/usr/bin/get_rdata is in falconkit 0.1.3+20140820-1.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 | #!/usr/bin/python
#################################################################################$$
# Copyright (c) 2011-2014, Pacific Biosciences of California, Inc.
#
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted (subject to the limitations in the
# disclaimer below) provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
#
# * Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following
# disclaimer in the documentation and/or other materials provided
# with the distribution.
#
# * Neither the name of Pacific Biosciences nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE
# GRANTED BY THIS LICENSE. THIS SOFTWARE IS PROVIDED BY PACIFIC
# BIOSCIENCES AND ITS CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED
# WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
# OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL PACIFIC BIOSCIENCES OR ITS
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
# USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
# ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
# OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
# SUCH DAMAGE.
#################################################################################$$
import sys
import glob
#import pkg_resources
import uuid
from datetime import datetime
from collections import Counter
from multiprocessing import Pool
#from pbtools.pbdagcon.q_sense import *
import os
"""
try:
__p4revision__ = "$Revision: #4 $"
__p4change__ = "$Change: 121571 $"
revNum = int(__p4revision__.strip("$").split(" ")[1].strip("#"))
changeNum = int(__p4change__.strip("$").split(":")[-1])
__version__ = "%s-r%d-c%d" % ( pkg_resources.require("pbtools.pbhgap")[0].version, revNum, changeNum )
except:
__version__ = "pbtools.hbar-dtk-github"
"""
query_fasta_fn = sys.argv[1]
target_fasta_fn = sys.argv[2]
m4_fofn = sys.argv[3]
bestn = int(sys.argv[4])
group_id = int(sys.argv[5])
num_chunk = int(sys.argv[6])
min_cov = int(sys.argv[7])
max_cov = int(sys.argv[8])
trim_align = int(sys.argv[9])
trim_plr = int(sys.argv[10])
rmap = dict(zip("ACGTNacgt-","TGCANntgca-"))
def rc(seq):
return "".join([rmap[c] for c in seq[::-1]])
"""0x239fb832/0_590 0x722a1e26 -1843 81.6327 0 62 590 590 0 6417 6974 9822 254 11407 -74.5375 -67.9 1"""
query_to_target = {}
with open(m4_fofn) as fofn:
for fn in fofn:
fn = fn.strip()
with open(fn) as m4_f:
for l in m4_f:
d = l.strip().split()
id1, id2 = d[:2]
#if -noSplitSubread not used, we will need the following line
#id1 = id1.split("/")[0]
if id1 == id2:
continue
if hash(id2) % num_chunk != group_id:
continue
if int(d[2]) > -1000: continue
if int(d[11]) < 4000: continue
query_to_target.setdefault(id1, [])
query_to_target[id1].append( (int(d[2]), l) )
target_to_query = {}
for id1 in query_to_target:
query_to_target[id1].sort()
rank = 0
for s, ll in query_to_target[id1][:bestn]:
l = ll.strip()
d = l.split()
id1, id2 = d[:2]
target_to_query.setdefault(id2,[])
target_to_query[id2].append( ( (int(d[5])-int(d[6]), int(d[2])), l ) )
#target_to_query[id2].append( ( int(d[2]), l ) )
#rank += 1
from pbcore.io import FastaIO
query_data = {}
with open(query_fasta_fn) as fofn:
for fa_fn in fofn:
fa_fn = fa_fn.strip()
f_s = FastaIO.FastaReader(fa_fn)
for s in f_s:
id1 = s.name
if id1 not in query_to_target:
continue
query_data[id1]=s.sequence
f_s.file.close()
target_data = {}
with open(target_fasta_fn) as fofn:
for fa_fn in fofn:
fa_fn = fa_fn.strip()
f_s = FastaIO.FastaReader(fa_fn)
for s in f_s:
id2 = s.name
if hash(id2) % num_chunk != group_id:
continue
target_data[id2]=s.sequence
f_s.file.close()
ec_data = []
base_count = Counter()
r_count =0
for id2 in target_to_query:
if len(target_to_query[id2])<10:
continue
if id2 not in target_data:
continue
ref_data = (id2, target_data[id2])
ref_len = len(target_data[id2])
base_count.clear()
base_count.update( target_data[id2] )
if 1.0*base_count.most_common(1)[0][1]/ref_len > 0.8: # don't do preassmbly if a read is of >80% of the same base
continue
read_data = []
query_alignment = target_to_query[id2]
query_alignment.sort() # get better alignment
total_bases = 0
max_cov_bases = max_cov * ref_len * 1.2
#min_cov_bases = min_cov * ref_len * 3
for rank_score, l in query_alignment:
rank, score = rank_score
#score = rank_score
l = l.split()
id1 = l[0]
#if -noSplitSubread not used, we will need the following line
#id1 = id1.split("/")[0]
q_s = int(l[5]) + trim_align
q_e = int(l[6]) - trim_align
strand = int(l[8])
t_s = int(l[9])
t_e = int(l[10])
t_l = int(l[11])
#if strand == 1:
# t_s, t_e = t_l - t_e, t_l - t_s
# t_s += trim_align
# t_e -= trim_align
if q_e - q_s < 400:
continue
total_bases += q_e - q_s
if total_bases > max_cov_bases:
break
q_seq = query_data[id1][q_s:q_e]
read_data.append( ( "%s/0/%d_%d" % (id1, q_s, q_e), q_s, q_e, q_seq, strand, t_s, t_e) )
if len(read_data) > 5:
r_count += 1
t_id, t_seq = ref_data
t_len = len(t_seq)
print t_id, t_seq
for r in read_data:
q_id, q_s, q_e, q_seq, strand, t_s, t_e = r
if strand == 1:
q_seq = rc(q_seq)
print q_id, q_seq
#if r_count > 600:
# break
print "+ +"
print "- -"
#output_dir,dumb = os.path.split( os.path.abspath( output_file ) )
#output_log = open ( os.path.join( output_dir, "j%02d.log" % group_id ), "w" )
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