),
data[temp_name] = DBI.init(args.data[i], args.format[i])
output = open(args.output, 'w')
Input = open(args.input, 'r')
lines = Input.read().split("\n")
# header
header = ["chr", "start", "end", "type", "name", "subtype", "count"
] + data.keys()
print >> output, "\t".join(g + "_%d" % (f) for f in [1, 2]
for g in header) + "\tinteraction\tp-value"
num = 0
print >> sys.stderr, "Start process interactions:"
for l in lines:
if l.strip() == '': continue
l = l.strip().split('\t')
num = num + 1
if l[0] == "chrM" or l[7] == "chrM": continue
C1 = Bed([l[0], int(l[1]), int(l[2])])
C2 = Bed([l[7], int(l[8]), int(l[9])])
rpkm1 = "\t".join(
str(f) for f in
[RPKM(C1, data[n], total_reads[n], n) for n in data.keys()])
rpkm2 = "\t".join(
str(f) for f in
[RPKM(C2, data[n], total_reads[n], n) for n in data.keys()])
print >> output, "\t".join(
str(f) for f in l[:7] + [rpkm1] + l[7:14] + [rpkm2, l[14], l[15]])
if num % 1000 == 0:
print >> sys.stderr, " Output interaction: %d\r" % (num),
def Main():
global args
args=ParseArg()
if args.output=="stdout":
out=sys.stdout
else:
try:
out=open(args.output,"w")
except IOError:
print >>sys.stderr,"can't open file ",args.output,"to write. Using stdout instead"
out=sys.stdout
dbi=DBI.init(args.db,"genebed")
count={}
count["Intergenic"]=0
for x in TableIO.parse(args.input,args.input_format):
flag=0
gene=""
for hit in dbi.query(x):
flag=1
if hit.align_id==gene:
continue
gene=hit.align_id
#print hit
#print hit.cds_start,hit.cds_stop
if (hit.cds_start==hit.cds_stop):
if hit.align_id[0:3]=="Mir":
loc="MiRNA"
else:
loc="Non-coding"
elif hit.strand=="+":
if x.stop<=hit.cds_start:
loc="5-UTR"
elif x.start>=hit.cds_stop:
loc="3-UTR"
else:
loc=judge_exon(x,hit)
else:
if x.stop<=hit.cds_start:
loc="3-UTR"
elif x.start>=hit.cds_stop:
loc="5-UTR"
else:
loc=judge_exon(x,hit)
print >>out,"\t".join (str(f) for f in [x.chr,x.start,x.stop,x.id,x.score,x.strand,hit.align_id,loc])
if count.has_key(loc):
count[loc]+=1
else:
count[loc]=1
if flag==0:
print >>out, "\t".join (str(f) for f in [x.chr,x.start,x.stop,x.id,x.score,x.strand,"None","Intergenic"])
count["Intergenic"]+=1
out2=open(args.output.split(".")[0]+".cisStat","w")
for key in sorted(count.keys()):
print >>out2,key+"\t"+str(count[key])
def Main():
global args,out
args=ParseArg()
if args.output=="stdout":
out=sys.stdout
else:
try:
out=open(args.output,"w")
except IOError:
print >>sys.stderr,"can't open file ",args.output,"to write. Using stdout instead"
out=sys.stdout
dbi=DBI.init(args.db,args.dbformat)
for x in TableIO.parse(args.input,args.input_format):
print "QR\t",x
for j in DBI.query(x,dbi):
print "HT\t",j
x.chr=x.chr.replace("chr","")
for j in DBI.query(x,dbi):
print "HT\t",j
def ReadHistones(fhist_name):
sp1 = []
sp2 = []
with open(fhist_name, "r") as fhist:
fhist.readline()
while True:
line = fhist.readline().strip()
if "@" in line:
break
line = line.split()
sp1.append(DBI.init(line[0], "bed"))
while True:
line = fhist.readline().strip()
if line == "":
break
line = line.split()
sp2.append(DBI.init(line[0], "bed"))
return sp1, sp2
def Main():
args=ParseArg()
if len(args.data)!=len(args.name):
print >> sys.stderr, "ERROR: Number of data is not the same as number of names!"
sys.exit(0)
# store data information
data={}
total_reads={}
for i in range(len(args.data)):
temp_name=args.name[i]
print >> sys.stderr, "\n Reading data file:"+temp_name+"..."
total_reads[temp_name]=0
if args.format[i]=="bam":
total_reads[temp_name] = reduce(lambda x, y: x + y, [ int(l.rstrip('\n').split('\t')[2]) for l in pysam.idxstats(args.data[i])])
else:
Format="bed"
for b in TableIO.parse(args.data[i],Format):
total_reads[temp_name]+=1
if total_reads[temp_name]%50000==0:
print >> sys.stderr, " reading %d reads..\r"%(total_reads[temp_name]),
data[temp_name]=DBI.init(args.data[i],args.format[i])
output=open(args.output,'w')
Input=open(args.input,'r')
lines=Input.read().split("\n")
# header
header=["chr","start","end","type","name","subtype","count"]+data.keys()
print >> output, "\t".join(g+"_%d"%(f) for f in [1,2] for g in header)+"\tinteraction\tp-value"
num=0
print >> sys.stderr, "Start process interactions:"
for l in lines:
if l.strip()=='': continue
l=l.strip().split('\t')
num=num+1
if l[0]=="chrM" or l[7]=="chrM": continue
C1=Bed([l[0],int(l[1]),int(l[2])])
C2=Bed([l[7],int(l[8]),int(l[9])])
rpkm1="\t".join (str(f) for f in [RPKM(C1,data[n],total_reads[n],n) for n in data.keys()])
rpkm2="\t".join (str(f) for f in [RPKM(C2,data[n],total_reads[n],n) for n in data.keys()])
print >> output, "\t".join(str(f) for f in l[:7]+[rpkm1]+l[7:14]+[rpkm2,l[14],l[15]])
if num%1000==0:
print >> sys.stderr, " Output interaction: %d\r"%(num),
def Main():
args = ParseArg()
#store bed files with indexing and count information:
bed = {}
print >> sys.stderr, "Starting index bed files:"
for i in range(len(args.beds)):
temp_name = args.name[i]
print >> sys.stderr, " #Indexing for bed file of", temp_name, "\r",
bed[temp_name] = DBI.init(args.beds[i], 'bed')
half_len = int(args.len)
print >> sys.stderr
print >> sys.stderr, "Reading nucleosome peak xls file from Danpos."
nucleosomes = TableIO.parse(args.nucleosome, 'metabed', header=True)
print >> sys.stderr, "Start Counting..."
count_matrix = []
out = open(args.output, "w")
line_head = open(args.nucleosome, 'r').readline().strip()
line_head = line_head + "\t" + "\t".join(str(f) for f in args.name)
print >> out, line_head
for i in nucleosomes:
chrom = i.chr
if chrom == 'chrY' or chrom == 'chrX' or chrom == 'chrM':
continue
center = int(i.start + i.end) / 2
count = np.zeros(len(args.beds), dtype="float")
line = str(i)
for k, name in enumerate(bed.keys()):
for j in bed[name].query(
Bed([
chrom, center - ma - (half_len - 75),
center + ma + (half_len - 75)
])):
j_center = find_center(j, half_len)
weight = max(min(1, (ma - abs(j_center - center)) / 25.0), 0)
count[k] += weight
line = line + "\t" + "\t".join(str(f) for f in count)
print >> out, line
count_matrix.append(count)
def Main():
global args,out
args=ParseArg()
if args.output=="stdout":
out=sys.stdout
else:
try:
out=open(args.output,"w")
except IOError:
print >>sys.stderr,"can't open file ",args.output,"to write. Using stdout instead"
out=sys.stdout
argv=sys.argv
argv[0]=argv[0].split("/")[-1]
print >>out,"# This data was generated by program ",argv[0],"(version %s)"%VERSION,
print >>out,"in bam2x ( https://github.com/nimezhu/bam2x )"
print >>out,"# Date: ",time.asctime()
print >>out,"# The command line is :\n#\t"," ".join(argv)
dbi=DBI.init(args.db,args.dbformat)
hits=0
query=0
if args.input=="stdin":
input=sys.stdin
else:
input=args.input
query_length=0
hits_number=0
query_sets=[]
for x in TableIO.parse(input,args.input_format):
query_sets.append(x)
length=len(query_sets)
size=length/args.thread
#results=[[] for i in range(args.thread)]
for i in range(args.thread):
end= (i+1)*size if (i+1)*size < length else length
end= end if (i+1)!=args.thread else length
querys=query_sets[i*size:end]
# print i*size,end
# for j in querys: print j
thread.start_new_thread(fquery,(querys,dbi,i))
def Main():
args=ParseArg()
#store bed files with indexing and count information:
bed={}
print >>sys.stderr,"Starting index bed files:"
for i in range(len(args.beds)):
temp_name=args.name[i]
print >>sys.stderr," #Indexing for bed file of",temp_name,"\r",
bed[temp_name]=DBI.init(args.beds[i],'bed')
half_len=int(args.len)
print >>sys.stderr
print >>sys.stderr,"Reading nucleosome peak xls file from Danpos."
nucleosomes=TableIO.parse(args.nucleosome,'metabed',header=True)
print >>sys.stderr,"Start Counting..."
count_matrix=[]
out=open(args.output,"w")
line_head=open(args.nucleosome,'r').readline().strip()
line_head=line_head+"\t"+"\t".join(str(f) for f in args.name)
print >>out,line_head
for i in nucleosomes:
chrom=i.chr
if chrom == 'chrY' or chrom == 'chrX' or chrom == 'chrM':
continue
center=int(i.start+i.end)/2
count=np.zeros(len(args.beds),dtype="float")
line=str(i)
for k,name in enumerate(bed.keys()):
for j in bed[name].query(Bed([chrom,center-ma-(half_len-75),center+ma+(half_len-75)])):
j_center=find_center(j,half_len)
weight = max(min(1,(ma-abs(j_center-center))/25.0),0)
count[k]+=weight
line = line + "\t" + "\t".join(str(f) for f in count)
print >>out,line
count_matrix.append(count)
def Main():
args = ParseArg()
anno = DBI.init(args.annotation, "bed")
ext_dis = args.ext_dis
target_num = args.target_num
with open(args.input, "r") as fin, open(args.output, "w") as fout:
for line in fin:
bed_region = Bed(line.strip().split())
mid_point = (bed_region.start + bed_region.stop) / 2
ori_start = bed_region.start
ori_stop = bed_region.stop
bed_region.start = mid_point - ext_dis
bed_region.stop = mid_point + ext_dis
gene_list = findNearbyGene(bed_region, anno, ori_start, ori_stop,
target_num)
for gene in gene_list:
print >> fout, "\t".join(
[bed_region.id, gene[1],
str(gene[0])])
def Main():
'''
IO TEMPLATE
'''
global args, out
args = ParseArg()
fin = IO.fopen(args.input, "r")
out = IO.fopen(args.output, "w")
'''
END OF IO TEMPLATE
'''
print >> out, "# This data was generated by program ", sys.argv[
0], " (version: %s)" % VERSION,
print >> out, "in bam2x ( https://github.com/nimezhu/bam2x )"
print >> out, "# Date: ", time.asctime()
print >> out, "# The command line is :"
print >> out, "#\t", " ".join(sys.argv)
dbi = DBI.init(args.db, Tools.guess_format(args.db))
references = dbi.bamfiles[0].references
for i in TableIO.parse(fin, args.format):
print i
n = 0
c_count = 0
reads = dbi.query(i, args.method)
for read in reads:
compatible = Tools.compatible_with_transcript(
read, i, references=references, strand=args.strand)
print "HT:"
for i0, r in enumerate(
TableIO.parse(read.reads,
"bam2bed12",
references=references)):
print "READ" + str(i0) + "\t", r
print "COMPATIBLE:", compatible, "\n\n"
if compatible: c_count += 1
n += 1
print "COMPATIBLE / ALL OVERLAP READS = ", c_count, "/", n
print "RATIO\t%.4f" % float(c_count) / n
def Main():
global args, out
args = ParseArg()
if args.output == "stdout":
out = sys.stdout
else:
try:
out = open(args.output, "w")
except IOError:
print >> sys.stderr, "can't open file ", args.output, "to write. Using stdout instead"
out = sys.stdout
argv = sys.argv
argv[0] = argv[0].split("/")[-1]
print >> out, "# This data was generated by program ", argv[
0], "(version %s)" % VERSION,
print >> out, "in bam2x ( https://github.com/nimezhu/bam2x )"
print >> out, "# Date: ", time.asctime()
print >> out, "# The command line is :\n#\t", " ".join(argv)
dbi = DBI.init(args.bam, "bam")
if args.input == "stdin":
input = sys.stdin
else:
input = args.input
for x in TableIO.parse(input, args.input_format):
promoter = x.core_promoter(1000, 1000)
print >> out, x
print >> out, promoter
retv = []
for (i, r) in enumerate(dbi.query(promoter)):
retv.append(sum(r))
if x.strand == "-":
retv = retv[::-1]
for i in retv:
print >> out, i,
print >> out, ""
def Main():
global args,out
args=ParseArg()
if args.output=="stdout":
out=sys.stdout
else:
try:
out=open(args.output,"w")
except IOError:
print >>sys.stderr,"can't open file ",args.output,"to write. Using stdout instead"
out=sys.stdout
argv=sys.argv
argv[0]=argv[0].split("/")[-1]
print >>out,"# This data was generated by program ",argv[0],"(version %s)"%VERSION,
print >>out,"in bam2x ( https://github.com/nimezhu/bam2x )"
print >>out,"# Date: ",time.asctime()
print >>out,"# The command line is :\n#\t"," ".join(argv)
dbi=DBI.init(args.bam,"bam")
if args.input=="stdin":
input=sys.stdin
else:
input=args.input
for x in TableIO.parse(input,args.input_format):
promoter=x.core_promoter(1000,1000)
print >>out,x
print >>out,promoter
retv=[]
for (i,r) in enumerate(dbi.query(promoter)):
retv.append(sum(r))
if x.strand=="-":
retv=retv[::-1]
for i in retv:
print >>out,i,
print >>out,""
def Main():
global args, out
args = ParseArg()
dict = {}
if args.output == "stdout":
out = sys.stdout
else:
try:
out = open(args.output, "w")
except IOError:
print >> sys.stderr, "can't open file ", args.output, "to write. Using stdout instead"
out = sys.stdout
argv = sys.argv
argv[0] = argv[0].split("/")[-1]
print >> out, "# This data was generated by program ", argv[
0], "(version %s)" % VERSION,
print >> out, "in bam2x ( https://github.com/nimezhu/bam2x )"
print >> out, "# Date: ", time.asctime()
print >> out, "# The command line is :\n#\t", " ".join(argv)
if args.query_method:
dict["method"] = args.query_method
dbi = DBI.init(args.db, args.dbformat)
hits = 0
query = 0
if args.input == "stdin":
input = sys.stdin
else:
input = args.input
query_length = 0
hits_number = 0
for (i0, x) in enumerate(TableIO.parse(input, args.input_format)):
if i0 % 10 == 0:
print >> sys.stderr, "query ", i0, " entries\r",
print >> out, "QR\t", x
hit = 0
query += 1
query_length += len(x)
results = dbi.query(x, **dict)
compatible = 0
#print >>sys.stderr,type(results)
if isinstance(results, numpy.ndarray) or isinstance(results, list):
if not args.silence:
print >> out, "HT\t",
for value in results:
print >> out, str(value) + ",",
print >> out, ""
hit = 1
hits_number += 1
elif isinstance(results, str):
if not args.silence:
print >> out, "HT\t",
print >> out, results
hit = 1
hits_number += 1
else:
this_query_hits = 0
for j in results:
if not args.silence:
print >> out, "HT\t", j,
hit = 1
hits_number += 1
this_query_hits += 1
if isinstance(j, xplib.Annotation.Bed12) and isinstance(
x, xplib.Annotation.Bed12):
compatible_binary = Tools.compatible_with_transcript(j, x)
if not args.silence:
print >> out, "\tCompatible:", compatible_binary
if compatible_binary:
compatible += 1
else:
if not args.silence:
print >> out, ""
print >> out, "HN\t", this_query_hits
if compatible > 0:
print >> out, "CP\t", compatible
if args.dbformat == "tabix":
x.chr = x.chr.replace("chr", "")
for j in dbi.query(x, **dict):
print >> out, "HT\t", j
hit = 1
hits_number += 1
hits += hit
print >> out, "# Query Number:", query, "\n# Query Have Hits:", hits
print >> out, "# Query Length:", query_length
print >> out, "# Hits Number:", hits_number
def Main():
global args, out
args = ParseArg()
dict = {}
if args.output == "stdout":
out = sys.stdout
else:
try:
out = open(args.output, "w")
except IOError:
print >> sys.stderr, "can't open file ", args.output, "to write. Using stdout instead"
out = sys.stdout
argv = sys.argv
argv[0] = argv[0].split("/")[-1]
print >> out, "# This data was generated by program ", argv[
0], "(version %s)" % VERSION,
print >> out, "in bam2x ( https://github.com/nimezhu/bam2x )"
print >> out, "# Date: ", time.asctime()
print >> out, "# The command line is :\n#\t", " ".join(argv)
init_dict = {}
if args.dbformat == "guess":
if Tools.suffix(args.db) == "gz":
args.dbformat = "tabix"
args.tabix_format = Tools.guess_format(args.db)
else:
args.dbformat = Tools.guess_format(args.db)
if args.query_method:
dict["method"] = args.query_method
if args.tabix_format:
init_dict["tabix"] = args.tabix_format
dbi = DBI.init(args.db, args.dbformat, **init_dict)
hits = 0
query = 0
if args.input == "stdin":
input = sys.stdin
else:
input = args.input
query_length = 0
hits_number = 0
if (args.input_format == "guess"):
args.input_format = Tools.guess_format(args.input)
for (i0, x) in enumerate(TableIO.parse(input, args.input_format)):
if i0 % 100 == 0:
print >> sys.stderr, "query ", i0, " entries\r",
print >> out, "QR\t", x
hit = 0
query += 1
query_length += len(x)
#print dbi;#debug
results = dbi.query(x, **dict)
#results=dbi.query(x) #DEBUG
#print >>sys.stderr,type(results)
if isinstance(results, numpy.ndarray) or isinstance(results, list):
print >> out, "HT\t",
for value in results:
print >> out, str(value) + ",",
print >> out, ""
hit = 1
hits_number += 1
elif isinstance(results, str):
print >> out, "HT\t",
print >> out, results
hit = 1
hits_number += 1
else:
for j in results:
print >> out, "HT\t", j
hit = 1
hits_number += 1
if args.dbformat == "tabix":
x.chr = x.chr.replace("chr", "")
for j in dbi.query(x, **dict):
print >> out, "HT\t", j
hit = 1
hits_number += 1
hits += hit
print >> out, "# Query Number:", query, "\n# Query Have Hits:", hits
print >> out, "# Query Length:", query_length
print >> out, "# Hits Number:", hits_number
def Main():
global args,out
args=ParseArg()
dict={}
if args.output=="stdout":
out=sys.stdout
else:
try:
out=open(args.output,"w")
except IOError:
print >>sys.stderr,"can't open file ",args.output,"to write. Using stdout instead"
out=sys.stdout
argv=sys.argv
argv[0]=argv[0].split("/")[-1]
print >>out,"# This data was generated by program ",argv[0],"(version %s)"%VERSION,
print >>out,"in bam2x ( https://github.com/nimezhu/bam2x )"
print >>out,"# Date: ",time.asctime()
print >>out,"# The command line is :\n#\t"," ".join(argv)
if args.query_method:
dict["method"]=args.query_method
dbi=DBI.init(args.db,args.dbformat)
hits=0
query=0
if args.input=="stdin":
input=sys.stdin
else:
input=args.input
query_length=0
hits_number=0
for (i0,x) in enumerate(TableIO.parse(input,args.input_format)):
if i0%10==0:
print >>sys.stderr,"query ",i0," entries\r",
print >>out,"QR\t",x
hit=0
query+=1
query_length+=len(x)
results=dbi.query(x,**dict)
compatible=0
#print >>sys.stderr,type(results)
if isinstance(results,numpy.ndarray) or isinstance(results,list):
if not args.silence:
print >>out,"HT\t",
for value in results:
print >>out,str(value)+",",
print >>out,""
hit=1
hits_number+=1
elif isinstance(results,str):
if not args.silence:
print >>out,"HT\t",
print >>out,results
hit=1
hits_number+=1
else:
this_query_hits=0
for j in results:
if not args.silence:
print >>out,"HT\t",j,
hit=1
hits_number+=1
this_query_hits+=1
if isinstance(j,xplib.Annotation.Bed12) and isinstance(x,xplib.Annotation.Bed12):
compatible_binary=Tools.compatible_with_transcript(j,x)
if not args.silence:
print >>out,"\tCompatible:",compatible_binary
if compatible_binary:
compatible+=1
else:
if not args.silence:
print >>out,""
print >>out,"HN\t",this_query_hits
if compatible>0:
print >>out,"CP\t",compatible
if args.dbformat=="tabix":
x.chr=x.chr.replace("chr","")
for j in dbi.query(x,**dict):
print >>out,"HT\t",j
hit=1
hits_number+=1
hits+=hit
print >>out,"# Query Number:",query,"\n# Query Have Hits:",hits
print >>out,"# Query Length:",query_length
print >>out,"# Hits Number:",hits_number
def Main():
'''
IO TEMPLATE
'''
global args,out,isoforms_set,selected_isoforms_set,reads_set,selected_reads_set,dbi
args=ParseArg()
if args.output=="stdout":
out=sys.stdout
else:
try:
out=open(args.output,"w")
except IOError:
print >>sys.stderr,"can't open file ",args.output,"to write. Using stdout instead"
out=sys.stdout
if args.input=="stdin":
fin=sys.stdin
else:
try:
x=args.input.split(".")
if x[-1]=="gz":
fin=gzip.open(args.input,"r")
else:
fin=open(args.input,"r")
except IOError:
print >>sys.stderr,"can't read file",args.input
fin=sys.stdin
'''
END OF IO TEMPLATE
'''
print >>out,"# This data was generated by program ",sys.argv[0]," (version: %s)"%VERSION,
print >>out,"in bam2x ( https://github.com/nimezhu/bam2x )"
print >>out,"# Date: ",time.asctime()
print >>out,"# The command line is :"
print >>out,"#\t"," ".join(sys.argv)
dbi=DBI.init(args.bam,args.format)
'''
reading all the isoforms
'''
isoforms=[]
iterator=TableIO.parse(fin,"bed")
beds=[]
for i in iterator:
beds.append(i)
beds.sort()
if len(beds)==0:
print >>sys.stderr,"error in reading file",args.input
exit(1)
bed=beds[0]
chr=bed.chr
min_start=bed.start
max_stop=bed.stop
j=0
for i in beds:
j+=1
if (j%10==0): print >>sys.stderr,"processed %d entries\r"%j,
if Tools.overlap(bed,i):
if bed.stop < i.stop:
bed.stop=i.stop
isoforms.append(i)
else:
compare(isoforms)
isoforms=[i]
bed=i
if len(isoforms)>0:
compare(isoforms)
def Main():
args=ParseArg()
#store bed files with indexing and count information:
bam={}
print >>sys.stderr,"Starting index bed files:"
for i in range(len(args.bams)):
temp_name=args.name[i]
print >>sys.stderr," #Indexing for bed file of",temp_name,"\r",
bam[temp_name]=DBI.init(args.bams[i],args.fmt)
print >>sys.stderr
print >>sys.stderr,"Reading nucleosome peak xls file from Danpos."
nucleosomes=TableIO.parse(args.nucleosome,'metabed',header=True)
print >>sys.stderr,"Initial output files..."
out=open(args.output,"w")
# -- for verbose ---
if args.verbose:
out_mark=[]
for n in args.name:
out_mark.append(open(n+'_shift_nucleosomes.bed','w'))
# ------------------
line_head=open(args.nucleosome,'r').readline().strip()
line_head=line_head+"\t"+"\t".join(str(f) for f in args.name)+'\t'+"\t".join(str(f)+'_off' for f in args.name)
print >>out,line_head
print >>sys.stderr,"Start Counting..."
num=0
t0 = time()
for i in nucleosomes:
chrom=i.chr
if i.smt_pval>0.01 or i.fuzziness_pval>0.01: continue # only choose nucleosomes with high value and low fuzziness
if chrom == 'chrY' or chrom == 'chrX' or chrom == 'chrM':
continue
num=num+1
center=int(i.start+i.end)/2
count=np.zeros(len(args.bams),dtype="float")
offset=np.zeros(len(args.bams),dtype='int')
line=str(i)
for k,name in enumerate(bam.keys()):
if args.fmt=='bam':
query=bam[name].query(Bed([chrom,center-ma-(half_len-75)-rangeS,center+ma+(half_len-75)+rangeS]),method='fetch')
else:
query=bam[name].query(Bed([chrom,center-ma-(half_len-75)-rangeS,center+ma+(half_len-75)+rangeS]))
read_centers=[]
for j in query:
read_centers.append(find_center(j,args.fmt))
[o,c]=getCount(read_centers,center)
count[k]=c
offset[k]=o
# -- for verbose ---
if args.verbose:
print >>out_mark[k],chrom+'\t%d\t%d'%(i.start+o,i.end+o)
# ------------------
line = line + "\t" + "\t".join(str(f) for f in count) + '\t' + "\t".join(str(f) for f in offset)
if num%20000==0:
t1 = time()
print >>sys.stderr,"processing %dth nucleosome..., time: %.2fs."%(num,t1-t0),'\r',
t0 = time()
print >>out,line
print
out.close()
# -- for verbose ---
if args.verbose:
for k in out_mark:
k.close()
def Main():
args=ParseArg()
hist_n=args.hist_n
clu_n=args.clu_n
File=args.input
#read emission matrix and store in Rpy2
print "#Reading emission matrix from"
emission=args.emission
print '\t'+emission
robjects.r("emission=read.table('"+emission+"',header=T,sep='\t')")
robjects.r("emission=emission[c(12,11,13,8,7,10,6,9,4,5,2,1,3,15,14),match(c('H3K4me3','H3K4me2','H3K4me1','H3K27me3','H3K36me3','H3K27ac','H2AZ'),colnames(emission))]")
state_n=robjects.r("dim(emission)[1]")[0] # number of chromatin state
color_state=['red','pink','purple','DarkOrange','Orange','Gold','yellow','DeepSkyBlue','ForestGreen','Green','Lime','GreenYellow','LightCyan','white','white']
#Find overall distribution of all chromatin states
print "Counting distribution of chromatin states..."
chromHMM_segment = TableIO.parse(args.segment,'bed')
#count represent overall probability distribution of all chromatin states
count=np.zeros(state_n)
num=0
for segment in chromHMM_segment:
num=num+1
i=int(segment.id[1:])
count[i-1]+=(segment.stop-segment.start)/200
print 'Reading %d segments... [for distribution of chromatin states]'%(num),'\r',
print
## read and index histone pattern data for single nucleosomes in all populations
print "Indexing histone pattern data for single nucleosomes in all populations..."
data=TableIO.parse(File,'metabed',header=True)
## generate bed file for chromatin states in nucleosomes to be uploaded in UCSC genome browser
if args.bed:
name=os.path.basename(File).split('.')[0]
outbed=open(name+"_State_browser.bed",'w')
print "## Start generate BED9 file for uploading..."
print >>outbed,'track name="ChromatinState" description="'+name+'" visibility=2 itemRgb="On"'
#print >>outbed,'chr\tstart\tend\t'+'\t'.join('P_%d'%(s+1) for s in range(clu_n))
for n,i in enumerate(data):
matrix=np.array(str(i).split('\t')[8:(8+hist_n*clu_n)],dtype="int").reshape(hist_n,clu_n,order="F") # matrix of histone patterns, row: histone, column: population
if n % 50000 == 0:
print "\tWriting %dth nucleosomes into BED9 file,\r"%(n),
line='\t'.join (str(f) for f in [i.chr,i.start,i.stop])
for k in range(clu_n):
state=histone2state(matrix.T[k],count)
color_code=','.join (str(int(f)) for f in np.array(matplotlib.colors.colorConverter.to_rgb(color_state[state-1]))*255)
print >>outbed,'\t'.join (str(f) for f in [i.chr,i.start,i.stop,'P_%d_%d'%(k+1,state),0,'.',i.start,i.stop,color_code])
line=line+'\t%d'%(state)
#print >>outbed,line
outbed.close()
sys.exit(1)
# read region information
region=args.region
chro=region.split(":")[0]
start=int(region.split(":")[1].split("-")[0])
end=int(region.split(":")[1].split("-")[1])
print "#Query region:["+chro+": %d-%d]"%(start,end)
y_nucle=0.47 #location of nucleosome line
## query data in region
dbi=binindex(data)
query=dbi.query(Bed([chro,start,end]))
## initialize figure
fig=plt.figure(figsize=(10,6))
ax = plt.subplot(111,frameon=False,yticks=[])
ax.set_xlim(start-(end-start)/6,end)
n=0
print "##Start draw nucleosomes:"
#################################################
## draw genes from y = y_nucle+0.04*(clu_n+1)
#### index the gene.tab file
print " ## drawing gene track ..."
print " ## Indexing gene.tab ..."
gene_dbi=DBI.init(args.genetab,'genebed')
print " ## query regions from gene.tab"
query_gene=gene_dbi.query(Bed([chro,start,end]))
#### determine height of gene track
bottoms=[0 for i in range(100)]
max_index=0
for i in query_gene:
index=0
while(1):
if i.start > bottoms[index]:
bottoms[index]=i.stop
if max_index<index: max_index=index
break
else:
index+=1
gene_track_number=max_index+1
gene_track_height=0.03*gene_track_number+0.02
ax.set_ylim(0.05,1+gene_track_height+0.01)
print " ## start draw gene track"
# add frame for gene track
rect=matplotlib.patches.Rectangle((start,y_nucle+0.04),end-start, gene_track_height, edgecolor='black',fill=False)
ax.add_patch(rect)
bottoms=[0 for i in range(100)]
for i in gene_dbi.query(Bed([chro,start,end])):
index=0
while(1):
if i.start > bottoms[index]:
addGeneToFig(i,ax,start,end,1,0.03*index+y_nucle+0.05)
bottoms[index]=i.stop
break
index+=1
#################################################
top_heatmap_y = 0.71+gene_track_height # the y axis value for bottom of top heatmaps
print "## Draw nucleosome tracks..."
for i in query:
n=n+1
print " Nucleosome %d\t at "%(n)+chro+": %d-%d"%(i.start,i.stop)
matrix=np.array(str(i).split('\t')[8:(8+hist_n*clu_n)],dtype="int").reshape(hist_n,clu_n,order="F") # matrix of histone patterns, row: histone, column: population
prob=np.array(str(i).split('\t')[(8+hist_n*clu_n):],dtype=float)
ax.plot([i.smt_pos,i.smt_pos],[y_nucle+0.03,y_nucle],color='r') #red nucleosome midpoint
rect=matplotlib.patches.Rectangle((i.start,y_nucle), i.stop-i.start, 0.03, color='#EB70AA') #pink nucleosome region
ax.add_patch(rect)
for j in range(clu_n):
state=histone2state(matrix.T[j],count)
state_rect=matplotlib.patches.Rectangle((i.start,y_nucle+0.04*(j+1)+gene_track_height+0.01), i.stop-i.start, 0.03, color=color_state[state-1])
ax.add_patch(state_rect)
im = OffsetImage(matrix, interpolation='nearest',zoom=10/(1+gene_track_height+0.01),cmap=plt.cm.binary,alpha=0.5)
if n<=9:
xybox=((n+0.5)/10.0,top_heatmap_y)
xy = [i.smt_pos,y_nucle+0.04*clu_n+0.03+gene_track_height+0.01]
xytext=((n+0.7)/10.0,top_heatmap_y)
c_style="bar,angle=180,fraction=-0.1"
elif n<=18:
xybox=((n-9+0.5)/10.0,0.2)
xy = [i.smt_pos,y_nucle]
xytext = ((n-9+0.7)/10.0,0.40)
c_style="bar,angle=180,fraction=-0.1"
else:
print "WARN: nucleosome number larger than 18 in this region, only plot the pattern for first 18 nucleosomes"
break
ab = AnnotationBbox(im, xy,
xybox=xybox,
xycoords='data',
boxcoords=("axes fraction", "data"),
box_alignment=(0.,0.),
pad=0.1)
ax.annotate("",xy,
xytext=xytext,
xycoords='data',
textcoords=("axes fraction", "data"),
arrowprops=dict(arrowstyle="->",connectionstyle=c_style))
#arrowprops=None)
ax.add_artist(ab)
# add mark for histone mark and regions with low confidence
for i in range(hist_n):
if prob[i]<0.6:
xy_star=tuple(map(sum,zip(xybox,(0.065,0.03*(hist_n-1-i)-0.01))))
ax.annotate("*",xy=xy_star,xycoords=("axes fraction", "data"),color='red')
ax.annotate('Nucleosome:', xy=(start-(end-start)/6, y_nucle), xycoords='data',size=12)
ax.annotate('Epigenetic Pattern:', xy=(start-(end-start)/6, 0.23+top_heatmap_y), xycoords='data',size=12)
ax.annotate(chro, xy=(start-(end-start)/6, 0.1), xycoords='data',size=12)
name=open(File).readline().split('\t')[8:(8+hist_n)]
for n,i in enumerate(name):
ax.annotate(i.split("_")[0],xy=(start-(end-start)/8, top_heatmap_y+0.03*(hist_n-1-n)),xycoords='data',size=10)
ax.annotate(i.split("_")[0],xy=(start-(end-start)/8, 0.2+0.03*(hist_n-1-n)),xycoords='data',size=10)
# flame for nucleosome and chromatin state tracks
rect=matplotlib.patches.Rectangle((start,y_nucle),end-start, 0.03, edgecolor='black',fill=False)
ax.add_patch(rect)
for k in range(clu_n):
rect=matplotlib.patches.Rectangle((start,y_nucle+0.04*(k+1)+gene_track_height+0.01),end-start, 0.03, edgecolor='grey',fill=False)
ax.add_patch(rect)
ax.annotate('Population%d'%(k+1),xy=(start-(end-start)/6, y_nucle+0.04*(k+1)+gene_track_height+0.01),xycoords='data',size=12)
# chromatin state legend
for s in range(state_n):
dist=(end-start)*1.0/state_n
length=dist*0.75
rect=matplotlib.patches.Rectangle((start+dist*s,0.1), length, 0.03, color=color_state[s])
ax.add_patch(rect)
ax.annotate(s+1,xy=(start+dist*s+length/3,0.075),xycoords='data',size=10)
ax.annotate("Chromatin states:",xy=(start,0.14),xycoords='data',size=12)
ax.add_patch(matplotlib.patches.Rectangle((start-length/6,0.07),end-start, 0.1, edgecolor='grey',fill=False))
plt.title("Region: ["+chro+": %d-%d]"%(start,end),size=14)
plt.savefig(args.output)
plt.close()
def genome_annotation(outputbam,
annotationfile,
detail,
annotationRepeat,
mapq_thred,
strandenforced=False,
posstrand=True,
requireUnique=False,
results_dict=dict()):
# annotationfile is annotation file
# detail is db_detail file
if annotationfile:
dbi1 = DBI.init(annotationfile, "bed")
dbi2 = DBI.init(detail, "bed")
dbi3 = DBI.init(annotationRepeat, "bed")
newdict = dict()
# funmap = open(unmapfilename, 'w')
for record in outputbam:
# print >> sys.stderr, record.qname
if "N" not in record.cigarstring:
anno_start = record.pos
anno_end = record.aend
bed_start = record.pos
bed_end = record.aend
else:
bed_list, anno_start, anno_end = Exon_junction(record)
bed_start = ",".join([str(f[0]) for f in bed_list])
bed_end = ",".join([str(f[1]) for f in bed_list])
# print anno_start,anno_end,bed_start,bed_end
IsMapped = False
if Included(record, requireUnique, mapq_thred):
strandactual = ("+" if posstrand else "-")
strand = "+"
if record.is_reverse:
strandactual = ("-" if posstrand else "+")
strand = "-"
if annotationfile:
bed = Bed([
outputbam.getrname(record.tid), anno_start, anno_end, '.',
0.0, strandactual
])
[typ, name, subtype,
strandcol] = annotation(bed, dbi1, dbi2, dbi3)
if (not strandenforced) or strandcol == 'ProperStrand':
curr_anno_arr = (str(f) for f in [
outputbam.getrname(
record.tid), bed_start, bed_end, strand,
record.seq, 'genome', typ, name, subtype, strandcol
])
if not record.qname in newdict:
newdict[record.qname] = '\t'.join(curr_anno_arr)
if not Included(record, True, mapq_thred):
# not unique
newdict[record.qname] = [newdict[record.qname]]
else:
if type(newdict[record.qname]) is str:
newdict[record.qname] = [newdict[record.qname]]
newdict[record.qname].append('\t'.join(curr_anno_arr))
IsMapped = True
else:
strandcol = '.'
curr_anno_arr = (str(f) for f in [
outputbam.getrname(record.tid), record.aend - record.alen +
1, record.aend, strand, record.seq, 'genome', strandcol
])
if not record.qname in newdict:
newdict[record.qname] = '\t'.join(curr_anno_arr)
if not Included(record, True, mapq_thred):
# not unique
newdict[record.qname] = [newdict[record.qname]]
else:
if type(newdict[record.qname]) is str:
newdict[record.qname] = [newdict[record.qname]]
newdict[record.qname].append('\t'.join(curr_anno_arr))
IsMapped = True
newanno = dict(results_dict.items() + newdict.items())
return newanno
def Main():
args=ParseArg()
distance=args.distance*1000
pair_dist=args.pair_dist
print "\nChecking if linkedPair file is tabixed..."
if not os.path.isfile(args.linkedPair):
print "LinkedPair file is not exist, please check!!"
sys.exit(0)
if not os.path.isfile(args.linkedPair+".tbi"):
print " tabix-ing..."
os.system("sort -k1,1 -k2,2n "+args.linkedPair+" > temp_linkedPair.txt")
os.system("bgzip temp_linkedPair.txt")
os.system("tabix -p bed temp_linkedPair.txt.gz")
linkedPair='temp_linkedPair.txt.gz'
else:
linkedPair=args.linkedPair
print " linkedPair file is tabixed."
print "\nTabixing the interaction file..."
os.system("sort -k1,1 -k2,2n "+args.interaction+" > temp_interaction.txt")
os.system("bgzip temp_interaction.txt")
os.system("tabix -p bed temp_interaction.txt.gz")
print " interaction file is tabixed."
# start column number for second regions
# s1 for interaction file and s2 for linkedPair file
(s1,s2)=args.start
print "\nExtracting interaction information..."
if args.n:
Interactions=open(args.interaction,'r')
l=Interactions.read().split('\n')[args.n-1].split('\t')
part1=Bed(l[0:6])
part2=Bed(l[s1:(s1+6)])
elif len(args.r)==2:
part1=read_region(args.r[0])
part2=read_region(args.r[1])
else:
print >> sys.stderr, "need to specify two regions using '-r'"
if "chr" not in part1.chr or "chr" not in part2.chr:
print >> sys.stderr, "This program only works for genomic regions."
exit(0)
start1=part1.start-distance
end1=part1.stop+distance
start2=part2.start-distance
end2=part2.stop+distance
# if the searched regions for part1 and part2 are overlapped, using the same regions for both part
if part1.overlap(part2,-2*distance):
start1=min(start1,start2)
start2=min(start1,start2)
end1=max(end1,end2)
end2=max(end1,end2)
# initialize figure
print "\n Start plot interaction: "+part1.str_region()+" <-> "+part2.str_region()
col1="#4F81BD"
col2="#C0504D"
fig = plt.figure(figsize=(8,4))
ax1 = plt.subplot(111,frameon=False,yticks=[])
plt.tick_params(axis="y",which="both",left="off",right="off",labelleft="off") # remove y ticks
plt.subplots_adjust(top=0.75)
ax2 = ax1.twiny()
ax1.set_xlim(start1,end1)
ax2.set_xlim(start2,end2)
ax1.set_ylim(0,1)
ax2.set_ylim(0,1)
#set x ticks withour offset
locs=ax1.get_xticks()
ax1.set_xticklabels(map(lambda x: "%i"%x, locs),fontsize=8)
locs=ax2.get_xticks()
ax2.set_xticklabels(map(lambda x: "%i"%x, locs),fontsize=8)
# input bigWig file for phyloP score
bw_phyloP = BigWigFile(open(args.phyloP_wig))
print "\nStart draw gene track"
gene_dbi=DBI.init(args.genebed,"bed")
print " genebed indexed!"
print " Plot gene track for Part1"
gene1_top=Genetrack(Bed([part1.chr,start1,end1]),gene_dbi,ax1,0.08)
wig1_top=Wigtrack(Bed([part1.chr,start1,end1]), bw_phyloP, ax1, gene1_top,col1)
y_1=wig1_top+0.1
y_2=y_1+0.2
print " Plot gene track for Part2"
gene2_top=Genetrack(Bed([part2.chr,start2,end2]),gene_dbi,ax2,y_2+0.08)
wig2_top=Wigtrack(Bed([part2.chr,start2,end2]), bw_phyloP, ax2, gene2_top,col2)
print "\nQuery interactions within +-%dkbp of interaction"%(distance/1000)
os.system("tabix temp_interaction.txt.gz %s:%i-%i > temp2.txt"%(part1.chr,start1,end1))
print "\nList of interactions plotted: "
k=1
cmap=cm.get_cmap('Paired', 10)
cmap=cmap(range(10))
for b in read_interaction("temp2.txt",s1):
#if args.Slim and b[0].overlap(b[1],-pair_dist): continue
if Bed([part2.chr,start2,end2]).overlap(b[1],0):
k+=1
x1_2_start=transform(b[0].start,start1,end1,start2,end2)
x1_2_end=transform(b[0].stop,start1,end1,start2,end2)
ax2.add_patch(matplotlib.patches.Polygon([[x1_2_start,y_1+0.04],[x1_2_end,y_1+0.04],[b[1].stop,y_2],[b[1].start,y_2]],color=cmap[k%10],alpha=0.4,lw=0.5))
ax1.add_patch(matplotlib.patches.Rectangle((b[0].start,y_1),b[0].stop-b[0].start,0.04,color=col1,lw=0.5))
ax2.add_patch(matplotlib.patches.Rectangle((b[1].start,y_2),b[1].stop-b[1].start,0.04,color=col2,lw=0.5))
print " "+b[0].str_region()+" <-> "+b[1].str_region()
ax1.plot([start1,end1],[y_1+0.02,y_1+0.02],color=col1,linewidth=1,alpha=0.7)
ax2.plot([start2,end2],[y_2+0.02,y_2+0.02],color=col2,linewidth=1,alpha=0.7)
print "\nQuery linkedPairs within +-%dkbp of interaction"%(distance/1000)
os.system("tabix "+linkedPair+" %s:%i-%i > temp2.txt"%(part1.chr,start1,end1))
print "\nList of linked pairs plotted: "
for b in read_interaction("temp2.txt",s2):
col='k'
if args.Slim and SingleFragment(b[0],b[1],pair_dist): continue
if SingleFragment(b[0],b[1],pair_dist): col='#03C03C'
if part1.overlap(b[0],-distance) and part2.overlap(b[1],-distance):
x1_2_start=transform(b[0].start,start1,end1,start2,end2)
x1_2_end=transform(b[0].stop,start1,end1,start2,end2)
if b[0].strand=='-':
connect1=x1_2_start
else:
connect1=x1_2_end
if b[1].strand=="-":
connect2=b[1].start
else:
connect2=b[1].stop
ax2.plot([connect1,connect2],[y_1+0.02,y_2+0.02],color=col,alpha=0.3,lw=0.5)
ax1.plot([b[0].start,b[0].stop],[y_1+0.02,y_1+0.02],color=col,alpha=0.3,lw=0.8)
ax2.plot([b[1].start,b[1].stop],[y_2+0.02,y_2+0.02],color=col,alpha=0.3,lw=0.8)
# print " "+b[0].str_region()+" <-> "+b[1].str_region()
plt.text(0.5, 1.15, part1.str_region()+" <-> "+part2.str_region(),
horizontalalignment='center',
fontsize=10,
transform = ax1.transAxes)
plt.text(0.5, 1.10, "Distance: +-%dkbp of interaction"%(distance/1000),
horizontalalignment='center',
fontsize=8,
transform = ax1.transAxes)
ax1.text(part1.center,y_1-0.03,"|".join([part1.type,part1.name,part1.subtype]),
verticalalignment='center', horizontalalignment='center',fontsize=8,color=col1)
ax2.text(part2.center,y_2+0.07,"|".join([part2.type,part2.name,part2.subtype]),
verticalalignment='center', horizontalalignment='center',fontsize=8,color=col2)
ax1.set_ylim(0,wig2_top+0.1)
ax2.set_ylim(0,wig2_top+0.1)
ax1.text(start1, 0.05, part1.chr,horizontalalignment='left',fontsize=8)
ax2.text(start2, wig2_top+0.04, part2.chr,horizontalalignment='left',fontsize=8)
plt.savefig(args.output)
plt.show()
# remove temp file
os.system("rm temp_interaction.txt.gz*")
if not os.path.isfile(args.linkedPair+".tbi"):
os.system("rm temp_linkedPair.txt.gz*")
os.system("rm temp2.txt")
def Main():
"""
IO TEMPLATE
"""
global args, out
args = ParseArg()
fin = IO.fopen(args.input, "r")
out = IO.fopen(args.output, "w")
"""
END OF IO TEMPLATE
"""
print >> out, "# This data was generated by program ", sys.argv[0], " (version: %s)" % VERSION,
print >> out, "in bam2x ( https://github.com/nimezhu/bam2x )"
print >> out, "# Date: ", time.asctime()
print >> out, "# The command line is :"
print >> out, "#\t", " ".join(sys.argv)
hSites = {}
donorSites = {}
acceptorSites = {}
if args.genome is not None:
genome = DBI.init(args.genome, "genome")
else:
genome = None
j = 0
for j, i in enumerate(TableIO.parse(fin, "bam2bed12", references=fin.references, strand=args.strand)):
# print >>out,i
if j % 1000 == 0:
print >>sys.stderr, "processing ", j, "reads \r",
for intron in i.Introns():
if len(intron) < args.intron_min_length:
continue
donor = intron.head()
# print >>sys.stderr,intron
# print >>sys.stderr,donor
donorID = bedToID(donor)
if donorSites.has_key(donorID):
donorSites[donorID] += 1
else:
donorSites[donorID] = 1
acceptor = intron.tail()
acceptorID = bedToID(acceptor)
if acceptorSites.has_key(acceptorID):
acceptorSites[acceptorID] += 1
else:
acceptorSites[acceptorID] = 1
"""
if genome is not None:
s=genome.query(intron.head()).upper()+".."+genome.query(intron.tail()).upper()
if hSites.has_key(s):
hSites[s]+=1
else:
hSites[s]=1
"""
donors = []
for key in donorSites.keys():
a = key.split("\t")
donors.append(Bed([a[0], a[1], a[2], "noname_donor", donorSites[key], a[3]]))
donors.sort()
for i, x in enumerate(donors):
x.id = "donor_" + str(i)
print >> out, x, "\t", genome.query(x).upper()
acceptors = []
for key in acceptorSites.keys():
a = key.split("\t")
acceptors.append(Bed([a[0], a[1], a[2], "noname_acceptor", acceptorSites[key], a[3]]))
acceptors.sort()
for i, x in enumerate(acceptors):
x.id = "acceptor_" + str(i)
print >> out, x, "\t", genome.query(x).upper()
def genome_annotation(
outputbam,
annotationfile,
detail,
annotationRepeat,
mapq_thred,
strandenforced=False,
posstrand=True,
requireUnique=False,
results_dict=dict(),
):
# annotationfile is annotation file
# detail is db_detail file
if annotationfile:
dbi1 = DBI.init(annotationfile, "bed")
dbi2 = DBI.init(detail, "bed")
dbi3 = DBI.init(annotationRepeat, "bed")
newdict = dict()
# funmap = open(unmapfilename, 'w')
for record in outputbam:
# print >> sys.stderr, record.qname
if "N" not in record.cigarstring:
anno_start = record.pos
anno_end = record.aend
bed_start = record.pos
bed_end = record.aend
else:
bed_list, anno_start, anno_end = Exon_junction(record)
bed_start = ",".join([str(f[0]) for f in bed_list])
bed_end = ",".join([str(f[1]) for f in bed_list])
# print anno_start,anno_end,bed_start,bed_end
IsMapped = False
if Included(record, requireUnique, mapq_thred):
strandactual = "+" if posstrand else "-"
strand = "+"
if record.is_reverse:
strandactual = "-" if posstrand else "+"
strand = "-"
if annotationfile:
bed = Bed([outputbam.getrname(record.tid), anno_start, anno_end, ".", 0.0, strandactual])
[typ, name, subtype, strandcol] = annotation(bed, dbi1, dbi2, dbi3)
if (not strandenforced) or strandcol == "ProperStrand":
curr_anno_arr = (
str(f)
for f in [
outputbam.getrname(record.tid),
bed_start,
bed_end,
strand,
record.seq,
"genome",
typ,
name,
subtype,
strandcol,
]
)
if not record.qname in newdict:
newdict[record.qname] = "\t".join(curr_anno_arr)
if not Included(record, True, mapq_thred):
# not unique
newdict[record.qname] = [newdict[record.qname]]
else:
if type(newdict[record.qname]) is str:
newdict[record.qname] = [newdict[record.qname]]
newdict[record.qname].append("\t".join(curr_anno_arr))
IsMapped = True
else:
strandcol = "."
curr_anno_arr = (
str(f)
for f in [
outputbam.getrname(record.tid),
record.aend - record.alen + 1,
record.aend,
strand,
record.seq,
"genome",
strandcol,
]
)
if not record.qname in newdict:
newdict[record.qname] = "\t".join(curr_anno_arr)
if not Included(record, True, mapq_thred):
# not unique
newdict[record.qname] = [newdict[record.qname]]
else:
if type(newdict[record.qname]) is str:
newdict[record.qname] = [newdict[record.qname]]
newdict[record.qname].append("\t".join(curr_anno_arr))
IsMapped = True
newanno = dict(results_dict.items() + newdict.items())
return newanno
def Main():
args = ParseArg()
fastq1 = open("simulated_" + str(args.num) + "_read_R1.fastq", "w")
fastq2 = open("simulated_" + str(args.num) + "_read_R2.fastq", "w")
RNA = TableIO.parse(args.annotation, 'bed')
# create a dictionary for all RNAs pools except rRNA
RNAs = {}
for b in RNA:
if b.id.startswith('rRNA'): continue
if b.chr.startswith('chrM') or b.chr.startswith('chrNT'): continue
Type = b.id.split(".")[0]
if Type in RNAs:
RNAs[Type].append(b)
else:
RNAs[Type] = [b]
#---------------- read linker seq ------------------
linkers = []
for i in open(args.linker, 'r'):
i = i.strip()
linkers.append(i)
#---------------------------------------------------
#---------------- read barcode ---------------------
barcodes = []
for i in open(args.barcode, 'r'):
i = i.strip()
barcodes.append(i)
#---------------------------------------------------
# sample different classes: LinkerOnly, Nolinker, RNA1-linker, linker-RNA2, RNA1-linker-RNA2
xk = range(5)
pk = args.parameter
custm = stats.rv_discrete(name='custm', values=(xk, pk))
Class_index = custm.rvs(size=args.num)
# specify output
out = open(args.output, 'w')
# initiate the annotation database
if args.db_detail:
print >> sys.stderr, " # Index for the annotation database"
dbi1 = DBI.init(args.annotation, "bed")
dbi2 = DBI.init(args.db_detail, "bed")
dbi3 = DBI.init(
"/home/yu68/bharat-interaction/new_lincRNA_data/mouse.repeat.txt",
"bed")
print >> sys.stderr, " # Start to simulate reads"
t0 = time.time()
for i in range(0, args.num):
pair_id = "read_" + str(i)
# barcode
randSeq = "".join([random.choice("ACGT") for x in range(6)])
barcode = randSeq[0:4] + barcodes[0] + randSeq[4:6]
index = Class_index[i] # index for different classes of fragments
# Sample RNA1 and RNA2
RNA1_len = random.randrange(15, 150)
b, Type = randRegion(RNA1_len, RNAs)
RNA1_seq = fetchSeq(b.chr, b.start, b.stop, b.strand, args.genomeFa,
args.spath)
if args.db_detail:
[name1, typ1, subtype1] = annotation(b, dbi1, dbi2, dbi3)
RNA1_str = "\t".join(
str(f) for f in
[b.chr, b.start, b.stop, b.strand, name1, typ1, subtype1])
else:
RNA1_str = "\t".join(
str(f) for f in [b.chr, b.start, b.stop, b.strand, Type])
RNA2_len = random.randrange(15, 150)
b, Type = randRegion(RNA2_len, RNAs)
RNA2_seq = fetchSeq(b.chr, b.start, b.stop, b.strand, args.genomeFa,
args.spath)
if args.db_detail:
[name2, typ2, subtype2] = annotation(b, dbi1, dbi2, dbi3)
RNA2_str = "\t".join(
str(f) for f in
[b.chr, b.start, b.stop, b.strand, name2, typ2, subtype2])
else:
RNA2_str = "\t".join(
str(f) for f in [b.chr, b.start, b.stop, b.strand, Type])
# fragment is the recovered cDNA fragment
if index == 1: # single RNA or RNA1-RNA2
if random.choice([0, 1]) == 0: # single RNAs
fragment = barcode + RNA1_seq + RNA2_seq
print >> out, pair_id + "\t%d\tRNA1-RNA2\t0" % (
len(fragment)) + "\t" + RNA1_str + '\t' + RNA2_str
else: # RNA1-RNA2
fragment = barcode + RNA1_seq
print >> out, pair_id + "\t%d\tsingleRNA\t0" % (
len(fragment)) + "\t" + RNA1_str
else:
linker_n = random.choice([1, 2]) # number of linkers in fragment
linker = "".join([linkers[0]] * linker_n)
if index == 0:
fragment = barcode + linker
print >> out, pair_id + "\t%d\tlinkerOnly\t%d" % (
len(fragment), linker_n)
elif index == 2:
fragment = barcode + RNA1_seq + linker
print >> out, pair_id + "\t%d\tRNA1-linker\t%d" % (
len(fragment), linker_n) + "\t" + RNA1_str
elif index == 3:
fragment = barcode + linker + RNA2_seq
print >> out, pair_id + "\t%d\tlinker-RNA2\t%d" % (
len(fragment), linker_n) + "\t" + RNA2_str
elif index == 4:
fragment = barcode + RNA1_seq + linker + RNA2_seq
print >> out, pair_id + "\t%d\tRNA1-linker-RNA2\t%d" % (len(
fragment), linker_n) + "\t" + RNA1_str + "\t" + RNA2_str
read1, read2 = generatePairs(fragment, args.len, args.errorRate)
score = []
for j in range(0, args.len):
score.append(random.randrange(10, 40))
record1 = SeqRecord(Seq(read1, generic_dna), id=pair_id)
record1.letter_annotations["phred_quality"] = score
record2 = SeqRecord(Seq(read2, generic_dna), id=pair_id)
record2.letter_annotations["phred_quality"] = score
SeqIO.write(record1, fastq1, "fastq")
SeqIO.write(record2, fastq2, "fastq")
if i % 100 == 0:
print >> sys.stderr, "generate pairs %d\r" % (i),
fastq1.close()
fastq2.close()
out.close()
print time.time() - t0
def Main():
t1 = time()
args = ParseArg()
inp = open(args.input, 'r')
min_clusterS = args.min_clusterS
min_interaction = args.min_interaction
p_value = args.p_value
output = open(args.output, 'w')
outputIntra = open(args.output_intra, 'w')
hasAnnotation = False
if args.annotation:
dbi = DBI.init(args.annotation, "bed")
hasAnnotation = True
else:
dbi = False
if args.annotation_repeat:
dbirepeat = DBI.init(args.annotation_repeat, "bed")
hasAnnotationRepeat = True
else:
dbirepeat = False
#store count of RNA for part1 and part2
part = {}
k = 0
sgcount = 0 #single fragment count
print >> sys.stderr, "# Inputing data..."
interaction = {} # store number of interactions for different RNA
selfinteraction = {}
#Types = ["snoRNA","protein_coding","snRNA","lincRNA","tRNA","misc_RNA","pseudogene","miRNA","antisense","sense_intronic","non_coding","processed_transcript","sense_overlapping","rRNA_repeat","rRNA"]
for line in inp.read().split('\n'):
if line == '': continue
line = line.strip().split('\t')
p1 = annotated_bed_proper(line[0:10], id=k, cluster=1)
p2 = annotated_bed_proper(line[11:], id=k, cluster=1)
if isinstance(p1.start, list):
p1.start = int(p1.start[0])
p1.end = int(p1.end[-1])
if isinstance(p2.start, list):
p2.start = int(p2.start[0])
p2.end = int(p2.end[-1])
if SingleFragment(p1, p2):
sgcount += 1
continue
k += 1
#if p1.subtype=="intron" or p2.subtype=="intron": continue
#if p1.type in Types:
try:
p1_name = GetAnnotationName(p1, hasAnnotation, dbi,
hasAnnotationRepeat, dbirepeat)
if p1_name not in part:
part[p1_name] = 1
else:
part[p1_name] += 1
#if p2.type in Types:
p2_name = GetAnnotationName(p2, hasAnnotation, dbi,
hasAnnotationRepeat, dbirepeat)
if not p1_name == p2_name: # count once for self-interaction
if p2_name not in part:
part[p2_name] = 1
else:
part[p2_name] += 1
#if p1.type in Types and p2.type in Types:
if p1_name == p2_name:
if p1_name not in selfinteraction:
selfinteraction[p1_name] = copy.deepcopy(p1)
else:
selfinteraction[p1_name].Update(p1.start, p1.end)
selfinteraction[p1_name].Update(p2.start, p2.end)
selfinteraction[p1_name].cluster += 1
else:
if p1_name > p2_name:
temp = p1
p1 = p2
p2 = temp
tempName = p1_name
p1_name = p2_name
p2_name = tempName
inter_name = p1_name + "--" + p2_name
if inter_name not in interaction:
interaction[inter_name] = [
copy.deepcopy(p1),
copy.deepcopy(p2)
]
else:
interaction[inter_name][0].Update(p1.start, p1.end)
interaction[inter_name][1].Update(p2.start, p2.end)
interaction[inter_name][0].cluster += 1
except Exception as e:
print >> sys.stderr, e
if k % 20000 == 0:
print >> sys.stderr, " Reading %d pairs of segments\r" % (k),
print >> sys.stdout, "Get total %d pairs." % (k)
print >> sys.stdout, "Single fragment count: %d." % (sgcount)
print >> sys.stdout, " number of different RNAs is %d " % (
len(part))
total = k # total pairs used
n = 0
k = 0 # record number of strong interactions
for i in interaction:
n += 1
count = interaction[i][0].cluster
if count < min_interaction: continue
p1_name = i.split("--")[0]
p2_name = i.split("--")[1]
P1 = interaction[i][0]
P2 = interaction[i][1]
P1.cluster = part[p1_name]
P2.cluster = part[p2_name]
if part[p1_name] < min_clusterS or part[p2_name] < min_clusterS:
continue
real_p = 1 - hypergeom.cdf(count, total, part[p1_name], part[p2_name])
if real_p <= p_value:
k = k + 1
try:
log_p = math.log(real_p)
except:
log_p = -float("Inf")
print >> output, str(P1) + '\t' + str(P2) + '\t%d\t%.4f' % (count,
log_p)
if n % 500 == 0:
print >> sys.stderr, " Progress ( %d / %d )\r" % (
n, len(interaction)),
k1 = 0
for i in selfinteraction:
n += 1
count = selfinteraction[i].cluster
if count < min_interaction: continue
p1_name = i
P1 = selfinteraction[i]
P1.cluster = part[p1_name]
if part[p1_name] < min_clusterS: continue
k1 = k1 + 1
print >> outputIntra, str(P1) + '\t%d' % (count)
if n % 500 == 0:
print >> sys.stderr, " Progress ( %d / %d )\r" % (
n, len(interaction)),
print >> sys.stdout, "# Find %d strong and %d self interactions. Cost time: %.2f s" % (
k, k1, time() - t1)
def Main():
t1=time()
global min_interaction, p_value
args=ParseArg()
inp = open(args.input, 'r')
min_clusterS=args.min_clusterS
min_interaction=args.min_interaction
p_value=args.p_value
output=open(args.output,'w')
ncpus=args.parallel
#store genomic location of part1 and part2
part1=[]
part2=[]
k=0
print >> sys.stderr,"# Inputing data..."
chr_list=[]
for line in inp.read().split('\n'):
if line=='': continue
line=line.strip().split('\t')
p1=annotated_bed(line[0:10],id=k)
p2=annotated_bed(line[11:],id=k)
if isinstance(p1.start, list):
p1.start=int(p1.start[0])
p1.end=int(p1.end[-1])
if isinstance(p2.start, list):
p2.start=int(p2.start[0])
p2.end=int(p2.end[-1])
if SingleFragment(p1,p2): continue
k+=1
part1.append(p1)
part2.append(p2)
if p1.chr not in chr_list: chr_list.append(p1.chr)
if p2.chr not in chr_list: chr_list.append(p2.chr)
if k%20000==0:
print >> sys.stderr," Reading %d pairs of segments\r"%(k),
print >> sys.stderr,"Get total %d pairs."%(k)
if len(part1)!=len(part2):
print >> sys.stderr, "## ERROR: number of regions in two part not match!!"
sys.exit(0)
# sort in genomic order, easy for clustering
part1=sorted(part1, key=attrgetter('start'))
part1=sorted(part1, key=attrgetter('chr'))
part2=sorted(part2, key=attrgetter('start'))
part2=sorted(part2, key=attrgetter('chr'))
# for parallel computing
print >>sys.stderr,"# Generating clusters for two parts..."
# tuple of all parallel python servers to connect with
ppservers = ()
job_server = pp.Server(ncpus, ppservers=ppservers)
jobs1=[]
jobs2=[]
for chro in chr_list:
part1_temp=filter(lambda p: p.chr==chro, part1)
if len(part1_temp)>0:
jobs1.append(job_server.submit(cluster_regions,(part1_temp,min_clusterS),(annotated_bed,),("UnionFind","copy",)))
part2_temp=filter(lambda p: p.chr==chro, part2)
if len(part2_temp)>0:
jobs2.append(job_server.submit(cluster_regions,(part2_temp,min_clusterS),(annotated_bed,),("UnionFind","copy",)))
cluster_pool1={}
part1=[]
for job in jobs1:
try:
part1=part1+job()[1]
cluster_pool1.update(job()[0])
except:
print >> sys.stderr, "Wrong in %s, part1"%(job()[2])
continue
cluster_pool2={}
part2=[]
for job in jobs2:
try:
part2=part2+job()[1]
cluster_pool2.update(job()[0])
except:
continue
print >>sys.stderr," cluster number for part1 is %d "%(len(cluster_pool1))
print >>sys.stderr," cluster number for part2 is %d "%(len(cluster_pool2))
# sort back to pair two parts
part1=sorted(part1, key=attrgetter('id'))
part2=sorted(part2, key=attrgetter('id'))
print >> sys.stderr,"size of part1&2:",len(part1),len(part2)
c_interaction={}
for i in range(len(part1)):
region1=str(part1[i])
region2=str(part2[i])
try:
inter=part1[i].cluster+"--"+part2[i].cluster
except:
print >> sys.stderr,i,part1[i].cluster,part2[i].cluster
sys.exit()
if c_interaction.has_key(inter):
c_interaction[inter]+=1
else:
c_interaction[inter]=1
# annotation file
print >> sys.stderr,"# Indexing annotation files"
dbi_all=DBI.init(args.annotation,"bed")
dbi_detail=DBI.init(args.db_detail,"bed")
dbi_repeat=DBI.init("/home/yu68/bharat-interaction/new_lincRNA_data/mouse.repeat.txt","bed")
print >> sys.stderr,"# finding strong interactions from clusters..."
k=0 # record for strong interactions
n=0
# annotation file
for interaction in c_interaction:
n=n+1
count=c_interaction[interaction]
if count<min_interaction: continue
i=interaction.split("--")[0]
j=interaction.split("--")[1]
try: # we select clusters with size no less than 5, so some interactions cannot be found in clusters
count1=cluster_pool1[i].cluster
count2=cluster_pool2[j].cluster
except:
continue
real_p=1-hypergeom.cdf(count,len(part1),count1,count2)
if real_p<=p_value:
k=k+1
cluster_pool1[i].Annotate(dbi_all,dbi_detail,dbi_repeat)
cluster_pool2[j].Annotate(dbi_all,dbi_detail,dbi_repeat)
try:
log_p = math.log(real_p)
except:
log_p = -float("Inf")
print >> output,str(cluster_pool1[i])+'\t'+str(cluster_pool2[j])+'\t%d\t%.4f'%(count,log_p)
if n%1000==0: print >> sys.stderr, " Progress ( %d / %d )\r"%(n,len(c_interaction)),
print >> sys.stderr,"# Find %d strong interactions. Cost time: %.2f s"%(k,time()-t1)
if args.FDR:
print >> sys.stderr, "# Permutated results:"
for i in range(10):
shuffle(part2)
[n_r_I,n_r_SI]=Random_strongInteraction(part1,part2,cluster_pool1,cluster_pool2)
print >> sys.stderr, " ",i, n_r_I, n_r_SI, n_r_SI*1.0/n_r_I
def Main():
t1=time()
args=ParseArg()
inp = open(args.input, 'r')
min_clusterS=args.min_clusterS
min_interaction=args.min_interaction
p_value=args.p_value
output=open(args.output,'w')
outputIntra = open(args.output_intra, 'w')
hasAnnotation = False
if args.annotation:
dbi = DBI.init(args.annotation, "bed")
hasAnnotation = True
else:
dbi = False
if args.annotation_repeat:
dbirepeat = DBI.init(args.annotation_repeat, "bed")
hasAnnotationRepeat = True
else:
dbirepeat = False
#store count of RNA for part1 and part2
part={}
k=0
sgcount = 0 #single fragment count
print >> sys.stderr,"# Inputing data..."
interaction = {} # store number of interactions for different RNA
selfinteraction = {}
#Types = ["snoRNA","protein_coding","snRNA","lincRNA","tRNA","misc_RNA","pseudogene","miRNA","antisense","sense_intronic","non_coding","processed_transcript","sense_overlapping","rRNA_repeat","rRNA"]
for line in inp.read().split('\n'):
if line=='': continue
line=line.strip().split('\t')
p1=annotated_bed_proper(line[0:10],id=k,cluster=1)
p2=annotated_bed_proper(line[11:],id=k,cluster=1)
if isinstance(p1.start, list):
p1.start=int(p1.start[0])
p1.end=int(p1.end[-1])
if isinstance(p2.start, list):
p2.start=int(p2.start[0])
p2.end=int(p2.end[-1])
if SingleFragment(p1,p2):
sgcount += 1
continue
k+=1
#if p1.subtype=="intron" or p2.subtype=="intron": continue
#if p1.type in Types:
try:
p1_name = GetAnnotationName(p1, hasAnnotation, dbi, hasAnnotationRepeat, dbirepeat)
if p1_name not in part:
part[p1_name]=1
else:
part[p1_name]+=1
#if p2.type in Types:
p2_name = GetAnnotationName(p2, hasAnnotation, dbi, hasAnnotationRepeat, dbirepeat)
if not p1_name == p2_name: # count once for self-interaction
if p2_name not in part:
part[p2_name]=1
else:
part[p2_name]+=1
#if p1.type in Types and p2.type in Types:
if p1_name == p2_name:
if p1_name not in selfinteraction:
selfinteraction[p1_name]=copy.deepcopy(p1)
else:
selfinteraction[p1_name].Update(p1.start, p1.end)
selfinteraction[p1_name].Update(p2.start, p2.end)
selfinteraction[p1_name].cluster += 1
else:
if p1_name>p2_name:
temp = p1
p1 = p2
p2 = temp
tempName = p1_name
p1_name = p2_name
p2_name = tempName
inter_name = p1_name + "--" + p2_name
if inter_name not in interaction:
interaction[inter_name]=[copy.deepcopy(p1),copy.deepcopy(p2)]
else:
interaction[inter_name][0].Update(p1.start,p1.end)
interaction[inter_name][1].Update(p2.start,p2.end)
interaction[inter_name][0].cluster+=1
except Exception as e:
print >> sys.stderr, e
if k%20000==0:
print >> sys.stderr," Reading %d pairs of segments\r"%(k),
print >> sys.stdout,"Get total %d pairs."%(k)
print >> sys.stdout,"Single fragment count: %d."%(sgcount)
print >>sys.stdout," number of different RNAs is %d "%(len(part))
total = k # total pairs used
n=0
k=0 # record number of strong interactions
for i in interaction:
n+=1
count = interaction[i][0].cluster
if count < min_interaction: continue
p1_name = i.split("--")[0]
p2_name = i.split("--")[1]
P1 = interaction[i][0]
P2 = interaction[i][1]
P1.cluster = part[p1_name]
P2.cluster = part[p2_name]
if part[p1_name]<min_clusterS or part[p2_name]<min_clusterS: continue
real_p=1-hypergeom.cdf(count,total,part[p1_name],part[p2_name])
if real_p<=p_value:
k=k+1
try:
log_p = math.log(real_p)
except:
log_p = -float("Inf")
print >> output, str(P1)+'\t'+str(P2)+'\t%d\t%.4f'%(count,log_p)
if n%500==0: print >> sys.stderr, " Progress ( %d / %d )\r"%(n,len(interaction)),
k1=0
for i in selfinteraction:
n+=1
count = selfinteraction[i].cluster
if count < min_interaction: continue
p1_name = i
P1 = selfinteraction[i]
P1.cluster = part[p1_name]
if part[p1_name]<min_clusterS: continue
k1=k1+1
print >> outputIntra, str(P1)+'\t%d'%(count)
if n%500==0: print >> sys.stderr, " Progress ( %d / %d )\r"%(n,len(interaction)),
print >> sys.stdout,"# Find %d strong and %d self interactions. Cost time: %.2f s"%(k,k1,time()-t1)
def genome_annotation(outputbam, annotationfile, detail, readfilename, unmapfilename, strandenforced = False, posstrand = True, requireUnique = False, results_dict = dict()):
# annotationfile is annotation file
# detail is db_detail file
if annotationfile:
dbi1=DBI.init(annotationfile,"bed")
dbi2=DBI.init(detail,"bed")
dbi3=DBI.init("/home/yu68/bharat-interaction/new_lincRNA_data/mouse.repeat.txt","bed")
newdict = dict()
funmap = open(unmapfilename, 'w')
for record in outputbam:
# print >> sys.stderr, record.qname
IsMapped = False
if Included(record, requireUnique):
strandactual = ("+" if posstrand else "-")
strand = "+"
if record.is_reverse:
strandactual = ("-" if posstrand else "+")
strand = "-"
if annotationfile:
bed=Bed([outputbam.getrname(record.tid), record.pos, record.aend,'.',0.0,strandactual])
[typ, name, subtype, strandcol] = annotation(bed,dbi1,dbi2,dbi3)
if (not strandenforced) or strandcol == 'ProperStrand':
curr_anno_arr = (str(f) for f in [outputbam.getrname(record.tid), record.pos, record.aend, strand, record.seq, 'genome', typ, name, subtype, strandcol])
if not record.qname in newdict:
newdict[record.qname] = '\t'.join(curr_anno_arr)
if not Included(record, True):
# not unique
newdict[record.qname] = [newdict[record.qname]]
else:
if type(newdict[record.qname]) is str:
newdict[record.qname] = [newdict[record.qname]]
newdict[record.qname].append('\t'.join(curr_anno_arr))
IsMapped = True
else:
strandcol = '.'
curr_anno_arr = (str(f) for f in [outputbam.getrname(record.tid), record.aend - record.alen + 1, record.aend, strand, record.seq, 'genome', strandcol])
if not record.qname in newdict:
newdict[record.qname] = '\t'.join(curr_anno_arr)
if not Included(record, True):
# not unique
newdict[record.qname] = [newdict[record.qname]]
else:
if type(newdict[record.qname]) is str:
newdict[record.qname] = [newdict[record.qname]]
newdict[record.qname].append('\t'.join(curr_anno_arr))
IsMapped = True
if not IsMapped:
# output all pairs that cannot be mapped on both sides as unmaped pairs into two fasta file
seq = record.seq
if record.is_reverse:
seq = revcomp(record.seq, rev_table)
unmap_rec = SeqRecord(Seq(seq, IUPAC.unambiguous_dna), id = record.qname, description='')
SeqIO.write(unmap_rec, funmap, "fasta")
funmap.close()
newanno = dict(results_dict.items() + newdict.items())
return newanno
def Main():
global args
args = ParseArg()
if args.output == "stdout":
out = sys.stdout
else:
try:
out = open(args.output, "w")
except IOError:
print >> sys.stderr, "can't open file ", args.output, "to write. Using stdout instead"
out = sys.stdout
dbi = DBI.init(args.db, "genebed")
count = {}
count["Intergenic"] = 0
for x in TableIO.parse(args.input, args.input_format):
flag = 0
gene = ""
for hit in dbi.query(x):
flag = 1
if hit.align_id == gene:
continue
gene = hit.align_id
#print hit
#print hit.cds_start,hit.cds_stop
if (hit.cds_start == hit.cds_stop):
if hit.align_id[0:3] == "Mir":
loc = "MiRNA"
else:
loc = "Non-coding"
elif hit.strand == "+":
if x.stop <= hit.cds_start:
loc = "5-UTR"
elif x.start >= hit.cds_stop:
loc = "3-UTR"
else:
loc = judge_exon(x, hit)
else:
if x.stop <= hit.cds_start:
loc = "3-UTR"
elif x.start >= hit.cds_stop:
loc = "5-UTR"
else:
loc = judge_exon(x, hit)
print >> out, "\t".join(
str(f) for f in [
x.chr, x.start, x.stop, x.id, x.score, x.strand,
hit.align_id, loc
])
if count.has_key(loc):
count[loc] += 1
else:
count[loc] = 1
if flag == 0:
print >> out, "\t".join(
str(f) for f in [
x.chr, x.start, x.stop, x.id, x.score, x.strand, "None",
"Intergenic"
])
count["Intergenic"] += 1
out2 = open(args.output.split(".")[0] + ".cisStat", "w")
for key in sorted(count.keys()):
print >> out2, key + "\t" + str(count[key])
def Main():
global args,chrs,lengths,out
args=ParseArg()
if args.out=="stdout":
out=sys.stdout
else:
try:
out=open(args.out,"w")
except IOError:
print >>sys.stderr,"can't open file",args.out,"to write, using stdout instead"
out=sys.stdout
if args.bamlistA:
dbi_A=DBI.init(args.bamlistA,"bamlist")
else:
dbi_A=DBI.init(args.bamA,"bamlist")
if args.bamlistB:
dbi_B=DBI.init(args.bamlistB,"bamlist")
else:
dbi_B=DBI.init(args.bamB,"bamlist")
print_header()
'''
Priority:
Region > Annotations > chromSize
'''
if args.region:
'''
Query Only Region
'''
i=parseRegion(args.region)
for aps in QueryBed(i,dbi_A,dbi_B):
print >>out,aps
elif args.annotations:
'''
Query Regions in Bed file or VCF file etc.
'''
for i in TableIO.parse(args.annotations,args.annotation_format):
for aps in QueryBed(i,dbi_A,dbi_B):
print >>out,aps
elif args.chromsize:
'''
Query Whole Genome
Chromsize File Example:
chr1 249250621
chr2 243199373
chr3 198022430
.
.
.
'''
for x in TableIO.parse(args.chromsize):
(chr,size)=x
binsize=1000000
chr=chr.strip()
for i in xrange(0,size,binsize):
start=i
stop=i+binsize
if stop>size: stop=size
bed=Bed([chr,start,stop,".",".","."])
for aps in QueryBed(bed,dbi_A,dbi_B):
print >>out,aps
else:
print >>sys.stderr," at least one of the options -r,-g,-a are required"
exit(0)
s: start column number for second part of interaction
'''
a=open(File,'r')
for l in a.read().split('\n'):
if l.strip()=="": continue
lsep=l.split('\t')
if lsep[3] in ['+','-']:
bed1=Bed(lsep[0:3],strand=lsep[3])
bed2=Bed(lsep[s:(s+3)],strand=lsep[s+3])
else:
bed1=Bed(lsep[0:3])
bed2=Bed(lsep[s:(s+3)])
yield (bed1,bed2,lsep)
# annotation files
db="/home/yu68/bharat-interaction/new_lincRNA_data/all_RNAs-rRNA_repeat.txt"
db_detail="/home/yu68/bharat-interaction/new_lincRNA_data/Ensembl_mm9.genebed"
db_repeat="/home/yu68/bharat-interaction/new_lincRNA_data/mouse.repeat.txt"
print >>sys.stderr, "Indexing annotation files..."
ref_allRNA=DBI.init(db,"bed") # the DBI init file for bed6 file of all kinds of RNA
ref_detail=DBI.init(db_detail,"bed") # the DBI init file for bed12 file of lincRNA and mRNA with intron, exon, UTR
ref_repeat=DBI.init(db_repeat,"bed")
print >>sys.stderr, "Start to update..."
for l in read_interaction(sys.argv[1],7):
l[2][3:6] = annotation(l[0],ref_allRNA,ref_detail,ref_repeat)
l[2][10:13] = annotation(l[1],ref_allRNA,ref_detail,ref_repeat)
print "\t".join(l[2])
def Main():
args=ParseArg()
fastq1=open("simulated_"+str(args.num)+"_read_R1.fastq","w")
fastq2=open("simulated_"+str(args.num)+"_read_R2.fastq","w")
RNA=TableIO.parse(args.annotation,'bed')
# create a dictionary for all RNAs pools except rRNA
RNAs = {}
for b in RNA:
if b.id.startswith('rRNA'): continue
if b.chr.startswith('chrM') or b.chr.startswith('chrNT'): continue
Type = b.id.split(".")[0]
if Type in RNAs:
RNAs[Type].append(b)
else:
RNAs[Type]=[b]
#---------------- read linker seq ------------------
linkers=[]
for i in open(args.linker,'r'):
i=i.strip()
linkers.append(i)
#---------------------------------------------------
#---------------- read barcode ---------------------
barcodes=[]
for i in open(args.barcode,'r'):
i=i.strip()
barcodes.append(i)
#---------------------------------------------------
# sample different classes: LinkerOnly, Nolinker, RNA1-linker, linker-RNA2, RNA1-linker-RNA2
xk = range(5)
pk = args.parameter
custm = stats.rv_discrete(name='custm', values=(xk, pk))
Class_index = custm.rvs(size=args.num)
# specify output
out = open(args.output,'w')
# initiate the annotation database
if args.db_detail:
print >> sys.stderr, " # Index for the annotation database"
dbi1=DBI.init(args.annotation,"bed")
dbi2=DBI.init(args.db_detail,"bed")
dbi3=DBI.init("/home/yu68/bharat-interaction/new_lincRNA_data/mouse.repeat.txt","bed")
print >> sys.stderr, " # Start to simulate reads"
t0 = time.time()
for i in range(0,args.num):
pair_id = "read_"+str(i)
# barcode
randSeq = "".join([random.choice("ACGT") for x in range(6)])
barcode = randSeq[0:4]+barcodes[0]+randSeq[4:6]
index = Class_index[i] # index for different classes of fragments
# Sample RNA1 and RNA2
RNA1_len = random.randrange(15,150)
b,Type = randRegion(RNA1_len,RNAs)
RNA1_seq = fetchSeq(b.chr,b.start,b.stop,b.strand,args.genomeFa,args.spath)
if args.db_detail:
[name1,typ1,subtype1]=annotation(b,dbi1,dbi2,dbi3)
RNA1_str = "\t".join(str(f) for f in [b.chr,b.start,b.stop,b.strand,name1,typ1,subtype1])
else:
RNA1_str = "\t".join(str(f) for f in [b.chr,b.start,b.stop,b.strand,Type])
RNA2_len = random.randrange(15,150)
b,Type = randRegion(RNA2_len,RNAs)
RNA2_seq = fetchSeq(b.chr,b.start,b.stop,b.strand,args.genomeFa,args.spath)
if args.db_detail:
[name2,typ2,subtype2]=annotation(b,dbi1,dbi2,dbi3)
RNA2_str = "\t".join(str(f) for f in [b.chr,b.start,b.stop,b.strand,name2,typ2,subtype2])
else:
RNA2_str = "\t".join(str(f) for f in [b.chr,b.start,b.stop,b.strand,Type])
# fragment is the recovered cDNA fragment
if index == 1: # single RNA or RNA1-RNA2
if random.choice([0,1])==0: # single RNAs
fragment = barcode+RNA1_seq+RNA2_seq
print >> out, pair_id+"\t%d\tRNA1-RNA2\t0"%(len(fragment))+"\t"+RNA1_str+'\t'+RNA2_str
else: # RNA1-RNA2
fragment = barcode+RNA1_seq
print >> out, pair_id+"\t%d\tsingleRNA\t0"%(len(fragment))+"\t"+RNA1_str
else:
linker_n = random.choice([1,2]) # number of linkers in fragment
linker = "".join([linkers[0]]*linker_n)
if index == 0:
fragment = barcode+linker
print >> out, pair_id+"\t%d\tlinkerOnly\t%d"%(len(fragment),linker_n)
elif index == 2:
fragment = barcode+RNA1_seq+linker
print >> out, pair_id+"\t%d\tRNA1-linker\t%d"%(len(fragment),linker_n)+"\t"+RNA1_str
elif index == 3:
fragment = barcode+linker+RNA2_seq
print >> out, pair_id+"\t%d\tlinker-RNA2\t%d"%(len(fragment),linker_n)+"\t"+RNA2_str
elif index == 4:
fragment = barcode+RNA1_seq+linker+RNA2_seq
print >> out, pair_id+"\t%d\tRNA1-linker-RNA2\t%d"%(len(fragment),linker_n)+"\t"+RNA1_str+"\t"+RNA2_str
read1,read2 = generatePairs(fragment,args.len,args.errorRate)
score=[]
for j in range(0, args.len):
score.append(random.randrange(10,40))
record1 = SeqRecord(Seq(read1,generic_dna),id=pair_id)
record1.letter_annotations["phred_quality"] = score
record2 = SeqRecord(Seq(read2,generic_dna),id=pair_id)
record2.letter_annotations["phred_quality"] = score
SeqIO.write(record1,fastq1,"fastq")
SeqIO.write(record2,fastq2,"fastq")
if i%100==0:
print >>sys.stderr, "generate pairs %d\r"%(i),
fastq1.close()
fastq2.close()
out.close()
print time.time()-t0
def Main():
"""
IO TEMPLATE
"""
global args, out
args = ParseArg()
if args.output == "stdout":
out = sys.stdout
else:
try:
out = open(args.output, "w")
except IOError:
print >>sys.stderr, "can't open file ", args.output, "to write. Using stdout instead"
out = sys.stdout
if args.input == "stdin":
fin = sys.stdin
else:
try:
x = args.input.split(".")
if x[-1] == "gz":
fin = gzip.open(args.input, "r")
else:
fin = open(args.input, "r")
except IOError:
print >>sys.stderr, "can't read file", args.input
fin = sys.stdin
"""
END OF IO TEMPLATE
"""
print >> out, "# This data was generated by program ", sys.argv[0], " (version: %s)" % VERSION,
print >> out, "in bam2x ( https://github.com/nimezhu/bam2x )"
print >> out, "# Date: ", time.asctime()
print >> out, "# The command line is :"
print >> out, "#\t", " ".join(sys.argv)
gene = DBI.init(args.genetab, args.gene_format)
upstream_list = []
downstream_list = []
exons_list = []
introns_list = []
utr3_list = []
utr5_list = []
for g in gene:
upstream_list.append(g.upstream(args.upstream))
downstream_list.append(g.downstream(args.downstream))
for e in g.Exons():
exons_list.append(e)
for i in g.Introns():
introns_list.append(i)
if not (g.utr3() is None):
utr3_list.append(g.utr3())
if not (g.utr5() is None):
utr5_list.append(g.utr5())
upstream = DBI.init(upstream_list, "bed")
downstream = DBI.init(downstream_list, "bed")
exons = DBI.init(exons_list, "bed")
introns = DBI.init(introns_list, "bed")
utr3 = DBI.init(utr3_list, "genebed")
utr5 = DBI.init(utr5_list, "genebed")
if args.format == "guess":
args.format = Tools.guess_format(args.input)
for (i0, i) in enumerate(TableIO.parse(fin, args.format)):
if i0 == 0:
if isinstance(i, Bed12):
print >> out, "#chr\tstart\tend\tname\tscore\tstrand\tthick_start\tthick_end\titem_rgb\tblock_count\tblock_sizes\tblock_starts\tgene\tupstream\tdownstream\texon\tintron\tutr3\tutr5"
elif isinstance(i, GeneBed):
print >> out, "#name\tchr\tstrand\tstart\tend\tcds_start\texon_count\texon_starts\texont_ends\tgene\tupstream\tdownstream\texon\tintron\tutr3\tutr5"
else:
print >> out, "#chr\tstart\tend\tname\tscore\tstrand\tgene\tupstream\tdownstream\texon\tintron\tutr3\tutr5"
print >> out, i,
print >> out, "\t", toIDs(gene.query(i)),
print >> out, "\t", toIDs(upstream.query(i)),
print >> out, "\t", toIDs(downstream.query(i)),
print >> out, "\t", toIDs(exons.query(i)),
print >> out, "\t", toIDs(introns.query(i)),
print >> out, "\t", toIDs(utr3.query(i)),
print >> out, "\t", toIDs(utr5.query(i))
def Main():
'''
IO TEMPLATE
'''
global args,out
args=ParseArg()
if args.output=="stdout":
out=sys.stdout
else:
try:
out=open(args.output,"w")
except IOError:
print >>sys.stderr,"can't open file ",args.output,"to write. Using stdout instead"
out=sys.stdout
'''
END OF IO TEMPLATE
'''
print >>out,"# QUERY (VCF A):",args.VCF_A
print >>out,"# DATA (VCF B):",args.VCF_B
print >>out,"# A11 VCF in A and B, and alt nt is the same : A VCF entry"
print >>out,"# B11 VCF in A and B, and alt nt is the same : B VCF entry"
print >>out,"# A12 VCF position in A and B, and alt nt is not the same : A VCF entry"
print >>out,"# B12 VCF position in A and B, and alt nt is not the same : B VCF entry"
print >>out,"# A10 VCF, only exists in A"
print >>out,"# B01 VCF, only exists in B"
print >>sys.stderr,"Initialize data: reading ",args.VCF_A
VCF_A_DBI=DBI.init(args.VCF_A,"vcf")
print >>sys.stderr,"Initialize data: reading ",args.VCF_B
VCF_B_DBI=DBI.init(args.VCF_B,"vcf")
A11=0
A12=0
A10=0
B01=0
i0=0
print >>sys.stderr,"Query ",args.VCF_A
for (x,i) in enumerate(VCF_A_DBI):
if x%1000==0: print >>sys.stderr,x," entries\r",
flag=0
hit=None
for j in VCF_B_DBI.query(i):
if i==j:
hit=j
flag=1
continue
else:
hit=j
flag=2
if flag==1:
print >>out,"A11_%08d\t"%A11,i
print >>out,"B11_%08d\t"%A11,hit
print >>out,""
A11+=1
elif flag==2:
print >>out,"A12_%08d\t"%A12,i
print >>out,"B12_%08d\t"%A12,hit
print >>out,""
A12+=1
else:
print >>out,"A10_%08d\t"%A10,i
print >>out,""
print >>out,""
A10+=1
print >>sys.stderr,"Query ",args.VCF_B
for (x,i) in enumerate(VCF_B_DBI):
if x%1000==0: print >>sys.stderr,x," entries\r",
flag=0
for j in VCF_A_DBI.query(i):
flag=1
if flag==0:
print >>out,"B01_%08d\t"%B01,i
print >>out,""
print >>out,""
B01+=1
print >>out,"# [AB]11 number:",A11
print >>out,"# [AB]12 number:",A12
print >>out,"# A10 number:",A10
print >>out,"# B01 number:",B01
def Main():
global args,out
args=ParseArg()
if args.output=="stdout":
out=sys.stdout
else:
try:
out=open(args.output,"w")
except IOError:
print >>sys.stderr,"can't open file ",args.output,"to write. Using stdout instead"
out=sys.stdout
db_format=args.db_format
if len(db_format)==0:
db_format=["bed" for i in range(len(args.db))]
if len(db_format)==1:
db_format=[db_format[0] for i in range(len(args.db))]
if len(db_format)!=len(args.db):
print >>sys.stderr,"the number of annotation files is not same with the number of annotation formats"
print >>sys.stderr,"db format",db_format
print >>sys.stderr,"db ",args.db
exit(0)
print >>out,"# Input:",args.input
dbis=[]
hits=[] #count the hits
hcode={}
for i,f in enumerate(args.db):
print >>out,"# Features File No."+str(i+1),":",f
dbis.append(DBI.init(f,db_format[i]))
hits.append(0)
query_num=0
for bed in TableIO.parse(args.input,args.input_format):
if not args.m:
print >>out,"QR\t",bed
query_num+=1
code="@"
for i,dbi in enumerate(dbis):
flag=0
for hit in dbi.query(bed):
if not args.m:
print >>out,"\tDB"+str(i+1)+" HT\t",hit
flag=1
hits[i]+=flag
code+=str(flag)
if hcode.has_key(code):
hcode[code]+=1
else:
hcode[code]=1
if not args.m:
print >>out,"CD "+code,"\t",bed
print >>out,""
print >>out,""
else:
print >>out,bed,"\t","CD "+code
for i,x in enumerate(hits):
print >>out,"#",x,"/",query_num,"overlap with No."+str(i+1),args.db[i]
for key in sorted(hcode.keys()):
print >>out,"# code:"+key,"\t",hcode[key]
def Main():
"""
IO TEMPLATE
"""
global args, out
args = ParseArg()
if args.output == "stdout":
out = sys.stdout
else:
try:
out = open(args.output, "w")
except IOError:
print >>sys.stderr, "can't open file ", args.output, "to write. Using stdout instead"
out = sys.stdout
"""
END OF IO TEMPLATE
"""
print >> out, "# QUERY (VCF A):", args.VCF_A
print >> out, "# DATA (VCF B):", args.VCF_B
print >> out, "# A11 VCF in A and B, and alt nt is the same : A VCF entry"
print >> out, "# B11 VCF in A and B, and alt nt is the same : B VCF entry"
print >> out, "# A12 VCF position in A and B, and alt nt is not the same : A VCF entry"
print >> out, "# B12 VCF position in A and B, and alt nt is not the same : B VCF entry"
print >> out, "# A10 VCF, only exists in A"
print >> out, "# B01 VCF, only exists in B"
print >>sys.stderr, "Initialize data: reading ", args.VCF_A
VCF_A_DBI = DBI.init(args.VCF_A, "vcf")
print >>sys.stderr, "Initialize data: reading ", args.VCF_B
VCF_B_DBI = DBI.init(args.VCF_B, "vcf")
A11 = 0
A12 = 0
A10 = 0
B01 = 0
i0 = 0
print >>sys.stderr, "Query ", args.VCF_A
for (x, i) in enumerate(VCF_A_DBI):
if x % 1000 == 0:
print >>sys.stderr, x, " entries\r",
flag = 0
hit = None
for j in VCF_B_DBI.query(i):
if i == j:
hit = j
flag = 1
continue
else:
hit = j
flag = 2
if flag == 1:
print >> out, "A11_%08d\t" % A11, i
print >> out, "B11_%08d\t" % A11, hit
print >> out, ""
A11 += 1
elif flag == 2:
print >> out, "A12_%08d\t" % A12, i
print >> out, "B12_%08d\t" % A12, hit
print >> out, ""
A12 += 1
else:
print >> out, "A10_%08d\t" % A10, i
print >> out, ""
print >> out, ""
A10 += 1
print >>sys.stderr, "Query ", args.VCF_B
for (x, i) in enumerate(VCF_B_DBI):
if x % 1000 == 0:
print >>sys.stderr, x, " entries\r",
flag = 0
for j in VCF_A_DBI.query(i):
flag = 1
if flag == 0:
print >> out, "B01_%08d\t" % B01, i
print >> out, ""
print >> out, ""
B01 += 1
print >> out, "# [AB]11 number:", A11
print >> out, "# [AB]12 number:", A12
print >> out, "# A10 number:", A10
print >> out, "# B01 number:", B01
def Main():
'''
IO TEMPLATE
'''
global args,out
args=ParseArg()
if args.output=="stdout":
out=sys.stdout
else:
try:
out=open(args.output,"w")
except IOError:
print >>sys.stderr,"can't open file ",args.output,"to write. Using stdout instead"
out=sys.stdout
if args.input=="stdin":
fin=sys.stdin
else:
try:
x=args.input.split(".")
if x[-1]=="gz":
fin=gzip.open(args.input,"r")
else:
fin=open(args.input,"r")
except IOError:
print >>sys.stderr,"can't read file",args.input
fin=sys.stdin
'''
END OF IO TEMPLATE
'''
print >>out,"# This data was generated by program ",sys.argv[0]," (version: %s)"%VERSION,
print >>out,"in bam2x ( https://github.com/nimezhu/bam2x )"
print >>out,"# Date: ",time.asctime()
print >>out,"# The command line is :"
print >>out,"#\t"," ".join(sys.argv)
gene=DBI.init(args.genetab,args.gene_format);
upstream_list=[]
downstream_list=[]
exons_list=[]
introns_list=[]
utr3_list=[]
utr5_list=[]
for g in gene:
upstream_list.append(g.upstream(args.upstream));
downstream_list.append(g.downstream(args.downstream));
for e in g.Exons():
exons_list.append(e)
for i in g.Introns():
introns_list.append(i)
if not (g.utr3() is None):
utr3_list.append(g.utr3())
if not (g.utr5() is None):
utr5_list.append(g.utr5())
upstream=DBI.init(upstream_list,"bed")
downstream=DBI.init(downstream_list,"bed")
exons=DBI.init(exons_list,"bed")
introns=DBI.init(introns_list,"bed")
utr3=DBI.init(utr3_list,"genebed")
utr5=DBI.init(utr5_list,"genebed")
if args.format=="guess":
args.format=Tools.guess_format(args.input)
for (i0,i) in enumerate(TableIO.parse(fin,args.format)):
if i0==0:
if isinstance(i,Bed12):
print >>out,"#chr\tstart\tend\tname\tscore\tstrand\tthick_start\tthick_end\titem_rgb\tblock_count\tblock_sizes\tblock_starts\tgene\tupstream\tdownstream\texon\tintron\tutr3\tutr5"
elif isinstance(i,GeneBed):
print >>out,"#name\tchr\tstrand\tstart\tend\tcds_start\texon_count\texon_starts\texont_ends\tgene\tupstream\tdownstream\texon\tintron\tutr3\tutr5"
else:
print >>out,"#chr\tstart\tend\tname\tscore\tstrand\tgene\tupstream\tdownstream\texon\tintron\tutr3\tutr5"
print >>out,i,
print >>out,"\t",toIDs(gene.query(i)),
print >>out,"\t",toIDs(upstream.query(i)),
print >>out,"\t",toIDs(downstream.query(i)),
print >>out,"\t",toIDs(exons.query(i)),
print >>out,"\t",toIDs(introns.query(i)),
print >>out,"\t",toIDs(utr3.query(i)),
print >>out,"\t",toIDs(utr5.query(i))
def Main():
'''
IO TEMPLATE
'''
global args,out
args=ParseArg()
fin=IO.fopen(args.input,"r")
out=IO.fopen(args.output,"w")
'''
END OF IO TEMPLATE
'''
print >>out,"# This data was generated by program ",sys.argv[0]," (version: %s)"%VERSION,
print >>out,"in bam2x ( https://github.com/nimezhu/bam2x )"
print >>out,"# Date: ",time.asctime()
print >>out,"# The command line is :"
print >>out,"#\t"," ".join(sys.argv)
hSites={};
donorSites={};
acceptorSites={}
if args.genome is not None:
genome=DBI.init(args.genome,"genome")
else:
genome=None
j=0
for j,i in enumerate(TableIO.parse(fin,"bam2bed12",references=fin.references,strand=args.strand)):
#print >>out,i
if j%1000==0: print >>sys.stderr,"processing ",j,"reads \r",
for intron in i.Introns():
if len(intron)< args.intron_min_length: continue
donor=intron.head();
#print >>sys.stderr,intron
#print >>sys.stderr,donor
donorID=bedToID(donor)
if(donorSites.has_key(donorID)):
donorSites[donorID]+=1
else:
donorSites[donorID]=1
acceptor=intron.tail();
acceptorID=bedToID(acceptor)
if(acceptorSites.has_key(acceptorID)):
acceptorSites[acceptorID]+=1
else:
acceptorSites[acceptorID]=1
'''
if genome is not None:
s=genome.query(intron.head()).upper()+".."+genome.query(intron.tail()).upper()
if hSites.has_key(s):
hSites[s]+=1
else:
hSites[s]=1
'''
donors=[]
for key in donorSites.keys():
a=key.split("\t")
donors.append(Bed([a[0],a[1],a[2],"noname_donor",donorSites[key],a[3]]));
donors.sort()
for i,x in enumerate(donors):
x.id="donor_"+str(i)
print >>out,x,"\t",genome.query(x).upper()
acceptors=[]
for key in acceptorSites.keys():
a=key.split("\t")
acceptors.append(Bed([a[0],a[1],a[2],"noname_acceptor",acceptorSites[key],a[3]]));
acceptors.sort()
for i,x in enumerate(acceptors):
x.id="acceptor_"+str(i)
print >>out,x,"\t",genome.query(x).upper()
def Main():
args=ParseArg()
#store bed files with indexing and count information:
bam={}
print >>sys.stderr,"Starting index bam/bed files:"
for i in range(len(args.bams)):
temp_name=args.name[i]
print >>sys.stderr," #Indexing for bam/bed file of",temp_name,"\r",
bam[temp_name]=DBI.init(args.bams[i],args.fmt)
print >>sys.stderr
print >>sys.stderr,"Reading nucleosome peak xls file from Danpos."
nucleosomes=TableIO.parse(args.nucleosome,'metabed',header=True)
print >>sys.stderr,"Initial output files..."
out=open(args.output,"w")
# -- for verbose ---
if args.verbose:
out_mark=[]
for n in args.name:
out_mark.append(open(n+'_shift_nucleosomes.bed','w'))
# ------------------
line_head=open(args.nucleosome,'r').readline().strip()
line_head=line_head+"\t"+"\t".join(str(f) for f in args.name)+'\t'+"\t".join(str(f)+'_off' for f in args.name)
print >>out,line_head
print >>sys.stderr,"Start Counting..."
num=0
t0 = time()
for i in nucleosomes:
chrom=i.chr
if i.smt_pval>0.01 or i.fuzziness_pval>0.01: continue # only choose nucleosomes with high value and low fuzziness
if "random" in chrom or chrom == 'chrM':
continue
num=num+1
center=int(i.start+i.end)/2
count=np.zeros(len(args.bams),dtype="float")
offset=np.zeros(len(args.bams),dtype='int')
line=str(i)
for k,name in enumerate(args.name):
if args.fmt=='bam':
query=bam[name].query(Bed([chrom,center-ma-(half_len-75)-rangeS,center+ma+(half_len-75)+rangeS]),method='fetch')
else:
query=bam[name].query(Bed([chrom,center-ma-(half_len-75)-rangeS,center+ma+(half_len-75)+rangeS]))
read_centers=[]
for j in query:
read_centers.append(find_center(j,args.fmt))
[o,c]=getCount(read_centers,center)
count[k]=c
offset[k]=o
# -- for verbose ---
if args.verbose:
print >>out_mark[k],chrom+'\t%d\t%d'%(i.start+o,i.end+o)
# ------------------
line = line + "\t" + "\t".join(str(f) for f in count) + '\t' + "\t".join(str(f) for f in offset)
if num%20000==0:
t1 = time()
print >>sys.stderr,"processing %dth nucleosome..., time: %.2fs."%(num,t1-t0),'\r',
t0 = time()
print >>out,line
print
out.close()
# -- for verbose ---
if args.verbose:
for k in out_mark:
k.close()
def Main():
global args,out
args=ParseArg()
dict={}
if args.output=="stdout":
out=sys.stdout
else:
try:
out=open(args.output,"w")
except IOError:
print >>sys.stderr,"can't open file ",args.output,"to write. Using stdout instead"
out=sys.stdout
argv=sys.argv
argv[0]=argv[0].split("/")[-1]
print >>out,"# This data was generated by program ",argv[0],"(version %s)"%VERSION,
print >>out,"in bam2x ( https://github.com/nimezhu/bam2x )"
print >>out,"# Date: ",time.asctime()
print >>out,"# The command line is :\n#\t"," ".join(argv)
init_dict={}
if args.dbformat=="guess":
if Tools.suffix(args.db)=="gz":
args.dbformat="tabix"
args.tabix_format=Tools.guess_format(args.db)
else:
args.dbformat=Tools.guess_format(args.db)
if args.query_method:
dict["method"]=args.query_method
if args.tabix_format:
init_dict["tabix"]=args.tabix_format
dbi=DBI.init(args.db,args.dbformat,**init_dict)
hits=0
query=0
if args.input=="stdin":
input=sys.stdin
else:
input=args.input
query_length=0
hits_number=0
if (args.input_format=="guess"):
args.input_format=Tools.guess_format(args.input)
for (i0,x) in enumerate(TableIO.parse(input,args.input_format)):
if i0%100==0:
print >>sys.stderr,"query ",i0," entries\r",
print >>out,"QR\t",x
hit=0
query+=1
query_length+=len(x)
#print dbi;#debug
results=dbi.query(x,**dict)
#results=dbi.query(x) #DEBUG
#print >>sys.stderr,type(results)
if isinstance(results,numpy.ndarray) or isinstance(results,list):
print >>out,"HT\t",
for value in results:
print >>out,str(value)+",",
print >>out,""
hit=1
hits_number+=1
elif isinstance(results,str):
print >>out,"HT\t",
print >>out,results
hit=1
hits_number+=1
else:
for j in results:
print >>out,"HT\t",j
hit=1
hits_number+=1
if args.dbformat=="tabix":
x.chr=x.chr.replace("chr","")
for j in dbi.query(x,**dict):
print >>out,"HT\t",j
hit=1
hits_number+=1
hits+=hit
print >>out,"# Query Number:",query,"\n# Query Have Hits:",hits
print >>out,"# Query Length:",query_length
print >>out,"# Hits Number:",hits_number
def Main():
'''
IO TEMPLATE
'''
global args,out
args=ParseArg()
if args.output=="stdout":
out=sys.stdout
else:
try:
out=open(args.output,"w")
except IOError:
print >>sys.stderr,"can't open file ",args.output,"to write. Using stdout instead"
out=sys.stdout
if args.input=="stdin":
fin=sys.stdin
else:
try:
x=args.input.split(".")
if x[-1]=="gz":
fin=gzip.open(args.input,"r")
else:
fin=open(args.input,"r")
except IOError:
print >>sys.stderr,"can't read file",args.input
fin=sys.stdin
'''
END OF IO TEMPLATE
'''
print >>out,"# This data was generated by program ",sys.argv[0]," (version: %s)"%VERSION,
print >>out,"in bam2x ( https://github.com/nimezhu/bam2x )"
print >>out,"# Date: ",time.asctime()
print >>out,"# The command line is :"
print >>out,"#\t"," ".join(sys.argv)
gene=DBI.init(args.genetab,args.gene_format);
upstream_list=[]
downstream_list=[]
exons_list=[]
introns_list=[]
utr3_list=[]
utr5_list=[]
for g in gene:
upstream_list.append(g.upstream(args.upstream));
downstream_list.append(g.downstream(args.downstream));
for e in g.Exons():
exons_list.append(e)
for i in g.Introns():
introns_list.append(i)
if not (g.utr3() is None):
utr3_list.append(g.utr3())
if not (g.utr5() is None):
utr5_list.append(g.utr5())
upstream=DBI.init(upstream_list,"bed")
downstream=DBI.init(downstream_list,"bed")
exons=DBI.init(exons_list,"bed")
introns=DBI.init(introns_list,"bed")
utr3=DBI.init(utr3_list,"genebed")
utr5=DBI.init(utr5_list,"genebed")
print >>out,"#chr\tstart\tend\tname\tscore\tstrand\tgene\tupstream\tdownstream\texon\tintron\tutr3\tutr5"
for i in TableIO.parse(fin,args.format):
print >>out,i,
print >>out,"\t",toIDs(gene.query(i)),
print >>out,"\t",toIDs(upstream.query(i)),
print >>out,"\t",toIDs(downstream.query(i)),
print >>out,"\t",toIDs(exons.query(i)),
print >>out,"\t",toIDs(introns.query(i)),
print >>out,"\t",toIDs(utr3.query(i)),
print >>out,"\t",toIDs(utr5.query(i))
def Main():
t1 = time()
global min_interaction, p_value
args = ParseArg()
inp = open(args.input, 'r')
min_clusterS = args.min_clusterS
min_interaction = args.min_interaction
p_value = args.p_value
output = open(args.output, 'w')
ncpus = args.parallel
#store genomic location of part1 and part2
part1 = []
part2 = []
k = 0
print >> sys.stderr, "# Inputing data..."
chr_list = []
for line in inp.read().split('\n'):
if line == '': continue
line = line.strip().split('\t')
p1 = annotated_bed(line[0:10], id=k)
p2 = annotated_bed(line[11:], id=k)
if isinstance(p1.start, list):
p1.start = int(p1.start[0])
p1.end = int(p1.end[-1])
if isinstance(p2.start, list):
p2.start = int(p2.start[0])
p2.end = int(p2.end[-1])
if SingleFragment(p1, p2): continue
k += 1
part1.append(p1)
part2.append(p2)
if p1.chr not in chr_list: chr_list.append(p1.chr)
if p2.chr not in chr_list: chr_list.append(p2.chr)
if k % 20000 == 0:
print >> sys.stderr, " Reading %d pairs of segments\r" % (k),
print >> sys.stderr, "Get total %d pairs." % (k)
if len(part1) != len(part2):
print >> sys.stderr, "## ERROR: number of regions in two part not match!!"
sys.exit(0)
# sort in genomic order, easy for clustering
part1 = sorted(part1, key=attrgetter('start'))
part1 = sorted(part1, key=attrgetter('chr'))
part2 = sorted(part2, key=attrgetter('start'))
part2 = sorted(part2, key=attrgetter('chr'))
# for parallel computing
print >> sys.stderr, "# Generating clusters for two parts..."
# tuple of all parallel python servers to connect with
ppservers = ()
job_server = pp.Server(ncpus, ppservers=ppservers)
jobs1 = []
jobs2 = []
for chro in chr_list:
part1_temp = filter(lambda p: p.chr == chro, part1)
if len(part1_temp) > 0:
jobs1.append(
job_server.submit(cluster_regions, (part1_temp, min_clusterS),
(annotated_bed, ), (
"UnionFind",
"copy",
)))
part2_temp = filter(lambda p: p.chr == chro, part2)
if len(part2_temp) > 0:
jobs2.append(
job_server.submit(cluster_regions, (part2_temp, min_clusterS),
(annotated_bed, ), (
"UnionFind",
"copy",
)))
cluster_pool1 = {}
part1 = []
for job in jobs1:
try:
part1 = part1 + job()[1]
cluster_pool1.update(job()[0])
except:
print >> sys.stderr, "Wrong in %s, part1" % (job()[2])
continue
cluster_pool2 = {}
part2 = []
for job in jobs2:
try:
part2 = part2 + job()[1]
cluster_pool2.update(job()[0])
except:
continue
print >> sys.stderr, " cluster number for part1 is %d " % (
len(cluster_pool1))
print >> sys.stderr, " cluster number for part2 is %d " % (
len(cluster_pool2))
# sort back to pair two parts
part1 = sorted(part1, key=attrgetter('id'))
part2 = sorted(part2, key=attrgetter('id'))
print >> sys.stderr, "size of part1&2:", len(part1), len(part2)
c_interaction = {}
for i in range(len(part1)):
region1 = str(part1[i])
region2 = str(part2[i])
try:
inter = part1[i].cluster + "--" + part2[i].cluster
except:
print >> sys.stderr, i, part1[i].cluster, part2[i].cluster
sys.exit()
if c_interaction.has_key(inter):
c_interaction[inter] += 1
else:
c_interaction[inter] = 1
# annotation file
print >> sys.stderr, "# Indexing annotation files"
dbi_all = DBI.init(args.annotation, "bed")
dbi_detail = DBI.init(args.db_detail, "bed")
dbi_repeat = DBI.init(
"/home/yu68/bharat-interaction/new_lincRNA_data/mouse.repeat.txt",
"bed")
print >> sys.stderr, "# finding strong interactions from clusters..."
k = 0 # record for strong interactions
n = 0
# annotation file
for interaction in c_interaction:
n = n + 1
count = c_interaction[interaction]
if count < min_interaction: continue
i = interaction.split("--")[0]
j = interaction.split("--")[1]
try: # we select clusters with size no less than 5, so some interactions cannot be found in clusters
count1 = cluster_pool1[i].cluster
count2 = cluster_pool2[j].cluster
except:
continue
real_p = 1 - hypergeom.cdf(count, len(part1), count1, count2)
if real_p <= p_value:
k = k + 1
cluster_pool1[i].Annotate(dbi_all, dbi_detail, dbi_repeat)
cluster_pool2[j].Annotate(dbi_all, dbi_detail, dbi_repeat)
try:
log_p = math.log(real_p)
except:
log_p = -float("Inf")
print >> output, str(cluster_pool1[i]) + '\t' + str(
cluster_pool2[j]) + '\t%d\t%.4f' % (count, log_p)
if n % 1000 == 0:
print >> sys.stderr, " Progress ( %d / %d )\r" % (
n, len(c_interaction)),
print >> sys.stderr, "# Find %d strong interactions. Cost time: %.2f s" % (
k, time() - t1)
if args.FDR:
print >> sys.stderr, "# Permutated results:"
for i in range(10):
shuffle(part2)
[n_r_I,
n_r_SI] = Random_strongInteraction(part1, part2, cluster_pool1,
cluster_pool2)
print >> sys.stderr, " ", i, n_r_I, n_r_SI, n_r_SI * 1.0 / n_r_I
def Main():
args=ParseArg()
pair_dist=args.pair_dist
step=args.step
print "\nChecking if linkedPair file is tabixed..."
if not os.path.isfile(args.linkedPair):
print "LinkedPair file is not exist, please check!!"
sys.exit(0)
if not os.path.isfile(args.linkedPair+".tbi"):
print " tabix-ing..."
os.system("sort -k1,1 -k2,2n "+args.linkedPair+" > temp_linkedPair.txt")
os.system("bgzip temp_linkedPair.txt")
os.system("tabix -p bed temp_linkedPair.txt.gz")
linkedPair='temp_linkedPair.txt.gz'
else:
linkedPair=args.linkedPair
print " linkedPair file is tabixed."
print "\nTabixing the interaction file..."
os.system("sort -k1,1 -k2,2n "+args.interaction+" > temp_interaction.txt")
os.system("bgzip temp_interaction.txt")
os.system("tabix -p bed temp_interaction.txt.gz")
print " interaction file is tabixed."
# start column number for second regions
# s1 for interaction file and s2 for linkedPair file
(s1,s2)=args.start
print "\nGet region information."
if args.r:
Region = read_region(args.r)
elif args.name:
os.system('grep "%s" %s > temp2.txt'%(args.name,args.genebed))
g = open("temp2.txt").read().split('\t')
if len(g)<2:
print >> sys.stderr, "Error: the gene name is not found in database"
sys.exit(0)
s = int(g[1])
e = int(g[2])
Region = Bed([g[0],s-(e-s)/10,e+(e-s)/10,"region",".","."])
else:
print >> sys.stderr, "Error: Need to specify the region by '-r' or specify the gene name by '-n'"
sys.exit(0)
print "\n Start plot heatmaps on region: "+Region.str_region()
fig = plt.figure(figsize=(8,6))
ax = plt.subplot(111,frameon=False,yticks=[])
start = Region.start
end = Region.stop
ax.set_xlim(start,end)
#set x ticks withour offset
locs=ax.get_xticks()
ax.set_xticklabels(map(lambda x: "%i"%x, locs),fontsize=6)
print "\nStart draw gene track"
gene_dbi=DBI.init(args.genebed,"bed")
print " genebed indexed!"
print " Plot gene track"
gene_top=Genetrack(Region,gene_dbi,ax,0.08)
h = 1.5*step/(end-start) # unit height for triangles or polycons in heatmap
print "\nQuery linkedPairs within specified region"
os.system("tabix "+linkedPair+" %s:%i-%i > temp2.txt"%(Region.chr,Region.start,Region.stop))
Count = {}
for b in read_interaction("temp2.txt",s2):
col='k'
if args.Slim and SingleFragment(b[0],b[1],pair_dist): continue
if Region.overlap(b[0],0) and Region.overlap(b[1],0):
if b[0].strand=='-':
i = b[0].start
else:
i = b[0].stop
if b[1].strand=='-':
j = b[1].start
else:
j = b[1].stop
i = (i/step+1) * step # approximate to the nearest central point
j = (j/step+1) * step
if i > j:
temp=j
j=i
i=temp
if (i,j) not in Count:
Count[(i,j)] = 1
else:
Count[(i,j)] +=1
print Count
patches = []
colors = []
for i in range(start,end+1):
if i%step!=0: continue
for j in range(i,end+1):
if j%step!=0 or (i,j) not in Count: continue
patches.append(PatchGen(i,j,h,step,gene_top+0.01))
colors.append(np.log(Count[(i,j)]+1))
p = PatchCollection(patches, cmap=matplotlib.cm.Reds, alpha=0.7, edgecolor='k',linewidths=0.1)
p.set_array(np.array(colors))
ax.add_collection(p)
ax.set_ylim(0,((end-start)/step+2)*h+gene_top+0.01)
plt.colorbar(p)
if not args.SI:
plt.savefig(args.output)
plt.show()
os.system("rm temp_interaction.txt.gz*")
if not os.path.isfile(args.linkedPair+".tbi"):
os.system("rm temp_linkedPair.txt.gz*")
os.system("rm temp2.txt")
sys.exit(0)
print "\nQuery interactions"
os.system("tabix temp_interaction.txt.gz %s:%i-%i > temp2.txt"%(Region.chr,Region.start,Region.stop))
print "\nList of interactions plotted: "
k=1
cmap=cm.get_cmap('Paired', 10)
cmap=cmap(range(10))
bottom = gene_top+0.01
for b in read_interaction("temp2.txt",s1):
if b[0].overlap(b[1],0): continue
if Region.overlap(b[1],0):
k+=1
if b[1].stop > b[0].stop:
start1 = b[0].start
end1 = b[0].stop
start2 = b[1].start
end2 = b[1].stop
else:
start1 = b[1].start
end1 = b[1].stop
start2 = b[0].start
end2 = b[0].stop
P1=Polygon([[start1,bottom],[end1,bottom],[(end1+end2)*0.5,(end2-end1)*h/step+bottom],[(start1+end2)*0.5,(end2-start1)*h/step+bottom]],"True",facecolor='none',edgecolor=cmap[k%10],alpha=0.4,lw=0.5)
P2=Polygon([[start2,bottom],[end2,bottom],[(start1+end2)*0.5,(end2-start1)*h/step+bottom],[(start1+start2)*0.5,(start2-start1)*h/step+bottom]],"True",facecolor='none',edgecolor=cmap[k%10],alpha=0.4,lw=0.5)
ax.add_patch(P1)
ax.add_patch(P2)
print " "+b[0].str_region()+" <-> "+b[1].str_region()
plt.savefig(args.output)
plt.show()
# remove temp file
os.system("rm temp_interaction.txt.gz*")
if not os.path.isfile(args.linkedPair+".tbi"):
os.system("rm temp_linkedPair.txt.gz*")
os.system("rm temp2.txt")
def Main():
t1 = time()
global min_interaction, p_value
args = ParseArg()
inp = open(args.input, 'r')
min_clusterS = args.min_clusterS
min_interaction = args.min_interaction
p_value = args.p_value
output = open(args.output, 'w')
ncpus = args.parallel
#store genomic location of part1 and part2
part = []
k = 0
print >> sys.stderr, "# Inputing data..."
chr_list = []
for line in inp.read().split('\n'):
if line == '': continue
line = line.strip().split('\t')
p1 = annotated_bed(line[0:8], id=k, part=1)
p2 = annotated_bed(line[9:], id=k, part=2)
if SingleFragment(p1, p2): continue
k += 1
part.append(p1)
part.append(p2)
if p1.chr not in chr_list: chr_list.append(p1.chr)
if p2.chr not in chr_list: chr_list.append(p2.chr)
if k % 20000 == 0:
print >> sys.stderr, " Reading %d pairs of segments\r" % (k),
print >> sys.stderr, "Get total %d pairs." % (k)
# sort in genomic order, easy for clustering
part = sorted(part, key=attrgetter('start'))
part = sorted(part, key=attrgetter('chr'))
# for parallel computing
print >> sys.stderr, "# Generating clusters for two parts..."
# tuple of all parallel python servers to connect with
ppservers = ()
job_server = pp.Server(ncpus, ppservers=ppservers)
jobs = []
for chro in chr_list:
part_temp = filter(lambda p: p.chr == chro, part)
if len(part_temp) > 0:
jobs.append(
job_server.submit(cluster_regions, (part_temp, min_clusterS),
(annotated_bed, ), (
"UnionFind",
"copy",
)))
cluster_pool = {}
part = []
for job in jobs:
try:
part = part + job()[1]
cluster_pool.update(job()[0])
except:
print >> sys.stderr, "Wrong in %s, part1" % (job()[2])
continue
print >> sys.stderr, " cluster number is %d " % (
len(cluster_pool))
# sort back to pair two parts
part = sorted(part, key=attrgetter('part'))
part = sorted(part, key=attrgetter('id'))
print >> sys.stderr, "size of part", len(part)
c_interaction = {}
i = 0
while i < len(part):
P1 = part[i]
P2 = part[i + 1]
assert P1.id == P2.id
i += 2
print >> sys.stderr, "%d\r" % (i),
if P1.cluster == P2.cluster: continue
if P1.cluster < P2.cluster:
inter = P1.cluster + "--" + P2.cluster
else:
inter = P2.cluster + "--" + P1.cluster
if c_interaction.has_key(inter):
c_interaction[inter] += 1
else:
c_interaction[inter] = 1
# annotation file
print >> sys.stderr, "# Indexing annotation files"
dbi_all = DBI.init(args.annotation, "bed")
dbi_detail = DBI.init(args.db_detail, "bed")
dbi_repeat = DBI.init(
"/home/yu68/bharat-interaction/new_lincRNA_data/mouse.repeat.txt",
"bed")
print >> sys.stderr, "# finding strong interactions from clusters..."
k = 0 # record for strong interactions
n = 0
# annotation file
for interaction in c_interaction:
n = n + 1
count = c_interaction[interaction]
if count < min_interaction: continue
i = interaction.split("--")[0]
j = interaction.split("--")[1]
try: # we select clusters with size no less than 5, so some interactions cannot be found in clusters
count1 = cluster_pool[i].cluster
count2 = cluster_pool[j].cluster
except:
continue
real_p = 1 - hypergeom.cdf(count, len(part) / 2, count1, count2)
if real_p <= p_value:
k = k + 1
cluster_pool[i].Annotate(dbi_all, dbi_detail, dbi_repeat)
cluster_pool[j].Annotate(dbi_all, dbi_detail, dbi_repeat)
try:
log_p = math.log(real_p)
except:
log_p = -float("Inf")
print >> output, str(cluster_pool[i]) + '\t' + str(
cluster_pool[j]) + '\t%d\t%.4f' % (count, log_p)
if n % 1000 == 0:
print >> sys.stderr, " Progress ( %d / %d )\r" % (
n, len(c_interaction)),
print >> sys.stderr, "# Find %d strong interactions. Cost time: %.2f s" % (
k, time() - t1)
def Main():
args = ParseArg()
pair_dist = args.pair_dist
step = args.step
print "\nChecking if linkedPair file is tabixed..."
if not os.path.isfile(args.linkedPair):
print "LinkedPair file is not exist, please check!!"
sys.exit(0)
if not os.path.isfile(args.linkedPair + ".tbi"):
print " tabix-ing..."
os.system("sort -k1,1 -k2,2n " + args.linkedPair +
" > temp_linkedPair.txt")
os.system("bgzip temp_linkedPair.txt")
os.system("tabix -p bed temp_linkedPair.txt.gz")
linkedPair = 'temp_linkedPair.txt.gz'
else:
linkedPair = args.linkedPair
print " linkedPair file is tabixed."
print "\nTabixing the interaction file..."
os.system("sort -k1,1 -k2,2n " + args.interaction +
" > temp_interaction.txt")
os.system("bgzip temp_interaction.txt")
os.system("tabix -p bed temp_interaction.txt.gz")
print " interaction file is tabixed."
# start column number for second regions
# s1 for interaction file and s2 for linkedPair file
(s1, s2) = args.start
print "\nGet region information."
if args.r:
Region = read_region(args.r)
elif args.name:
os.system('grep "%s" %s > temp2.txt' % (args.name, args.genebed))
g = open("temp2.txt").read().split('\t')
if len(g) < 2:
print >> sys.stderr, "Error: the gene name is not found in database"
sys.exit(0)
s = int(g[1])
e = int(g[2])
Region = Bed(
[g[0], s - (e - s) / 10, e + (e - s) / 10, "region", ".", "."])
else:
print >> sys.stderr, "Error: Need to specify the region by '-r' or specify the gene name by '-n'"
sys.exit(0)
print "\n Start plot heatmaps on region: " + Region.str_region()
fig = plt.figure(figsize=(8, 6))
ax = plt.subplot(111, frameon=False, yticks=[])
start = Region.start
end = Region.stop
ax.set_xlim(start, end)
#set x ticks withour offset
locs = ax.get_xticks()
ax.set_xticklabels(map(lambda x: "%i" % x, locs), fontsize=6)
print "\nStart draw gene track"
gene_dbi = DBI.init(args.genebed, "bed")
print " genebed indexed!"
print " Plot gene track"
gene_top = Genetrack(Region, gene_dbi, ax, 0.08)
h = 1.5 * step / (end - start
) # unit height for triangles or polycons in heatmap
print "\nQuery linkedPairs within specified region"
os.system("tabix " + linkedPair + " %s:%i-%i > temp2.txt" %
(Region.chr, Region.start, Region.stop))
Count = {}
for b in read_interaction("temp2.txt", s2):
col = 'k'
if args.Slim and SingleFragment(b[0], b[1], pair_dist): continue
if Region.overlap(b[0], 0) and Region.overlap(b[1], 0):
if b[0].strand == '-':
i = b[0].start
else:
i = b[0].stop
if b[1].strand == '-':
j = b[1].start
else:
j = b[1].stop
i = (i / step +
1) * step # approximate to the nearest central point
j = (j / step + 1) * step
if i > j:
temp = j
j = i
i = temp
if (i, j) not in Count:
Count[(i, j)] = 1
else:
Count[(i, j)] += 1
print Count
patches = []
colors = []
for i in range(start, end + 1):
if i % step != 0: continue
for j in range(i, end + 1):
if j % step != 0 or (i, j) not in Count: continue
patches.append(PatchGen(i, j, h, step, gene_top + 0.01))
colors.append(np.log(Count[(i, j)] + 1))
p = PatchCollection(patches,
cmap=matplotlib.cm.Reds,
alpha=0.7,
edgecolor='k',
linewidths=0.1)
p.set_array(np.array(colors))
ax.add_collection(p)
ax.set_ylim(0, ((end - start) / step + 2) * h + gene_top + 0.01)
plt.colorbar(p)
if not args.SI:
plt.savefig(args.output)
plt.show()
os.system("rm temp_interaction.txt.gz*")
if not os.path.isfile(args.linkedPair + ".tbi"):
os.system("rm temp_linkedPair.txt.gz*")
os.system("rm temp2.txt")
sys.exit(0)
print "\nQuery interactions"
os.system("tabix temp_interaction.txt.gz %s:%i-%i > temp2.txt" %
(Region.chr, Region.start, Region.stop))
print "\nList of interactions plotted: "
k = 1
cmap = cm.get_cmap('Paired', 10)
cmap = cmap(range(10))
bottom = gene_top + 0.01
for b in read_interaction("temp2.txt", s1):
if b[0].overlap(b[1], 0): continue
if Region.overlap(b[1], 0):
k += 1
if b[1].stop > b[0].stop:
start1 = b[0].start
end1 = b[0].stop
start2 = b[1].start
end2 = b[1].stop
else:
start1 = b[1].start
end1 = b[1].stop
start2 = b[0].start
end2 = b[0].stop
P1 = Polygon([[start1, bottom], [end1, bottom],
[(end1 + end2) * 0.5,
(end2 - end1) * h / step + bottom],
[(start1 + end2) * 0.5,
(end2 - start1) * h / step + bottom]],
"True",
facecolor='none',
edgecolor=cmap[k % 10],
alpha=0.4,
lw=0.5)
P2 = Polygon([[start2, bottom], [end2, bottom],
[(start1 + end2) * 0.5,
(end2 - start1) * h / step + bottom],
[(start1 + start2) * 0.5,
(start2 - start1) * h / step + bottom]],
"True",
facecolor='none',
edgecolor=cmap[k % 10],
alpha=0.4,
lw=0.5)
ax.add_patch(P1)
ax.add_patch(P2)
print " " + b[0].str_region() + " <-> " + b[1].str_region()
plt.savefig(args.output)
plt.show()
# remove temp file
os.system("rm temp_interaction.txt.gz*")
if not os.path.isfile(args.linkedPair + ".tbi"):
os.system("rm temp_linkedPair.txt.gz*")
os.system("rm temp2.txt")