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12g.py
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12g.py
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### shorting position on chromosome and writng to a new file all inormation we need
### Uses igv files as input
import time,numpy
import sys, os
#sys.setrecursionlimit(5000)
work_dir=os.getcwd()
lib_path = os.path.abspath(os.getcwd())
script_dir=os.getcwd()+'/'+'scripts'
sys.path.append(lib_path)
from configuration_12 import genotype
genotype=list(genotype)
def find_cluster(abud_cutoff,fi,fo,gap,mur):
f = open(fi,'r')
out = open(fo,'w')
out.write(str("Chrom"))
out.write("\t")
out.write(str("ChromStart"))
out.write("\t")
out.write(str("ChromEnd"))
out.write("\t")
out.write(str("Name"))
out.write("\t")
out.write(str("Abundance"))
out.write("\n")
out.close()
### count different size sRNA
size = {}
i= -1
sRNA = {}
previous = -10000
s = 0
abundance = 0
cluster = {}
cluster_sRNA = {}
in_cluster = False
## reading lines
for line in f.readlines():
i += 1
line = line.strip()
token = line.split('\t')
try:
genome_position = float(token[1])
except:
continue
sRNA[i] = token[3]
chro = token[0]
ab = 0
for j in range(4,4+len(genotype)):
ab += float(token[j])
if(i >=1):
#prfloat(genome_position,previous)
if((float(genome_position) - float(previous)) <= gap):
if(in_cluster == False):
start = previous
name = nam
cluster_sRNA[0] = 1
abundance = abund
in_cluster = True
token=sRNA[i].split('_')
abundance += ab
#prfloat(abundance,token[3],sRNA[position])
cluster_sRNA[0] += 1
name += ','
name += sRNA[i]
if((float(genome_position) - (float(previous)) > gap)&(in_cluster==True)):
name = str(cluster_sRNA[0])+','+name
in_cluster = False
if(((cluster_sRNA[0])>=mur)&( abundance >=abud_cutoff)):
end = previous+25
out = open(fo,'a')
out.write(str(chro))
out.write('\t')
out.write(str(int(start)))
out.write('\t')
out.write(str(int(end)))
out.write('\t')
out.write(str(name))
out.write('\t')
out.write(str(int(abundance)))
out.write('\n')
out.close()
names = name.split(',')
for t in range(1,len(names)-1):
if len(names[t]) in size:
size[len(names[t])] += 1
else:
size[len(names[t])] = 0
#prfloat(chro,start,end,name,abundance)
s += 1
previous = genome_position
nam = sRNA[i]
token=sRNA[i].split('_')
abund = ab
print "abundance cut-off: "+str(abud_cutoff)
print "max gap length: "+str(gap)
print "min number fo unique reads: "+str(mur)
print "number of clusters: "+str(s)
print "size fractionated read counts in clusters:",size
def find_cluster_size(abud_cutoff,fi,fo,seq_size,gap,mur):
f = open(fi,'r')
out = open(str(fo)+'_'+str(seq_size)+".txt",'w')
out.write(str("Chrom"))
out.write("\t")
out.write(str("ChromStart"))
out.write("\t")
out.write(str("ChromEnd"))
out.write("\t")
out.write(str("Name"))
out.write("\t")
out.write(str("Abundance"))
out.write("\n")
out.close()
### count different size sRNA
size = {}
i= 0
sRNA = {}
previous = -10000
s = 0
abundance = 0
cluster = {}
cluster_sRNA = {}
in_cluster = False
## reading lines
for line in f.readlines():
line = line.strip()
token = line.split('\t')
try:
genome_position = float(token[1])
except:
continue
if(len(token[3])==int(seq_size)): ###only read with specific size
sRNA[i] = token[3]
chro = token[0]
ab = 0
for j in range(4,4+len(genotype)):
ab += float(token[j])
if(i >=1):
#prfloat(genome_position,previous)
if((float(genome_position) - float(previous)) <= gap):
if(in_cluster == False):
start = previous
name = nam
cluster_sRNA[0] = 1
abundance = abund
in_cluster = True
token=sRNA[i].split('_')
abundance += ab
#prfloat(abundance,token[3],sRNA[position])
cluster_sRNA[0] += 1
name += ','
name += sRNA[i]
if((float(genome_position) - (float(previous)) > gap)&(in_cluster==True)):
name = str(cluster_sRNA[0])+','+name
in_cluster = False
if(((cluster_sRNA[0])>=mur)&( abundance >=abud_cutoff)):
end = previous+25
out = open(str(fo)+'_'+str(seq_size)+".txt",'a') ### difference size different file ??
out.write(str(chro))
out.write('\t')
out.write(str(int(start)))
out.write('\t')
out.write(str(int(end)))
out.write('\t')
out.write(str(name))
out.write('\t')
out.write(str(int(abundance)))
out.write('\n')
out.close()
names = name.split(',')
for t in range(1,len(names)-1):
if len(names[t]) in size:
size[len(names[t])] += 1
else:
size[len(names[t])] = 0
#prfloat(chro,start,end,name,abundance)
s += 1
previous = genome_position
nam = sRNA[i]
token=sRNA[i].split('_')
abund = ab
i += 1
print "abundance cut-off: "+str(abud_cutoff)
print "max gap length: "+str(gap)
print "min number fo unique reads: "+str(mur)
print("number of clusters: "+str(s))
print "size:number_of_reads =", size
""" for plotting size distribution
import numpy
y = [0]*6
x = [0]*6
z = 0
for element in size:
x[z] = element -0.5
y[z] = size[element]
z += 1
from pylab import *
fig = figure()
ax = fig.add_subplot(111,polar = False)
ax.bar(x, y)
show()
"""
def file_call(fi,fo,abu,gap,mur):
start = time.clock()
abud_cutoff = abu
find_cluster(abud_cutoff,fi,fo,gap,mur)
lap = time.clock() - start
def file_call_size(fi,fo,seq_size,abu,gap,mur):
start = time.clock()
abud_cutoff = abu
find_cluster_size(abud_cutoff,fi,fo,int(seq_size),gap,mur)
lap = time.clock() - start
### reading commond line
fi = sys.argv[1]
fo = sys.argv[2]
abu=float(sys.argv[4])
### call function to calculate clusters
### define cluster based on different sequence size
divide_by_size = sys.argv[3]
### max gap between two reads
gap=int(sys.argv[7])
min_unique_read=int(sys.argv[8])
mur=min_unique_read
print "size fractionation: ",(divide_by_size)
if (divide_by_size == 'True'):
for seq_size in range(int(sys.argv[5]),int(sys.argv[6])+1):
file_call_size(fi,fo,seq_size,abu,gap,mur)
file_call(fi,fo,abu,gap,mur)
else:
file_call(fi,fo,abu,gap,mur)