def fetch(self,**kwargs):
''' Fetch intervals in a given region. '''
if kwargs.has_key('chrom'):
wigs=wWigIO.getIntervals(self.fname,kwargs['chrom'],kwargs.get('start',0),kwargs.get('stop',0))
if isinstance(wigs,basestring): # bad value
raise ValueError("Couldn't get intervals.")
return wigs
raise ValueError("Chromosome not provided.")
return
def fetch(self, **kwargs):
''' Fetch intervals in a given region. '''
if kwargs.has_key('chrom'):
wigs = wWigIO.getIntervals(self.fname, kwargs['chrom'],
kwargs.get('start', 0),
kwargs.get('stop', 0))
if isinstance(wigs, basestring): # bad value
raise ValueError("Couldn't get intervals.")
return wigs
raise ValueError("Chromosome not provided.")
return
# ------------------------------------
# Misc functions
# ------------------------------------
# ------------------------------------
# Classes
# ------------------------------------
# ------------------------------------
# Main
# ------------------------------------
if __name__=="__main__":
# get information from bigwig file
wWigIO.open('test.bw')
chroms = wWigIO.getChromSize('test.bw')
wigs = wWigIO.getIntervals('test.bw', 'chr1', 10, 200)
wWigIO.close('test.bw')
print wigs
# bigwig -> wig
wWigIO.bigWigToWig('test.bw','test.wig')
# write the chrom sizes into test.sizes
with open('test.sizes','w') as fh:
for chrom in chroms:
print >>fh, chrom+"\t"+str(chroms[chrom])
# wig -> bigwig
wWigIO.wigToBigWig('test.wig','test.sizes','test2.bw')
def main(sim_fastq, U2_GTAG_5_file, U2_GTAG_3_file, phylop_vertebrates,
phylop_primates, exon_scores):
MEs = set([])
wWigIO.open(phylop_vertebrates)
wWigIO.open(phylop_primates)
U2_GTAG_5 = PWM_to_dict(U2_GTAG_5_file)
U2_GTAG_3 = PWM_to_dict(U2_GTAG_3_file)
U2_GTAG_5_max_score = 0
U2_GTAG_3_max_score = 0
for index in range(13):
U2_GTAG_5_max_score += max(U2_GTAG_5['A'][index],
U2_GTAG_5['C'][index],
U2_GTAG_5['T'][index],
U2_GTAG_5['G'][index])
for index in range(17):
U2_GTAG_3_max_score += max(U2_GTAG_3['A'][index],
U2_GTAG_3['C'][index],
U2_GTAG_3['T'][index],
U2_GTAG_3['G'][index])
TOTAL_U2_max_score = U2_GTAG_5_max_score + U2_GTAG_3_max_score
gencode_U2_scores = []
gencode_mean_conservation_vertebrates = []
gencode_mean_conservation_primates = []
for row in csv.reader(open(exon_scores), delimiter=' '):
chr, estart, eend, strand, U2_score, mean_conservation_vertebrates, mean_conservation_primates = row
gencode_U2_scores.append(float(U2_score))
gencode_mean_conservation_vertebrates.append(
float(mean_conservation_vertebrates))
gencode_mean_conservation_primates.append(
float(mean_conservation_primates))
for row in csv.reader(open(sim_fastq), delimiter='\t'):
if row[0][0] == "@":
SJ, ME_seq, estart, eend, total_coverage, n = row[0].split("_")
len_ME = len(ME_seq)
SJ = SJ[1:]
SJ_chr, SJ_istart, SJ_iend = re.findall(r"[\w']+", SJ)
SJ_len = int(SJ_iend) - int(SJ_istart)
Kmer = SJ_len - (len_ME + 1)
P_ME = 1 - (1 - (float(1) / float(4**len_ME + 4)))**Kmer
strand = "+"
if "-" in SJ:
strand = "-"
estart = int(estart)
eend = int(eend)
MEs.add((SJ_chr, strand, estart, eend, P_ME))
for m in MEs:
chr, strand, estart, eend, P_ME = m
estart, eend = sorted([estart, eend])
E5 = str(Genome[chr][estart - 14:estart + 3]).upper()
E3 = str(Genome[chr][eend - 3:eend + 10]).upper()
if strand == "-":
E5 = str(Genome[chr][eend - 3:eend +
14].reverse_complement()).upper()
E3 = str(Genome[chr][estart - 10:estart +
3].reverse_complement()).upper()
U2_score = 0
i = 0
for N in E5:
if N != "N":
U2_score += U2_GTAG_3[N][i]
i += 1
i = 0
for N in E3:
if N != "N":
U2_score += U2_GTAG_5[N][i]
i += 1
U2_score = percent(U2_score, TOTAL_U2_max_score)
conservation_vertebrates = wWigIO.getIntervals(phylop_vertebrates, chr,
estart - 2, eend + 2)
conservation_primates = wWigIO.getIntervals(phylop_primates, chr,
estart - 2, eend + 2)
mean_conservation_vertebrates = 0
mean_conservation_primates = 0
for i in conservation_vertebrates:
mean_conservation_vertebrates += i[2]
try:
mean_conservation_vertebrates = mean_conservation_vertebrates / len(
conservation_vertebrates)
except ZeroDivisionError:
pass
for i in conservation_primates:
mean_conservation_primates += i[2]
try:
mean_conservation_primates = mean_conservation_primates / len(
conservation_primates)
except ZeroDivisionError:
pass
ME_percentil_U2_score = stats.percentileofscore(
gencode_U2_scores, U2_score)
ME_percentil_mean_conservation_vertebrates = stats.percentileofscore(
gencode_mean_conservation_vertebrates, mean_conservation_primates)
ME_percentil_mean_conservation_primates = stats.percentileofscore(
gencode_mean_conservation_primates, mean_conservation_vertebrates)
overall_score = P_ME * (1 - ME_percentil_U2_score / 100) * (
1 - ME_percentil_mean_conservation_vertebrates / 100)
if ME_percentil_mean_conservation_primates > ME_percentil_mean_conservation_vertebrates:
overall_score = P_ME * (1 - ME_percentil_U2_score / 100) * (
1 - ME_percentil_mean_conservation_primates / 100)
#print chr, estart, eend, strand, U2_score, mean_conservation_vertebrates, mean_conservation_primates
print chr, estart, eend, strand, U2_score, ME_percentil_U2_score, mean_conservation_vertebrates, ME_percentil_mean_conservation_vertebrates, mean_conservation_primates, ME_percentil_mean_conservation_primates, P_ME, overall_score
def main(gencode_bed, U2_GTAG_5_file, U2_GTAG_3_file, phylop_vertebrates,
phylop_primates):
wWigIO.open(phylop_vertebrates)
wWigIO.open(phylop_primates)
U2_GTAG_5 = PWM_to_dict(U2_GTAG_5_file)
U2_GTAG_3 = PWM_to_dict(U2_GTAG_3_file)
U2_GTAG_5_max_score = 0
U2_GTAG_3_max_score = 0
for index in range(13):
U2_GTAG_5_max_score += max(U2_GTAG_5['A'][index],
U2_GTAG_5['C'][index],
U2_GTAG_5['T'][index],
U2_GTAG_5['G'][index])
for index in range(17):
U2_GTAG_3_max_score += max(U2_GTAG_3['A'][index],
U2_GTAG_3['C'][index],
U2_GTAG_3['T'][index],
U2_GTAG_3['G'][index])
TOTAL_U2_max_score = U2_GTAG_5_max_score + U2_GTAG_3_max_score
exons = set([])
for row in csv.reader(open(gencode_bed), delimiter='\t'):
csv.field_size_limit(1000000000)
qstarts = map(int, row[11].strip(",").split(","))
blocksizes = map(int, row[10].strip(",").split(","))
start = int(row[1])
strand = row[5]
bn = int(row[9])
chr = row[0]
for q1, b in zip(qstarts[1:-1], blocksizes[1:-1]):
estart = start + q1
eend = start + q1 + b
E5 = str(Genome[chr][estart - 14:estart + 3]).upper()
E3 = str(Genome[chr][eend - 3:eend + 10]).upper()
if strand == "-":
E5 = str(Genome[chr][eend - 3:eend +
14].reverse_complement()).upper()
E3 = str(Genome[chr][estart - 10:estart +
3].reverse_complement()).upper()
U2_score = 0
i = 0
for N in E5:
U2_score += U2_GTAG_3[N][i]
i += 1
i = 0
for N in E3:
U2_score += U2_GTAG_5[N][i]
i += 1
U2_score = percent(U2_score, TOTAL_U2_max_score)
if E5[-5:-3] == "AG" and E3[3:5] == "GT":
exons.add((chr, estart, eend, strand, U2_score))
# if " ".join([chr, estart, eend]) == "chr17 26597935 26598725":
# print
for e in exons:
chr, estart, eend, strand, U2_score = e
conservation_vertebrates = wWigIO.getIntervals(phylop_vertebrates, chr,
estart - 2, eend + 2)
conservation_primates = wWigIO.getIntervals(phylop_primates, chr,
estart - 2, eend + 2)
mean_conservation_vertebrates = 0
mean_conservation_primates = 0
for i in conservation_vertebrates:
mean_conservation_vertebrates += i[2]
try:
mean_conservation_vertebrates = mean_conservation_vertebrates / len(
conservation_vertebrates)
except ZeroDivisionError:
pass
for i in conservation_primates:
mean_conservation_primates += i[2]
try:
mean_conservation_primates = mean_conservation_primates / len(
conservation_primates)
except ZeroDivisionError:
pass
print chr, estart, eend, strand, U2_score, mean_conservation_vertebrates, mean_conservation_primates
def __NDR_bin_detect(self):
"""检视所有 cover 的 bins."""
for idx in sorted(self.l_umt_met):
self.__bin_info(idx)
"""对这种可能显著并且不会继续落 reads 的 bin"""
if idx < self.bin_idx_min:
np_obs = self.l_umt_met[idx]
np_exp = self.np_RATIO * np.sum(np_obs)
chisquare = np.sum((np_obs - np_exp)**2 / np_exp)
pval = -1 * np.log10(1 - scipy.stats.chi2.cdf(chisquare, 1))
if np_obs[1] < np_exp[1]:
pval = -1 * pval
pos_center = int((self.bin_begin + self.bin_endin) / 2)
bin_up = pos_center - self.step_len * 10
bin_down = pos_center + self.step_len * 10
# print bin_up, bin_down
np_val_ext = np.zeros(2)
l_rat_umt_met_ext = []
l_rat_umt_met_sur1 = []
l_rat_umt_met_sur2 = []
try:
record = self.tb_file.query(self.chrom, bin_up, bin_down)
for rec in record:
pos = (int(rec[1]) + int(rec[2])) / 2
total = int(rec[3]) + int(rec[4])
if total >= self.depth:
np_val_ext[0] += int(rec[3])
np_val_ext[1] += int(rec[4])
ratio = int(rec[4]) / (int(rec[3]) + int(rec[4]))
l_rat_umt_met_ext.append(ratio)
if abs(pos - (self.bin_begin - 40)) < 40:
l_rat_umt_met_sur1.append(ratio)
if abs(pos - (self.bin_endin + 40)) < 40:
l_rat_umt_met_sur2.append(ratio)
except:
pass
np_obs_ext = np_val_ext
np_exp_ext = self.np_RATIO * np.sum(np_obs_ext)
val_reg = np.array(self.l_rat_umt_met[idx]).mean()
val_ext = np.array(l_rat_umt_met_ext).mean()
val_sur1 = np.array(l_rat_umt_met_sur1).mean()
val_sur2 = np.array(l_rat_umt_met_sur2).mean()
chisquare_ext = np.sum(
(np_obs_ext - np_exp_ext)**2 / np_exp_ext)
pval_ext = -1 * np.log10(
1 - scipy.stats.chi2.cdf(chisquare_ext, 1))
if np_obs_ext[1] < np_exp_ext[1]:
pval_ext = -1 * pval_ext
pval_ttest = -1 * np.log10(
scipy.stats.ttest_ind(self.l_rat_umt_met[idx],
l_rat_umt_met_ext,
equal_var=False)[1])
if val_reg < val_ext:
pval_ttest = -1 * pval_ttest
pval_ttest2l = -1 * np.log10(
scipy.stats.ttest_ind(self.l_rat_umt_met[idx],
l_rat_umt_met_sur1,
equal_var=False)[1])
if val_reg < val_sur1:
pval_ttest2l = -1 * pval_ttest2l
pval_ttest2r = -1 * np.log10(
scipy.stats.ttest_ind(self.l_rat_umt_met[idx],
l_rat_umt_met_sur2,
equal_var=False)[1])
if val_reg < val_sur2:
pval_ttest2r = -1 * pval_ttest2r
np_bw = np.array([
f[2] for f in wWigIO.getIntervals(
in_bw, self.chrom, self.bin_begin, self.bin_endin)
])
# print self.bin_begin, self.bin_endin, np_bw
mean_bw = np_bw.mean()
print "%s\t%d\t%d\t%1.2f\t%1.2f\t%1.2f\t%1.2f\t%1.2f\t%1.2f\t%d,%d\t%d,%d\t%1.2f,%1.2f\t%1.2f,%1.2f\t%1.2f,%1.2f,%1.2f,%1.2f" % (
self.chrom, self.bin_begin, self.bin_endin, mean_bw, pval,
pval_ext, pval_ttest, pval_ttest2l, pval_ttest2r,
self.l_umt_met[idx][0], self.l_umt_met[idx][1],
np_val_ext[0], np_val_ext[1], np_exp[0], np_exp[1],
np_exp_ext[0], np_exp_ext[1], val_reg, val_ext, val_sur1,
val_sur2)
# print "%s\t%d\t%d\t%1.2f\t%s\t%s" % (self.chrom, self.bin_begin, self.bin_endin, pval_ttest, val_reg, val_ext)
del self.l_umt_met[idx]
del self.l_rat_umt_met[idx]
# ------------------------------------
# Misc functions
# ------------------------------------
# ------------------------------------
# Classes
# ------------------------------------
# ------------------------------------
# Main
# ------------------------------------
if __name__ == "__main__":
# get information from bigwig file
wWigIO.open('test.bw')
chroms = wWigIO.getChromSize('test.bw')
wigs = wWigIO.getIntervals('test.bw', 'chr1', 10, 200)
wWigIO.close('test.bw')
print wigs
# bigwig -> wig
wWigIO.bigWigToWig('test.bw', 'test.wig')
# write the chrom sizes into test.sizes
with open('test.sizes', 'w') as fh:
for chrom in chroms:
print >> fh, chrom + "\t" + str(chroms[chrom])
# wig -> bigwig
wWigIO.wigToBigWig('test.wig', 'test.sizes', 'test2.bw')
def main(sim_fastq, U2_GTAG_5_file, U2_GTAG_3_file, phylop_vertebrates,
phylop_primates):
MEs = set([])
wWigIO.open(phylop_vertebrates)
wWigIO.open(phylop_primates)
U2_GTAG_5 = PWM_to_dict(U2_GTAG_5_file)
U2_GTAG_3 = PWM_to_dict(U2_GTAG_3_file)
U2_GTAG_5_max_score = 0
U2_GTAG_3_max_score = 0
for index in range(13):
U2_GTAG_5_max_score += max(U2_GTAG_5['A'][index],
U2_GTAG_5['C'][index],
U2_GTAG_5['T'][index],
U2_GTAG_5['G'][index])
for index in range(17):
U2_GTAG_3_max_score += max(U2_GTAG_3['A'][index],
U2_GTAG_3['C'][index],
U2_GTAG_3['T'][index],
U2_GTAG_3['G'][index])
TOTAL_U2_max_score = U2_GTAG_5_max_score + U2_GTAG_3_max_score
for row in csv.reader(open(sim_fastq), delimiter='\t'):
chr, estart, eend, exon, exon_len, strand = row
estart = int(estart)
eend = int(eend)
# if row[0][0]=="@":
# SJ, ME_seq, estart, eend, total_coverage, n = row[0].split("_")
# len_ME = len(ME_seq)
# SJ = SJ[1:]
# SJ_chr, SJ_istart, SJ_iend = re.findall(r"[\w']+", SJ)
# SJ_len = int(SJ_iend) - int(SJ_istart)
# Kmer = SJ_len - (len_ME+1)
# P_ME = 1 - ( 1 - (float(1)/float(4**len_ME+4)))**Kmer
# strand = "+"
# if "-" in SJ:
# strand = "-"
# estart = int(estart)
# eend = int(eend)
# MEs.add((SJ_chr, strand, estart, eend, P_ME))
# for m in MEs:
# chr, strand, estart, eend, P_ME = m
# estart, eend = sorted([estart, eend])
E5 = str(Genome[chr][estart - 14:estart + 3]).upper()
E3 = str(Genome[chr][eend - 3:eend + 10]).upper()
if strand == "-":
E5 = str(Genome[chr][eend - 3:eend +
14].reverse_complement()).upper()
E3 = str(Genome[chr][estart - 10:estart +
3].reverse_complement()).upper()
E5 = E5[:-5] + "AG" + E5[-3:]
E3 = E3[:3] + "GT" + E3[5:]
U2_score = 0
ME5_U2_score = 0
ME3_U2_score = 0
i = 0
for N in E5:
if N != "N":
U2_score += U2_GTAG_3[N][i]
ME5_U2_score += U2_GTAG_3[N][i]
i += 1
i = 0
for N in E3:
if N != "N":
U2_score += U2_GTAG_5[N][i]
ME3_U2_score += U2_GTAG_5[N][i]
i += 1
ME3_U2_score = percent(ME3_U2_score, U2_GTAG_5_max_score)
ME5_U2_score = percent(ME5_U2_score, U2_GTAG_3_max_score)
U2_score = percent(U2_score, TOTAL_U2_max_score)
conservation_vertebrates = wWigIO.getIntervals(phylop_vertebrates, chr,
estart - 2, eend + 2)
conservation_primates = wWigIO.getIntervals(phylop_primates, chr,
estart - 2, eend + 2)
mean_conservation_vertebrates = 0
mean_conservation_primates = 0
for i in conservation_vertebrates:
mean_conservation_vertebrates += i[2]
try:
mean_conservation_vertebrates = mean_conservation_vertebrates / len(
conservation_vertebrates)
except ZeroDivisionError:
pass
for i in conservation_primates:
mean_conservation_primates += i[2]
try:
mean_conservation_primates = mean_conservation_primates / len(
conservation_primates)
except ZeroDivisionError:
pass
#print chr, estart, eend, strand, U2_score, mean_conservation_vertebrates, mean_conservation_primates
print chr, estart, eend, strand, U2_score, ME5_U2_score, ME3_U2_score, mean_conservation_vertebrates, mean_conservation_primates
def main(sim_fastq, U2_GTAG_5_file, U2_GTAG_3_file, phylop_vertebrates, phylop_primates):
MEs = set([])
wWigIO.open(phylop_vertebrates)
wWigIO.open(phylop_primates)
U2_GTAG_5 = PWM_to_dict(U2_GTAG_5_file)
U2_GTAG_3 = PWM_to_dict(U2_GTAG_3_file)
U2_GTAG_5_max_score = 0
U2_GTAG_3_max_score = 0
for index in range(13):
U2_GTAG_5_max_score += max(U2_GTAG_5['A'][index], U2_GTAG_5['C'][index], U2_GTAG_5['T'][index], U2_GTAG_5['G'][index])
for index in range(17):
U2_GTAG_3_max_score += max(U2_GTAG_3['A'][index], U2_GTAG_3['C'][index], U2_GTAG_3['T'][index], U2_GTAG_3['G'][index])
TOTAL_U2_max_score = U2_GTAG_5_max_score + U2_GTAG_3_max_score
for row in csv.reader(open(sim_fastq), delimiter = '\t'):
chr, estart, eend, exon, exon_len, strand = row
estart = int(estart)
eend = int(eend)
# if row[0][0]=="@":
# SJ, ME_seq, estart, eend, total_coverage, n = row[0].split("_")
# len_ME = len(ME_seq)
# SJ = SJ[1:]
# SJ_chr, SJ_istart, SJ_iend = re.findall(r"[\w']+", SJ)
# SJ_len = int(SJ_iend) - int(SJ_istart)
# Kmer = SJ_len - (len_ME+1)
# P_ME = 1 - ( 1 - (float(1)/float(4**len_ME+4)))**Kmer
# strand = "+"
# if "-" in SJ:
# strand = "-"
# estart = int(estart)
# eend = int(eend)
# MEs.add((SJ_chr, strand, estart, eend, P_ME))
# for m in MEs:
# chr, strand, estart, eend, P_ME = m
# estart, eend = sorted([estart, eend])
E5 = str(Genome[chr][estart-14:estart+3]).upper()
E3 = str(Genome[chr][eend-3:eend+10]).upper()
if strand == "-":
E5 = str(Genome[chr][eend-3:eend+14].reverse_complement()).upper()
E3 = str(Genome[chr][estart-10:estart+3].reverse_complement()).upper()
E5 = E5[:-5] + "AG" + E5[-3:]
E3 = E3[:3] + "GT" + E3[5:]
U2_score = 0
ME5_U2_score = 0
ME3_U2_score = 0
i = 0
for N in E5:
if N!="N":
U2_score += U2_GTAG_3[N][i]
ME5_U2_score += U2_GTAG_3[N][i]
i += 1
i = 0
for N in E3:
if N!="N":
U2_score += U2_GTAG_5[N][i]
ME3_U2_score += U2_GTAG_5[N][i]
i += 1
ME3_U2_score = percent(ME3_U2_score, U2_GTAG_5_max_score)
ME5_U2_score = percent(ME5_U2_score, U2_GTAG_3_max_score)
U2_score = percent(U2_score, TOTAL_U2_max_score)
conservation_vertebrates = wWigIO.getIntervals(phylop_vertebrates, chr, estart-2, eend+2)
conservation_primates = wWigIO.getIntervals(phylop_primates, chr, estart-2, eend+2)
mean_conservation_vertebrates = 0
mean_conservation_primates = 0
for i in conservation_vertebrates:
mean_conservation_vertebrates += i[2]
try:
mean_conservation_vertebrates = mean_conservation_vertebrates/len(conservation_vertebrates)
except ZeroDivisionError:
pass
for i in conservation_primates:
mean_conservation_primates += i[2]
try:
mean_conservation_primates = mean_conservation_primates/len(conservation_primates)
except ZeroDivisionError:
pass
#print chr, estart, eend, strand, U2_score, mean_conservation_vertebrates, mean_conservation_primates
print chr, estart, eend, strand, U2_score, ME5_U2_score, ME3_U2_score, mean_conservation_vertebrates, mean_conservation_primates
def main(gencode_bed, U2_GTAG_5_file, U2_GTAG_3_file, phylop_vertebrates, phylop_primates):
wWigIO.open(phylop_vertebrates)
wWigIO.open(phylop_primates)
U2_GTAG_5 = PWM_to_dict(U2_GTAG_5_file)
U2_GTAG_3 = PWM_to_dict(U2_GTAG_3_file)
U2_GTAG_5_max_score = 0
U2_GTAG_3_max_score = 0
for index in range(13):
U2_GTAG_5_max_score += max(U2_GTAG_5['A'][index], U2_GTAG_5['C'][index], U2_GTAG_5['T'][index], U2_GTAG_5['G'][index])
for index in range(17):
U2_GTAG_3_max_score += max(U2_GTAG_3['A'][index], U2_GTAG_3['C'][index], U2_GTAG_3['T'][index], U2_GTAG_3['G'][index])
TOTAL_U2_max_score = U2_GTAG_5_max_score + U2_GTAG_3_max_score
exons = set([])
for row in csv.reader(open(gencode_bed), delimiter = '\t'):
csv.field_size_limit(1000000000)
qstarts = map (int, row[11].strip(",").split(","))
blocksizes = map(int, row[10].strip(",").split(","))
start = int(row[1])
strand = row[5]
bn = int(row[9])
chr = row[0]
for q1, b in zip(qstarts[1:-1], blocksizes[1:-1]):
estart = start + q1
eend = start + q1 + b
E5 = str(Genome[chr][estart-14:estart+3]).upper()
E3 = str(Genome[chr][eend-3:eend+10]).upper()
if strand == "-":
E5 = str(Genome[chr][eend-3:eend+14].reverse_complement()).upper()
E3 = str(Genome[chr][estart-10:estart+3].reverse_complement()).upper()
U2_score = 0
i = 0
for N in E5:
U2_score += U2_GTAG_3[N][i]
i += 1
i = 0
for N in E3:
U2_score += U2_GTAG_5[N][i]
i += 1
U2_score = percent(U2_score, TOTAL_U2_max_score)
if E5[-5:-3]=="AG" and E3[3:5] == "GT":
exons.add((chr, estart, eend, strand, U2_score))
# if " ".join([chr, estart, eend]) == "chr17 26597935 26598725":
# print
for e in exons:
chr, estart, eend, strand, U2_score = e
conservation_vertebrates = wWigIO.getIntervals(phylop_vertebrates, chr, estart-2, eend+2)
conservation_primates = wWigIO.getIntervals(phylop_primates, chr, estart-2, eend+2)
mean_conservation_vertebrates = 0
mean_conservation_primates = 0
for i in conservation_vertebrates:
mean_conservation_vertebrates += i[2]
try:
mean_conservation_vertebrates = mean_conservation_vertebrates/len(conservation_vertebrates)
except ZeroDivisionError:
pass
for i in conservation_primates:
mean_conservation_primates += i[2]
try:
mean_conservation_primates = mean_conservation_primates/len(conservation_primates)
except ZeroDivisionError:
pass
print chr, estart, eend, strand, U2_score, mean_conservation_vertebrates, mean_conservation_primates
