annotate build/scripts-3.6/SeqSero2_package.py @ 14:047956dacae4 draft default tip

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author cstrittmatter
date Thu, 21 May 2020 22:01:02 -0400
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10
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1 #!/Users/charles.strittmatter/miniconda3/bin/python
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2
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3 import sys
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4 import time
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5 import random
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6 import os
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7 import subprocess
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8 import gzip
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9 import io
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10 import pickle
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11 import argparse
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12 import itertools
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13 from distutils.version import LooseVersion
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14 from distutils.spawn import find_executable
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15 sys.path.insert(1,sys.path[0]+'/..')
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16
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17 try:
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18 from .version import SeqSero2_version
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19 except Exception: #ImportError
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20 from version import SeqSero2_version
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21
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22 ### SeqSero Kmer
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23 def parse_args():
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24 "Parse the input arguments, use '-h' for help."
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25 parser = argparse.ArgumentParser(usage='SeqSero2_package.py -t <data_type> -m <mode> -i <input_data> [-d <output_directory>] [-p <number of threads>] [-b <BWA_algorithm>]\n\nDevelopper: Shaokang Zhang (zskzsk@uga.edu), Hendrik C Den-Bakker (Hendrik.DenBakker@uga.edu) and Xiangyu Deng (xdeng@uga.edu)\n\nContact email:seqsero@gmail.com\n\nVersion: v1.1.1')#add "-m <data_type>" in future
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26 parser.add_argument("-i",nargs="+",help="<string>: path/to/input_data",type=os.path.abspath) ### add 'type=os.path.abspath' to generate absolute path of input data.
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27 parser.add_argument("-t",choices=['1','2','3','4','5','6'],help="<int>: '1' for interleaved paired-end reads, '2' for separated paired-end reads, '3' for single reads, '4' for genome assembly, '5' for nanopore fasta, '6' for nanopore fastq")
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28 parser.add_argument("-b",choices=['sam','mem'],default="mem",help="<string>: algorithms for bwa mapping for allele mode; 'mem' for mem, 'sam' for samse/sampe; default=mem; optional; for now we only optimized for default 'mem' mode")
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29 parser.add_argument("-p",default="1",help="<int>: number of threads for allele mode, if p >4, only 4 threads will be used for assembly since the amount of extracted reads is small, default=1")
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30 parser.add_argument("-m",choices=['k','a'],default="a",help="<string>: which workflow to apply, 'a'(raw reads allele micro-assembly), 'k'(raw reads and genome assembly k-mer), default=a")
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31 parser.add_argument("-n",help="<string>: optional, to specify a sample name in the report output")
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32 parser.add_argument("-d",help="<string>: optional, to specify an output directory name, if not set, the output directory would be 'SeqSero_result_'+time stamp+one random number")
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33 parser.add_argument("-c",action="store_true",help="<flag>: if '-c' was flagged, SeqSero2 will only output serotype prediction without the directory containing log files")
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34 parser.add_argument("-s",action="store_true",help="<flag>: if '-s' was flagged, SeqSero2 will not output header in SeqSero_result.tsv")
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35 parser.add_argument("--check",action="store_true",help="<flag>: use '--check' flag to check the required dependencies")
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36 parser.add_argument('-v', '--version', action='version', version='%(prog)s ' + SeqSero2_version)
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37 return parser.parse_args()
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38
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39 ### check paths of dependencies
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40 check_dependencies = parse_args().check
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41 dependencies = ['bwa','samtools','blastn','fastq-dump','spades.py','bedtools','SalmID.py']
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42 if check_dependencies:
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43 for item in dependencies:
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44 ext_path = find_executable(item)
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45 if ext_path is not None:
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46 print ("Using "+item+" - "+ext_path)
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47 else:
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48 print ("ERROR: can not find "+item+" in PATH")
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49 sys.exit()
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50 ### end of --check
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51
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52 def reverse_complement(sequence):
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53 complement = {
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54 'A': 'T',
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55 'C': 'G',
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56 'G': 'C',
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57 'T': 'A',
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58 'N': 'N',
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59 'M': 'K',
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60 'R': 'Y',
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61 'W': 'W',
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62 'S': 'S',
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63 'Y': 'R',
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64 'K': 'M',
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65 'V': 'B',
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66 'H': 'D',
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67 'D': 'H',
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68 'B': 'V'
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69 }
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70 return "".join(complement[base] for base in reversed(sequence))
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71
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72
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73 def createKmerDict_reads(list_of_strings, kmer):
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74 kmer_table = {}
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75 for string in list_of_strings:
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76 sequence = string.strip('\n')
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77 for i in range(len(sequence) - kmer + 1):
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78 new_mer = sequence[i:i + kmer].upper()
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79 new_mer_rc = reverse_complement(new_mer)
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80 if new_mer in kmer_table:
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81 kmer_table[new_mer.upper()] += 1
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82 else:
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83 kmer_table[new_mer.upper()] = 1
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84 if new_mer_rc in kmer_table:
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85 kmer_table[new_mer_rc.upper()] += 1
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86 else:
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87 kmer_table[new_mer_rc.upper()] = 1
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88 return kmer_table
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89
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90
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91 def multifasta_dict(multifasta):
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92 multifasta_list = [
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93 line.strip() for line in open(multifasta, 'r') if len(line.strip()) > 0
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94 ]
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95 headers = [i for i in multifasta_list if i[0] == '>']
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96 multifasta_dict = {}
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97 for h in headers:
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98 start = multifasta_list.index(h)
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99 for element in multifasta_list[start + 1:]:
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100 if element[0] == '>':
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101 break
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102 else:
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103 if h[1:] in multifasta_dict:
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104 multifasta_dict[h[1:]] += element
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105 else:
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106 multifasta_dict[h[1:]] = element
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107 return multifasta_dict
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108
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109
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110 def multifasta_single_string(multifasta):
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111 multifasta_list = [
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112 line.strip() for line in open(multifasta, 'r')
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113 if (len(line.strip()) > 0) and (line.strip()[0] != '>')
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114 ]
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115 return ''.join(multifasta_list)
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116
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117
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118 def chunk_a_long_sequence(long_sequence, chunk_size=60):
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119 chunk_list = []
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120 steps = len(long_sequence) // 60 #how many chunks
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121 for i in range(steps):
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122 chunk_list.append(long_sequence[i * chunk_size:(i + 1) * chunk_size])
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123 chunk_list.append(long_sequence[steps * chunk_size:len(long_sequence)])
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124 return chunk_list
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125
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126
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127 def target_multifasta_kmerizer(multifasta, k, kmerDict):
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128 forward_length = 300 #if find the target, put forward 300 bases
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129 reverse_length = 2200 #if find the target, put backward 2200 bases
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130 chunk_size = 60 #it will firstly chunk the single long sequence to multiple smaller sequences, it controls the size of those smaller sequences
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131 target_mers = []
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132 long_single_string = multifasta_single_string(multifasta)
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133 multifasta_list = chunk_a_long_sequence(long_single_string, chunk_size)
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134 unit_length = len(multifasta_list[0])
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135 forward_lines = int(forward_length / unit_length) + 1
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136 reverse_lines = int(forward_length / unit_length) + 1
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137 start_num = 0
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138 end_num = 0
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139 for i in range(len(multifasta_list)):
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140 if i not in range(start_num, end_num): #avoid computational repetition
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141 line = multifasta_list[i]
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142 start = int((len(line) - k) // 2)
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143 s1 = line[start:k + start]
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144 if s1 in kmerDict: #detect it is a potential read or not (use the middle part)
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145 if i - forward_lines >= 0:
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146 start_num = i - forward_lines
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147 else:
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148 start_num = 0
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149 if i + reverse_lines <= len(multifasta_list) - 1:
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150 end_num = i + reverse_lines
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151 else:
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152 end_num = len(multifasta_list) - 1
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153 target_list = [
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154 x.strip() for x in multifasta_list[start_num:end_num]
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155 ]
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156 target_line = "".join(target_list)
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157 target_mers += [
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158 k1 for k1 in createKmerDict_reads([str(target_line)], k)
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159 ] ##changed k to k1, just want to avoid the mixes of this "k" (kmer) to the "k" above (kmer length)
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160 else:
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161 pass
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162 return set(target_mers)
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163
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164
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165 def target_read_kmerizer(file, k, kmerDict):
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166 i = 1
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167 n_reads = 0
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168 total_coverage = 0
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169 target_mers = []
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170 if file.endswith(".gz"):
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171 file_content = io.BufferedReader(gzip.open(file))
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172 else:
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173 file_content = open(file, "r").readlines()
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174 for line in file_content:
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175 start = int((len(line) - k) // 2)
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176 if i % 4 == 2:
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177 if file.endswith(".gz"):
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178 s1 = line[start:k + start].decode()
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179 line = line.decode()
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180 else:
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181 s1 = line[start:k + start]
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182 if s1 in kmerDict: #detect it is a potential read or not (use the middle part)
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183 n_reads += 1
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184 total_coverage += len(line)
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185 target_mers += [
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186 k1 for k1 in createKmerDict_reads([str(line)], k)
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187 ] #changed k to k1, just want to avoid the mixes of this "k" (kmer) to the "k" above (kmer length)
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188 i += 1
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189 if total_coverage >= 4000000:
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190 break
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191 return set(target_mers)
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192
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193
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194 def minion_fasta_kmerizer(file, k, kmerDict):
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195 i = 1
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196 n_reads = 0
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197 total_coverage = 0
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198 target_mers = {}
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199 for line in open(file):
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200 if i % 2 == 0:
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201 for kmer, rc_kmer in kmers(line.strip().upper(), k):
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202 if (kmer in kmerDict) or (rc_kmer in kmerDict):
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203 if kmer in target_mers:
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204 target_mers[kmer] += 1
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205 else:
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206 target_mers[kmer] = 1
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207 if rc_kmer in target_mers:
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208 target_mers[rc_kmer] += 1
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209 else:
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210 target_mers[rc_kmer] = 1
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211 i += 1
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212 return set([h for h in target_mers])
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213
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214
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215 def minion_fastq_kmerizer(file, k, kmerDict):
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216 i = 1
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217 n_reads = 0
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218 total_coverage = 0
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219 target_mers = {}
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220 for line in open(file):
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221 if i % 4 == 2:
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222 for kmer, rc_kmer in kmers(line.strip().upper(), k):
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223 if (kmer in kmerDict) or (rc_kmer in kmerDict):
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224 if kmer in target_mers:
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225 target_mers[kmer] += 1
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226 else:
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227 target_mers[kmer] = 1
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228 if rc_kmer in target_mers:
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229 target_mers[rc_kmer] += 1
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230 else:
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231 target_mers[rc_kmer] = 1
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232 i += 1
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233 return set([h for h in target_mers])
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234
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235
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236 def multifasta_single_string2(multifasta):
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237 single_string = ''
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238 with open(multifasta, 'r') as f:
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239 for line in f:
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240 if line.strip()[0] == '>':
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241 pass
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242 else:
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243 single_string += line.strip()
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244 return single_string
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245
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246
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247 def kmers(seq, k):
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248 rev_comp = reverse_complement(seq)
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249 for start in range(1, len(seq) - k + 1):
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250 yield seq[start:start + k], rev_comp[-(start + k):-start]
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251
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252
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253 def multifasta_to_kmers_dict(multifasta,k_size):#used to create database kmer set
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254 multi_seq_dict = multifasta_dict(multifasta)
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255 lib_dict = {}
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256 for h in multi_seq_dict:
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257 lib_dict[h] = set(
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258 [k for k in createKmerDict_reads([multi_seq_dict[h]], k_size)])
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259 return lib_dict
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260
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261
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262 def Combine(b, c):
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263 fliC_combinations = []
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264 fliC_combinations.append(",".join(c))
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265 temp_combinations = []
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266 for i in range(len(b)):
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267 for x in itertools.combinations(b, i + 1):
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268 temp_combinations.append(",".join(x))
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269 for x in temp_combinations:
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270 temp = []
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271 for y in c:
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272 temp.append(y)
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273 temp.append(x)
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274 temp = ",".join(temp)
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275 temp = temp.split(",")
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276 temp.sort()
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277 temp = ",".join(temp)
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278 fliC_combinations.append(temp)
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279 return fliC_combinations
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280
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281
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282 def seqsero_from_formula_to_serotypes(Otype, fliC, fljB, special_gene_list,subspecies):
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283 #like test_output_06012017.txt
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284 #can add more varialbles like sdf-type, sub-species-type in future (we can conclude it into a special-gene-list)
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285 from Initial_Conditions import phase1,phase2,phaseO,sero,subs,remove_list,rename_dict
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286 rename_dict_not_anymore=[rename_dict[x] for x in rename_dict]
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287 rename_dict_all=rename_dict_not_anymore+list(rename_dict) #used for decide whether to
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288 seronames = []
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289 seronames_none_subspecies=[]
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290 for i in range(len(phase1)):
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291 fliC_combine = []
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292 fljB_combine = []
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293 if phaseO[i] == Otype: # no VII in KW, but it's there
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294 ### for fliC, detect every possible combinations to avoid the effect of "["
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295 if phase1[i].count("[") == 0:
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296 fliC_combine.append(phase1[i])
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297 elif phase1[i].count("[") >= 1:
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298 c = []
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299 b = []
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300 if phase1[i][0] == "[" and phase1[i][-1] == "]" and phase1[i].count(
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301 "[") == 1:
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302 content = phase1[i].replace("[", "").replace("]", "")
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303 fliC_combine.append(content)
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304 fliC_combine.append("-")
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305 else:
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306 for x in phase1[i].split(","):
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307 if "[" in x:
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308 b.append(x.replace("[", "").replace("]", ""))
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309 else:
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310 c.append(x)
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311 fliC_combine = Combine(
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312 b, c
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313 ) #Combine will offer every possible combinations of the formula, like f,[g],t: f,t f,g,t
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314 ### end of fliC "[" detect
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315 ### for fljB, detect every possible combinations to avoid the effect of "["
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316 if phase2[i].count("[") == 0:
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317 fljB_combine.append(phase2[i])
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318 elif phase2[i].count("[") >= 1:
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319 d = []
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320 e = []
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321 if phase2[i][0] == "[" and phase2[i][-1] == "]" and phase2[i].count(
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322 "[") == 1:
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323 content = phase2[i].replace("[", "").replace("]", "")
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324 fljB_combine.append(content)
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325 fljB_combine.append("-")
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326 else:
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327 for x in phase2[i].split(","):
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328 if "[" in x:
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329 d.append(x.replace("[", "").replace("]", ""))
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330 else:
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331 e.append(x)
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332 fljB_combine = Combine(d, e)
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333 ### end of fljB "[" detect
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334 new_fliC = fliC.split(
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335 ","
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336 ) #because some antigen like r,[i] not follow alphabetical order, so use this one to judge and can avoid missings
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337 new_fliC.sort()
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338 new_fliC = ",".join(new_fliC)
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339 new_fljB = fljB.split(",")
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340 new_fljB.sort()
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341 new_fljB = ",".join(new_fljB)
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342 if (new_fliC in fliC_combine
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343 or fliC in fliC_combine) and (new_fljB in fljB_combine
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344 or fljB in fljB_combine):
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345 ######start, remove_list,rename_dict, added on 11/11/2018
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346 if sero[i] not in remove_list:
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347 temp_sero=sero[i]
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348 if temp_sero in rename_dict:
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349 temp_sero=rename_dict[temp_sero] #rename if in the rename list
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350 if temp_sero not in seronames:#the new sero may already included, if yes, then not consider
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351 if subs[i] == subspecies:
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352 seronames.append(temp_sero)
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353 seronames_none_subspecies.append(temp_sero)
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354 else:
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355 pass
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356 else:
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357 pass
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358 ######end, added on 11/11/2018
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359 #analyze seronames
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360 subspecies_pointer=""
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361 if len(seronames) == 0 and len(seronames_none_subspecies)!=0:
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362 # ed_SL_12182019: modified to fix the subspecies output problem
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363 #seronames=seronames_none_subspecies
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364 seronames=["N/A"]
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365 #subspecies_pointer="1"
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366 subspecies_pointer="0"
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367 if len(seronames) == 0:
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368 seronames = [
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369 "N/A (The predicted antigenic profile does not exist in the White-Kauffmann-Le Minor scheme)"
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370 ]
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371 star = ""
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372 star_line = ""
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373 if len(seronames) > 1: #there are two possible predictions for serotypes
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374 star = "*"
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375 #changed 04072019
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diff changeset
376 #star_line = "The predicted serotypes share the same general formula:\t" + Otype + ":" + fliC + ":" + fljB + "\n"
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diff changeset
377 if subspecies_pointer=="1" and len(seronames_none_subspecies)!=0:
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diff changeset
378 star="*"
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379 star_line="The predicted O and H antigens correspond to serotype '"+(" or ").join(seronames)+"' in the Kauffmann-White scheme. The predicted subspecies by SalmID (github.com/hcdenbakker/SalmID) may not be consistent with subspecies designation in the Kauffmann-White scheme. " + star_line
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cstrittmatter
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diff changeset
380 #star_line="The formula with this subspieces prediction can't get a serotype in KW manual, and the serotyping prediction was made without considering it."+star_line
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cstrittmatter
parents:
diff changeset
381 if Otype=="":
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cstrittmatter
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diff changeset
382 Otype="-"
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diff changeset
383 predict_form = Otype + ":" + fliC + ":" + fljB
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cstrittmatter
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diff changeset
384 predict_sero = (" or ").join(seronames)
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cstrittmatter
parents:
diff changeset
385 ###special test for Enteritidis
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cstrittmatter
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diff changeset
386 if predict_form == "9:g,m:-":
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diff changeset
387 sdf = "-"
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diff changeset
388 for x in special_gene_list:
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diff changeset
389 if x.startswith("sdf"):
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diff changeset
390 sdf = "+"
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391 #star_line="Detected sdf gene, a marker to differentiate Gallinarum and Enteritidis"
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cstrittmatter
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392 star_line="sdf gene detected. "
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cstrittmatter
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393 #predict_form = predict_form + " Sdf prediction:" + sdf
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394 predict_form = predict_form #changed 04072019
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cstrittmatter
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diff changeset
395 if sdf == "-":
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diff changeset
396 star = "*"
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397 #star_line="Didn't detected sdf gene, a marker to differentiate Gallinarum and Enteritidis"
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cstrittmatter
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398 star_line="sdf gene not detected. "
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cstrittmatter
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diff changeset
399 #changed in 04072019, for new output
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cstrittmatter
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400 #star_line = "Additional characterization is necessary to assign a serotype to this strain. Commonly circulating strains of serotype Enteritidis are sdf+, although sdf- strains of serotype Enteritidis are known to exist. Serotype Gallinarum is typically sdf- but should be quite rare. Sdf- strains of serotype Enteritidis and serotype Gallinarum can be differentiated by phenotypic profile or genetic criteria.\n"
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401 #predict_sero = "Gallinarum/Enteritidis" #04132019, for new output requirement
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402 predict_sero = "Gallinarum or Enteritidis"
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403 ###end of special test for Enteritidis
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404 elif predict_form == "4:i:-":
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405 predict_sero = "I 4,[5],12:i:-" # change serotype name
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406 elif predict_form == "4:r:-":
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407 predict_sero = "N/A (4:r:-)"
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408 elif predict_form == "4:b:-":
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409 predict_sero = "N/A (4:b:-)"
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410 #elif predict_form == "8:e,h:1,2": #removed after official merge of newport and bardo
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411 #predict_sero = "Newport"
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412 #star = "*"
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413 #star_line = "Serotype Bardo shares the same antigenic profile with Newport, but Bardo is exceedingly rare."
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414 claim = "The serotype(s) is/are the only serotype(s) with the indicated antigenic profile currently recognized in the Kauffmann White Scheme. New serotypes can emerge and the possibility exists that this antigenic profile may emerge in a different subspecies. Identification of strains to the subspecies level should accompany serotype determination; the same antigenic profile in different subspecies is considered different serotypes.\n"
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415 if "N/A" in predict_sero:
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416 claim = ""
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417 #special test for Typhimurium
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418 if "Typhimurium" in predict_sero or predict_form == "4:i:-":
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419 normal = 0
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420 mutation = 0
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421 for x in special_gene_list:
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422 if "oafA-O-4_full" in x:
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423 normal = float(special_gene_list[x])
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424 elif "oafA-O-4_5-" in x:
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425 mutation = float(special_gene_list[x])
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426 if normal > mutation:
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427 pass
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428 elif normal < mutation:
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429 #predict_sero = predict_sero.strip() + "(O5-)"
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430 predict_sero = predict_sero.strip() #diable special sero for new output requirement, 04132019
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431 star = "*"
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432 #star_line = "Detected the deletion of O5-."
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433 star_line = "Detected a deletion that causes O5- variant of Typhimurium. "
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diff changeset
434 else:
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435 pass
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cstrittmatter
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diff changeset
436 #special test for Paratyphi B
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437 if "Paratyphi B" in predict_sero or predict_form == "4:b:-":
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438 normal = 0
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439 mutation = 0
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440 for x in special_gene_list:
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441 if "gntR-family-regulatory-protein_dt-positive" in x:
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442 normal = float(special_gene_list[x])
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443 elif "gntR-family-regulatory-protein_dt-negative" in x:
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444 mutation = float(special_gene_list[x])
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445 #print(normal,mutation)
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446 if normal > mutation:
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447 #predict_sero = predict_sero.strip() + "(dt+)" #diable special sero for new output requirement, 04132019
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448 predict_sero = predict_sero.strip()+' var. L(+) tartrate+' if "Paratyphi B" in predict_sero else predict_sero.strip()
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449 star = "*"
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450 #star_line = "Didn't detect the SNP for dt- which means this isolate is a Paratyphi B variant L(+) tartrate(+)."
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451 star_line = "The SNP that causes d-Tartrate nonfermentating phenotype of Paratyphi B was not detected. "
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452 elif normal < mutation:
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453 #predict_sero = predict_sero.strip() + "(dt-)" #diable special sero for new output requirement, 04132019
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454 predict_sero = predict_sero.strip()
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diff changeset
455 star = "*"
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456 #star_line = "Detected the SNP for dt- which means this isolate is a systemic pathovar of Paratyphi B."
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cstrittmatter
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457 star_line = "Detected the SNP for d-Tartrate nonfermenting phenotype of Paratyphi B. "
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diff changeset
458 else:
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459 star = "*"
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460 #star_line = " Failed to detect the SNP for dt-, can't decide it's a Paratyphi B variant L(+) tartrate(+) or not."
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461 star_line = " " ## ed_SL_05152019: do not report this situation.
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462 #special test for O13,22 and O13,23
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463 if Otype=="13":
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464 #ex_dir = os.path.dirname(os.path.realpath(__file__))
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465 ex_dir = os.path.abspath(os.path.join(os.path.dirname(os.path.dirname(__file__)),'seqsero2_db')) # ed_SL_09152019
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466 f = open(ex_dir + '/special.pickle', 'rb')
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467 special = pickle.load(f)
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468 O22_O23=special['O22_O23']
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cstrittmatter
parents:
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469 if predict_sero.split(" or ")[0] in O22_O23[-1] and predict_sero.split(" or ")[0] not in rename_dict_all:#if in rename_dict_all, then it means already merged, no need to analyze
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470 O22_score=0
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471 O23_score=0
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472 for x in special_gene_list:
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473 if "O:22" in x:
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474 O22_score = O22_score+float(special_gene_list[x])
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475 elif "O:23" in x:
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476 O23_score = O23_score+float(special_gene_list[x])
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cstrittmatter
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477 #print(O22_score,O23_score)
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parents:
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478 for z in O22_O23[0]:
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479 if predict_sero.split(" or ")[0] in z:
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diff changeset
480 if O22_score > O23_score:
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481 star = "*"
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cstrittmatter
parents:
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482 #star_line = "Detected O22 specific genes to further differenciate '"+predict_sero+"'." #diabled for new output requirement, 04132019
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483 predict_sero = z[0]
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484 elif O22_score < O23_score:
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cstrittmatter
parents:
diff changeset
485 star = "*"
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parents:
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486 #star_line = "Detected O23 specific genes to further differenciate '"+predict_sero+"'." #diabled for new output requirement, 04132019
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487 predict_sero = z[1]
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488 else:
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parents:
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489 star = "*"
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490 #star_line = "Fail to detect O22 and O23 differences." #diabled for new output requirement, 04132019
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cstrittmatter
parents:
diff changeset
491 if " or " in predict_sero:
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492 star_line = star_line + "The predicted serotypes share the same general formula: " + Otype + ":" + fliC + ":" + fljB + "."
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493 #special test for O6,8
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494 #merge_O68_list=["Blockley","Bovismorbificans","Hadar","Litchfield","Manhattan","Muenchen"] #remove 11/11/2018, because already in merge list
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diff changeset
495 #for x in merge_O68_list:
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diff changeset
496 # if x in predict_sero:
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497 # predict_sero=x
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498 # star=""
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499 # star_line=""
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diff changeset
500 #special test for Montevideo; most of them are monophasic
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diff changeset
501 #if "Montevideo" in predict_sero and "1,2,7" in predict_form: #remove 11/11/2018, because already in merge list
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502 #star="*"
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503 #star_line="Montevideo is almost always monophasic, having an antigen called for the fljB position may be a result of Salmonella-Salmonella contamination."
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504 return predict_form, predict_sero, star, star_line, claim
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505 ### End of SeqSero Kmer part
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506
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507 ### Begin of SeqSero2 allele prediction and output
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508 def xml_parse_score_comparision_seqsero(xmlfile):
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509 #used to do seqsero xml analysis
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510 from Bio.Blast import NCBIXML
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511 handle=open(xmlfile)
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512 handle=NCBIXML.parse(handle)
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513 handle=list(handle)
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514 List=[]
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515 List_score=[]
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516 List_ids=[]
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517 List_query_region=[]
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518 for i in range(len(handle)):
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519 if len(handle[i].alignments)>0:
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520 for j in range(len(handle[i].alignments)):
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521 score=0
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522 ids=0
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523 cover_region=set() #fixed problem that repeated calculation leading percentage > 1
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524 List.append(handle[i].query.strip()+"___"+handle[i].alignments[j].hit_def)
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525 for z in range(len(handle[i].alignments[j].hsps)):
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526 hsp=handle[i].alignments[j].hsps[z]
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527 temp=set(range(hsp.query_start,hsp.query_end))
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528 if len(cover_region)==0:
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529 cover_region=cover_region|temp
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530 fraction=1
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531 else:
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532 fraction=1-len(cover_region&temp)/float(len(temp))
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533 cover_region=cover_region|temp
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534 if "last" in handle[i].query or "first" in handle[i].query:
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535 score+=hsp.bits*fraction
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536 ids+=float(hsp.identities)/handle[i].query_length*fraction
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537 else:
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538 score+=hsp.bits*fraction
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539 ids+=float(hsp.identities)/handle[i].query_length*fraction
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540 List_score.append(score)
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541 List_ids.append(ids)
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542 List_query_region.append(cover_region)
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543 temp=zip(List,List_score,List_ids,List_query_region)
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544 Final_list=sorted(temp, key=lambda d:d[1], reverse = True)
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545 return Final_list
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546
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547
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548 def Uniq(L,sort_on_fre="none"): #return the uniq list and the count number
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549 Old=L
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550 L.sort()
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551 L = [L[i] for i in range(len(L)) if L[i] not in L[:i]]
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552 count=[]
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553 for j in range(len(L)):
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554 y=0
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555 for x in Old:
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556 if L[j]==x:
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557 y+=1
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558 count.append(y)
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559 if sort_on_fre!="none":
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560 d=zip(*sorted(zip(count, L)))
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561 L=d[1]
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562 count=d[0]
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563 return (L,count)
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564
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565 def judge_fliC_or_fljB_from_head_tail_for_one_contig(nodes_vs_score_list):
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566 #used to predict it's fliC or fljB for one contig, based on tail and head score, but output the score difference,if it is very small, then not reliable, use blast score for whole contig to test
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diff changeset
567 #this is mainly used for
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568 a=nodes_vs_score_list
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569 fliC_score=0
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570 fljB_score=0
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571 for z in a:
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572 if "fliC" in z[0]:
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573 fliC_score+=z[1]
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574 elif "fljB" in z[0]:
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575 fljB_score+=z[1]
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576 if fliC_score>=fljB_score:
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577 role="fliC"
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578 else:
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579 role="fljB"
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580 return (role,abs(fliC_score-fljB_score))
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581
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582 def judge_fliC_or_fljB_from_whole_contig_blast_score_ranking(node_name,Final_list,Final_list_passed):
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diff changeset
583 #used to predict contig is fliC or fljB, if the differnce score value on above head_and_tail is less than 10 (quite small)
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584 #also used when no head or tail got blasted score for the contig
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diff changeset
585 role=""
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586 for z in Final_list_passed:
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587 if node_name in z[0]:
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588 role=z[0].split("_")[0]
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589 break
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590 return role
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591
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592 def fliC_or_fljB_judge_from_head_tail_sequence(nodes_list,tail_head_list,Final_list,Final_list_passed):
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593 #nodes_list is the c created by c,d=Uniq(nodes) in below function
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594 first_target=""
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595 role_list=[]
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596 for x in nodes_list:
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597 a=[]
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598 role=""
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599 for y in tail_head_list:
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600 if x in y[0]:
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601 a.append(y)
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602 if len(a)==4:
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603 role,diff=judge_fliC_or_fljB_from_head_tail_for_one_contig(a)
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604 if diff<20:
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605 role=judge_fliC_or_fljB_from_whole_contig_blast_score_ranking(x,Final_list,Final_list_passed)
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606 elif len(a)==3:
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607 ###however, if the one with highest score is the fewer one, compare their accumulation score
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608 role,diff=judge_fliC_or_fljB_from_head_tail_for_one_contig(a)
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609 if diff<20:
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610 role=judge_fliC_or_fljB_from_whole_contig_blast_score_ranking(x,Final_list,Final_list_passed)
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611 ###end of above score comparison
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612 elif len(a)==2:
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613 #must on same node, if not, then decide with unit blast score, blast-score/length_of_special_sequence(30 or 37)
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diff changeset
614 temp=[]
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cstrittmatter
parents:
diff changeset
615 for z in a:
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parents:
diff changeset
616 temp.append(z[0].split("_")[0])
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diff changeset
617 m,n=Uniq(temp)#should only have one choice, but weird situation might occur too
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cstrittmatter
parents:
diff changeset
618 if len(m)==1:
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cstrittmatter
parents:
diff changeset
619 pass
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cstrittmatter
parents:
diff changeset
620 else:
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cstrittmatter
parents:
diff changeset
621 pass
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cstrittmatter
parents:
diff changeset
622 role,diff=judge_fliC_or_fljB_from_head_tail_for_one_contig(a)
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cstrittmatter
parents:
diff changeset
623 if diff<20:
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cstrittmatter
parents:
diff changeset
624 role=judge_fliC_or_fljB_from_whole_contig_blast_score_ranking(x,Final_list,Final_list_passed)
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cstrittmatter
parents:
diff changeset
625 ###need to desgin a algorithm to guess most possible situation for nodes_list, See the situations of test evaluation
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cstrittmatter
parents:
diff changeset
626 elif len(a)==1:
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cstrittmatter
parents:
diff changeset
627 #that one
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cstrittmatter
parents:
diff changeset
628 role,diff=judge_fliC_or_fljB_from_head_tail_for_one_contig(a)
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cstrittmatter
parents:
diff changeset
629 if diff<20:
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cstrittmatter
parents:
diff changeset
630 role=judge_fliC_or_fljB_from_whole_contig_blast_score_ranking(x,Final_list,Final_list_passed)
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cstrittmatter
parents:
diff changeset
631 #need to evaluate, in future, may set up a cut-off, if not met, then just find Final_list_passed best match,like when "a==0"
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diff changeset
632 else:#a==0
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cstrittmatter
parents:
diff changeset
633 #use Final_list_passed best match
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cstrittmatter
parents:
diff changeset
634 for z in Final_list_passed:
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cstrittmatter
parents:
diff changeset
635 if x in z[0]:
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cstrittmatter
parents:
diff changeset
636 role=z[0].split("_")[0]
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cstrittmatter
parents:
diff changeset
637 break
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cstrittmatter
parents:
diff changeset
638 #print x,role,len(a)
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parents:
diff changeset
639 role_list.append((role,x))
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parents:
diff changeset
640 if len(role_list)==2:
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parents:
diff changeset
641 if role_list[0][0]==role_list[1][0]:#this is the most cocmmon error, two antigen were assigned to same phase
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cstrittmatter
parents:
diff changeset
642 #just use score to do a final test
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diff changeset
643 role_list=[]
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cstrittmatter
parents:
diff changeset
644 for x in nodes_list:
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cstrittmatter
parents:
diff changeset
645 role=judge_fliC_or_fljB_from_whole_contig_blast_score_ranking(x,Final_list,Final_list_passed)
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diff changeset
646 role_list.append((role,x))
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diff changeset
647 return role_list
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648
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diff changeset
649 def decide_contig_roles_for_H_antigen(Final_list,Final_list_passed):
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cstrittmatter
parents:
diff changeset
650 #used to decide which contig is FliC and which one is fljB
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parents:
diff changeset
651 contigs=[]
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diff changeset
652 nodes=[]
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cstrittmatter
parents:
diff changeset
653 for x in Final_list_passed:
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cstrittmatter
parents:
diff changeset
654 if x[0].startswith("fl") and "last" not in x[0] and "first" not in x[0]:
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cstrittmatter
parents:
diff changeset
655 nodes.append(x[0].split("___")[1].strip())
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diff changeset
656 c,d=Uniq(nodes)#c is node_list
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diff changeset
657 #print c
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diff changeset
658 tail_head_list=[x for x in Final_list if ("last" in x[0] or "first" in x[0])]
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cstrittmatter
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diff changeset
659 roles=fliC_or_fljB_judge_from_head_tail_sequence(c,tail_head_list,Final_list,Final_list_passed)
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cstrittmatter
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diff changeset
660 return roles
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diff changeset
661
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diff changeset
662 def decide_O_type_and_get_special_genes(Final_list,Final_list_passed):
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diff changeset
663 #decide O based on Final_list
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diff changeset
664 O_choice="?"
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cstrittmatter
parents:
diff changeset
665 O_list=[]
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diff changeset
666 special_genes={}
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cstrittmatter
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diff changeset
667 nodes=[]
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parents:
diff changeset
668 for x in Final_list_passed:
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cstrittmatter
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diff changeset
669 if x[0].startswith("O-"):
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cstrittmatter
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diff changeset
670 nodes.append(x[0].split("___")[1].strip())
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diff changeset
671 elif not x[0].startswith("fl"):
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diff changeset
672 special_genes[x[0]]=x[2]#08172018, x[2] changed from x[-1]
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diff changeset
673 #print "special_genes:",special_genes
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674 c,d=Uniq(nodes)
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675 #print "potential O antigen contig",c
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diff changeset
676 final_O=[]
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diff changeset
677 O_nodes_list=[]
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diff changeset
678 for x in c:#c is the list for contigs
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diff changeset
679 temp=0
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diff changeset
680 for y in Final_list_passed:
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diff changeset
681 if x in y[0] and y[0].startswith("O-"):
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diff changeset
682 final_O.append(y)
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diff changeset
683 break
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diff changeset
684 ### O contig has the problem of two genes on same contig, so do additional test
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diff changeset
685 potenial_new_gene=""
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diff changeset
686 for x in final_O:
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diff changeset
687 pointer=0 #for genes merged or not
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diff changeset
688 #not consider O-1,3,19_not_in_3,10, too short compared with others
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cstrittmatter
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diff changeset
689 if "O-1,3,19_not_in_3,10" not in x[0] and int(x[0].split("__")[1].split("___")[0])*x[2]+850 <= int(x[0].split("length_")[1].split("_")[0]):#gene length << contig length; for now give 300*2 (for secureity can use 400*2) as flank region
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diff changeset
690 pointer=x[0].split("___")[1].strip()#store the contig name
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diff changeset
691 print(pointer)
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diff changeset
692 if pointer!=0:#it has potential merge event
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cstrittmatter
parents:
diff changeset
693 for y in Final_list:
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cstrittmatter
parents:
diff changeset
694 if pointer in y[0] and y not in final_O and (y[1]>=int(y[0].split("__")[1].split("___")[0])*1.5 or (y[1]>=int(y[0].split("__")[1].split("___")[0])*y[2] and y[1]>=400)):#that's a realtively strict filter now; if passed, it has merge event and add one more to final_O
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diff changeset
695 potenial_new_gene=y
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diff changeset
696 #print(potenial_new_gene)
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diff changeset
697 break
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parents:
diff changeset
698 if potenial_new_gene!="":
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diff changeset
699 print("two differnt genes in same contig, fix it for O antigen")
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parents:
diff changeset
700 print(potenial_new_gene[:3])
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parents:
diff changeset
701 pointer=0
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parents:
diff changeset
702 for y in final_O:
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parents:
diff changeset
703 if y[0].split("___")[-1]==potenial_new_gene[0].split("___")[-1]:
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cstrittmatter
parents:
diff changeset
704 pointer=1
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parents:
diff changeset
705 if pointer!=0: #changed to consider two genes in same contig
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cstrittmatter
parents:
diff changeset
706 final_O.append(potenial_new_gene)
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cstrittmatter
parents:
diff changeset
707 ### end of the two genes on same contig test
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diff changeset
708 final_O=sorted(final_O,key=lambda x: x[2], reverse=True)#sorted
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cstrittmatter
parents:
diff changeset
709 if len(final_O)==0 or (len(final_O)==1 and "O-1,3,19_not_in_3,10" in final_O[0][0]):
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cstrittmatter
parents:
diff changeset
710 #print "$$$No Otype, due to no hit"#may need to be changed
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cstrittmatter
parents:
diff changeset
711 O_choice="-"
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diff changeset
712 else:
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parents:
diff changeset
713 highest_O_coverage=max([float(x[0].split("_cov_")[-1].split("_")[0]) for x in final_O if "O-1,3,19_not_in_3,10" not in x[0]])
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cstrittmatter
parents:
diff changeset
714 O_list=[]
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cstrittmatter
parents:
diff changeset
715 O_list_less_contamination=[]
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cstrittmatter
parents:
diff changeset
716 for x in final_O:
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cstrittmatter
parents:
diff changeset
717 if not "O-1,3,19_not_in_3,10__130" in x[0]:#O-1,3,19_not_in_3,10 is too small, which may affect further analysis; to avoid contamination affect, use 0.15 of highest coverage as cut-off
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cstrittmatter
parents:
diff changeset
718 O_list.append(x[0].split("__")[0])
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cstrittmatter
parents:
diff changeset
719 O_nodes_list.append(x[0].split("___")[1])
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cstrittmatter
parents:
diff changeset
720 if float(x[0].split("_cov_")[-1].split("_")[0])>highest_O_coverage*0.15:
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cstrittmatter
parents:
diff changeset
721 O_list_less_contamination.append(x[0].split("__")[0])
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cstrittmatter
parents:
diff changeset
722 ### special test for O9,46 and O3,10 family
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cstrittmatter
parents:
diff changeset
723 if ("O-9,46_wbaV" in O_list or "O-9,46_wbaV-from-II-9,12:z29:1,5-SRR1346254" in O_list) and O_list_less_contamination[0].startswith("O-9,"):#not sure should use and float(O9_wbaV)/float(num_1) > 0.1
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cstrittmatter
parents:
diff changeset
724 if "O-9,46_wzy" in O_list or "O-9,46_wzy_partial" in O_list:#and float(O946_wzy)/float(num_1) > 0.1
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cstrittmatter
parents:
diff changeset
725 O_choice="O-9,46"
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cstrittmatter
parents:
diff changeset
726 #print "$$$Most possilble Otype: O-9,46"
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cstrittmatter
parents:
diff changeset
727 elif "O-9,46,27_partial_wzy" in O_list:#and float(O94627)/float(num_1) > 0.1
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cstrittmatter
parents:
diff changeset
728 O_choice="O-9,46,27"
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cstrittmatter
parents:
diff changeset
729 #print "$$$Most possilble Otype: O-9,46,27"
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cstrittmatter
parents:
diff changeset
730 else:
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cstrittmatter
parents:
diff changeset
731 O_choice="O-9"#next, detect O9 vs O2?
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cstrittmatter
parents:
diff changeset
732 O2=0
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cstrittmatter
parents:
diff changeset
733 O9=0
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cstrittmatter
parents:
diff changeset
734 for z in special_genes:
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cstrittmatter
parents:
diff changeset
735 if "tyr-O-9" in z:
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cstrittmatter
parents:
diff changeset
736 O9=special_genes[z]
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cstrittmatter
parents:
diff changeset
737 elif "tyr-O-2" in z:
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cstrittmatter
parents:
diff changeset
738 O2=special_genes[z]
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cstrittmatter
parents:
diff changeset
739 if O2>O9:
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cstrittmatter
parents:
diff changeset
740 O_choice="O-2"
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cstrittmatter
parents:
diff changeset
741 elif O2<O9:
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cstrittmatter
parents:
diff changeset
742 pass
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cstrittmatter
parents:
diff changeset
743 else:
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cstrittmatter
parents:
diff changeset
744 pass
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cstrittmatter
parents:
diff changeset
745 #print "$$$No suitable one, because can't distinct it's O-9 or O-2, but O-9 has a more possibility."
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cstrittmatter
parents:
diff changeset
746 elif ("O-3,10_wzx" in O_list) and ("O-9,46_wzy" in O_list) and (O_list[0].startswith("O-3,10") or O_list_less_contamination[0].startswith("O-9,46_wzy")):#and float(O310_wzx)/float(num_1) > 0.1 and float(O946_wzy)/float(num_1) > 0.1
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cstrittmatter
parents:
diff changeset
747 if "O-3,10_not_in_1,3,19" in O_list:#and float(O310_no_1319)/float(num_1) > 0.1
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cstrittmatter
parents:
diff changeset
748 O_choice="O-3,10"
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cstrittmatter
parents:
diff changeset
749 #print "$$$Most possilble Otype: O-3,10 (contain O-3,10_not_in_1,3,19)"
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cstrittmatter
parents:
diff changeset
750 else:
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cstrittmatter
parents:
diff changeset
751 O_choice="O-1,3,19"
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cstrittmatter
parents:
diff changeset
752 #print "$$$Most possilble Otype: O-1,3,19 (not contain O-3,10_not_in_1,3,19)"
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cstrittmatter
parents:
diff changeset
753 ### end of special test for O9,46 and O3,10 family
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cstrittmatter
parents:
diff changeset
754 else:
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cstrittmatter
parents:
diff changeset
755 try:
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cstrittmatter
parents:
diff changeset
756 max_score=0
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cstrittmatter
parents:
diff changeset
757 for x in final_O:
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cstrittmatter
parents:
diff changeset
758 if x[2]>=max_score and float(x[0].split("_cov_")[-1].split("_")[0])>highest_O_coverage*0.15:#use x[2],08172018, the "coverage identity = cover_length * identity"; also meet coverage threshold
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cstrittmatter
parents:
diff changeset
759 max_score=x[2]#change from x[-1] to x[2],08172018
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cstrittmatter
parents:
diff changeset
760 O_choice=x[0].split("_")[0]
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cstrittmatter
parents:
diff changeset
761 if O_choice=="O-1,3,19":
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cstrittmatter
parents:
diff changeset
762 O_choice=final_O[1][0].split("_")[0]
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cstrittmatter
parents:
diff changeset
763 #print "$$$Most possilble Otype: ",O_choice
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cstrittmatter
parents:
diff changeset
764 except:
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cstrittmatter
parents:
diff changeset
765 pass
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cstrittmatter
parents:
diff changeset
766 #print "$$$No suitable Otype, or failure of mapping (please check the quality of raw reads)"
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cstrittmatter
parents:
diff changeset
767 if O_choice=="O-9,46,27" and len(O_list)==2 and "O-4_wzx" in O_list: #special for very low chance sitatuion between O4 and O9,27,46, this is for serotypes like Bredeney and Schwarzengrund (normallly O-4 will have higher score, but sometimes sequencing quality may affect the prediction)
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cstrittmatter
parents:
diff changeset
768 O_choice="O-4"
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cstrittmatter
parents:
diff changeset
769 #print "O:",O_choice,O_nodes_list
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cstrittmatter
parents:
diff changeset
770 Otypes=[]
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cstrittmatter
parents:
diff changeset
771 for x in O_list:
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cstrittmatter
parents:
diff changeset
772 if x!="O-1,3,19_not_in_3,10":
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cstrittmatter
parents:
diff changeset
773 if "O-9,46_" not in x:
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cstrittmatter
parents:
diff changeset
774 Otypes.append(x.split("_")[0])
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cstrittmatter
parents:
diff changeset
775 else:
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cstrittmatter
parents:
diff changeset
776 Otypes.append(x.split("-from")[0])#O-9,46_wbaV-from-II-9,12:z29:1,5-SRR1346254
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cstrittmatter
parents:
diff changeset
777 #Otypes=[x.split("_")[0] for x in O_list if x!="O-1,3,19_not_in_3,10"]
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cstrittmatter
parents:
diff changeset
778 Otypes_uniq,Otypes_fre=Uniq(Otypes)
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cstrittmatter
parents:
diff changeset
779 contamination_O=""
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cstrittmatter
parents:
diff changeset
780 if O_choice=="O-9,46,27" or O_choice=="O-3,10" or O_choice=="O-1,3,19":
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cstrittmatter
parents:
diff changeset
781 if len(Otypes_uniq)>2:
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cstrittmatter
parents:
diff changeset
782 contamination_O="potential contamination from O antigen signals"
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cstrittmatter
parents:
diff changeset
783 else:
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cstrittmatter
parents:
diff changeset
784 if len(Otypes_uniq)>1:
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cstrittmatter
parents:
diff changeset
785 if O_choice=="O-4" and len(Otypes_uniq)==2 and "O-9,46,27" in Otypes_uniq: #for special 4,12,27 case such as Bredeney and Schwarzengrund
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cstrittmatter
parents:
diff changeset
786 contamination_O=""
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cstrittmatter
parents:
diff changeset
787 elif O_choice=="O-9,46" and len(Otypes_uniq)==2 and "O-9,46_wbaV" in Otypes_uniq and "O-9,46_wzy" in Otypes_uniq: #for special 4,12,27 case such as Bredeney and Schwarzengrund
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cstrittmatter
parents:
diff changeset
788 contamination_O=""
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cstrittmatter
parents:
diff changeset
789 else:
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cstrittmatter
parents:
diff changeset
790 contamination_O="potential contamination from O antigen signals"
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cstrittmatter
parents:
diff changeset
791 return O_choice,O_nodes_list,special_genes,final_O,contamination_O,Otypes_uniq
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cstrittmatter
parents:
diff changeset
792 ### End of SeqSero2 allele prediction and output
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cstrittmatter
parents:
diff changeset
793
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cstrittmatter
parents:
diff changeset
794 def get_input_files(make_dir,input_file,data_type,dirpath):
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cstrittmatter
parents:
diff changeset
795 #tell input files from datatype
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cstrittmatter
parents:
diff changeset
796 #"<int>: '1'(pair-end reads, interleaved),'2'(pair-end reads, seperated),'3'(single-end reads), '4'(assembly),'5'(nanopore fasta),'6'(nanopore fastq)"
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cstrittmatter
parents:
diff changeset
797 for_fq=""
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cstrittmatter
parents:
diff changeset
798 rev_fq=""
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cstrittmatter
parents:
diff changeset
799 os.chdir(make_dir)
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cstrittmatter
parents:
diff changeset
800 if data_type=="1":
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cstrittmatter
parents:
diff changeset
801 input_file=input_file[0].split("/")[-1]
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cstrittmatter
parents:
diff changeset
802 if input_file.endswith(".sra"):
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cstrittmatter
parents:
diff changeset
803 subprocess.check_call("fastq-dump --split-files "+input_file,shell=True)
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cstrittmatter
parents:
diff changeset
804 for_fq=input_file.replace(".sra","_1.fastq")
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cstrittmatter
parents:
diff changeset
805 rev_fq=input_file.replace(".sra","_2.fastq")
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cstrittmatter
parents:
diff changeset
806 else:
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cstrittmatter
parents:
diff changeset
807 core_id=input_file.split(".fastq")[0].split(".fq")[0]
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cstrittmatter
parents:
diff changeset
808 for_fq=core_id+"_1.fastq"
e6437d423693 planemo upload commit 70dc513aa7d7ac6785847dfd86323687613b6b68-dirty
cstrittmatter
parents:
diff changeset
809 rev_fq=core_id+"_2.fastq"
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cstrittmatter
parents:
diff changeset
810 if input_file.endswith(".gz"):
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cstrittmatter
parents:
diff changeset
811 subprocess.check_call("gzip -dc "+input_file+" | "+dirpath+"/deinterleave_fastq.sh "+for_fq+" "+rev_fq,shell=True)
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cstrittmatter
parents:
diff changeset
812 else:
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cstrittmatter
parents:
diff changeset
813 subprocess.check_call("cat "+input_file+" | "+dirpath+"/deinterleave_fastq.sh "+for_fq+" "+rev_fq,shell=True)
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cstrittmatter
parents:
diff changeset
814 elif data_type=="2":
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cstrittmatter
parents:
diff changeset
815 for_fq=input_file[0].split("/")[-1]
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cstrittmatter
parents:
diff changeset
816 rev_fq=input_file[1].split("/")[-1]
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cstrittmatter
parents:
diff changeset
817 elif data_type=="3":
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cstrittmatter
parents:
diff changeset
818 input_file=input_file[0].split("/")[-1]
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cstrittmatter
parents:
diff changeset
819 if input_file.endswith(".sra"):
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cstrittmatter
parents:
diff changeset
820 subprocess.check_call("fastq-dump --split-files "+input_file,shell=True)
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cstrittmatter
parents:
diff changeset
821 for_fq=input_file.replace(".sra","_1.fastq")
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cstrittmatter
parents:
diff changeset
822 else:
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cstrittmatter
parents:
diff changeset
823 for_fq=input_file
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cstrittmatter
parents:
diff changeset
824 elif data_type in ["4","5","6"]:
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cstrittmatter
parents:
diff changeset
825 for_fq=input_file[0].split("/")[-1]
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cstrittmatter
parents:
diff changeset
826 os.chdir("..")
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cstrittmatter
parents:
diff changeset
827 return for_fq,rev_fq
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cstrittmatter
parents:
diff changeset
828
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cstrittmatter
parents:
diff changeset
829 def predict_O_and_H_types(Final_list,Final_list_passed,new_fasta):
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cstrittmatter
parents:
diff changeset
830 #get O and H types from Final_list from blast parsing; allele mode
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cstrittmatter
parents:
diff changeset
831 from Bio import SeqIO
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cstrittmatter
parents:
diff changeset
832 fliC_choice="-"
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cstrittmatter
parents:
diff changeset
833 fljB_choice="-"
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cstrittmatter
parents:
diff changeset
834 fliC_contig="NA"
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cstrittmatter
parents:
diff changeset
835 fljB_contig="NA"
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cstrittmatter
parents:
diff changeset
836 fliC_region=set([0])
e6437d423693 planemo upload commit 70dc513aa7d7ac6785847dfd86323687613b6b68-dirty
cstrittmatter
parents:
diff changeset
837 fljB_region=set([0,])
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cstrittmatter
parents:
diff changeset
838 fliC_length=0 #can be changed to coverage in future; in 03292019, changed to ailgned length
e6437d423693 planemo upload commit 70dc513aa7d7ac6785847dfd86323687613b6b68-dirty
cstrittmatter
parents:
diff changeset
839 fljB_length=0 #can be changed to coverage in future; in 03292019, changed to ailgned length
e6437d423693 planemo upload commit 70dc513aa7d7ac6785847dfd86323687613b6b68-dirty
cstrittmatter
parents:
diff changeset
840 O_choice="-"#no need to decide O contig for now, should be only one
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cstrittmatter
parents:
diff changeset
841 O_choice,O_nodes,special_gene_list,O_nodes_roles,contamination_O,Otypes_uniq=decide_O_type_and_get_special_genes(Final_list,Final_list_passed)#decide the O antigen type and also return special-gene-list for further identification
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cstrittmatter
parents:
diff changeset
842 O_choice=O_choice.split("-")[-1].strip()
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cstrittmatter
parents:
diff changeset
843 if (O_choice=="1,3,19" and len(O_nodes_roles)==1 and "1,3,19" in O_nodes_roles[0][0]) or O_choice=="":
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cstrittmatter
parents:
diff changeset
844 O_choice="-"
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cstrittmatter
parents:
diff changeset
845 H_contig_roles=decide_contig_roles_for_H_antigen(Final_list,Final_list_passed)#decide the H antigen contig is fliC or fljB
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cstrittmatter
parents:
diff changeset
846 #add alignment locations, used for further selection, 03312019
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cstrittmatter
parents:
diff changeset
847 for i in range(len(H_contig_roles)):
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cstrittmatter
parents:
diff changeset
848 x=H_contig_roles[i]
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cstrittmatter
parents:
diff changeset
849 for y in Final_list_passed:
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cstrittmatter
parents:
diff changeset
850 if x[1] in y[0] and y[0].startswith(x[0]):
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cstrittmatter
parents:
diff changeset
851 H_contig_roles[i]+=H_contig_roles[i]+(y[-1],)
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cstrittmatter
parents:
diff changeset
852 break
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cstrittmatter
parents:
diff changeset
853 log_file=open("SeqSero_log.txt","a")
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cstrittmatter
parents:
diff changeset
854 extract_file=open("Extracted_antigen_alleles.fasta","a")
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cstrittmatter
parents:
diff changeset
855 handle_fasta=list(SeqIO.parse(new_fasta,"fasta"))
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cstrittmatter
parents:
diff changeset
856
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cstrittmatter
parents:
diff changeset
857 #print("O_contigs:")
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cstrittmatter
parents:
diff changeset
858 log_file.write("O_contigs:\n")
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cstrittmatter
parents:
diff changeset
859 extract_file.write("#Sequences with antigen signals (if the micro-assembled contig only covers the flanking region, it will not be used for contamination analysis)\n")
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cstrittmatter
parents:
diff changeset
860 extract_file.write("#O_contigs:\n")
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cstrittmatter
parents:
diff changeset
861 for x in O_nodes_roles:
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cstrittmatter
parents:
diff changeset
862 if "O-1,3,19_not_in_3,10" not in x[0]:#O-1,3,19_not_in_3,10 is just a small size marker
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cstrittmatter
parents:
diff changeset
863 #print(x[0].split("___")[-1],x[0].split("__")[0],"blast score:",x[1],"identity%:",str(round(x[2]*100,2))+"%",str(min(x[-1]))+" to "+str(max(x[-1])))
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cstrittmatter
parents:
diff changeset
864 log_file.write(x[0].split("___")[-1]+" "+x[0].split("__")[0]+"; "+"blast score: "+str(x[1])+" identity%: "+str(round(x[2]*100,2))+"%; alignment from "+str(min(x[-1]))+" to "+str(max(x[-1]))+" of antigen\n")
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cstrittmatter
parents:
diff changeset
865 title=">"+x[0].split("___")[-1]+" "+x[0].split("__")[0]+"; "+"blast score: "+str(x[1])+" identity%: "+str(round(x[2]*100,2))+"%; alignment from "+str(min(x[-1]))+" to "+str(max(x[-1]))+" of antigen\n"
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cstrittmatter
parents:
diff changeset
866 seqs=""
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cstrittmatter
parents:
diff changeset
867 for z in handle_fasta:
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cstrittmatter
parents:
diff changeset
868 if x[0].split("___")[-1]==z.description:
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cstrittmatter
parents:
diff changeset
869 seqs=str(z.seq)
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cstrittmatter
parents:
diff changeset
870 extract_file.write(title+seqs+"\n")
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cstrittmatter
parents:
diff changeset
871 if len(H_contig_roles)!=0:
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cstrittmatter
parents:
diff changeset
872 highest_H_coverage=max([float(x[1].split("_cov_")[-1].split("_")[0]) for x in H_contig_roles]) #less than highest*0.1 would be regarded as contamination and noises, they will still be considered in contamination detection and logs, but not used as final serotype output
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cstrittmatter
parents:
diff changeset
873 else:
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cstrittmatter
parents:
diff changeset
874 highest_H_coverage=0
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cstrittmatter
parents:
diff changeset
875 for x in H_contig_roles:
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cstrittmatter
parents:
diff changeset
876 #if multiple choices, temporately select the one with longest length for now, will revise in further change
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cstrittmatter
parents:
diff changeset
877 if "fliC" == x[0] and len(x[-1])>=fliC_length and x[1] not in O_nodes and float(x[1].split("_cov_")[-1].split("_")[0])>highest_H_coverage*0.13:#remember to avoid the effect of O-type contig, so should not in O_node list
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cstrittmatter
parents:
diff changeset
878 fliC_contig=x[1]
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cstrittmatter
parents:
diff changeset
879 fliC_length=len(x[-1])
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cstrittmatter
parents:
diff changeset
880 elif "fljB" == x[0] and len(x[-1])>=fljB_length and x[1] not in O_nodes and float(x[1].split("_cov_")[-1].split("_")[0])>highest_H_coverage*0.13:
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cstrittmatter
parents:
diff changeset
881 fljB_contig=x[1]
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cstrittmatter
parents:
diff changeset
882 fljB_length=len(x[-1])
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cstrittmatter
parents:
diff changeset
883 for x in Final_list_passed:
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cstrittmatter
parents:
diff changeset
884 if fliC_choice=="-" and "fliC_" in x[0] and fliC_contig in x[0]:
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cstrittmatter
parents:
diff changeset
885 fliC_choice=x[0].split("_")[1]
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cstrittmatter
parents:
diff changeset
886 elif fljB_choice=="-" and "fljB_" in x[0] and fljB_contig in x[0]:
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cstrittmatter
parents:
diff changeset
887 fljB_choice=x[0].split("_")[1]
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cstrittmatter
parents:
diff changeset
888 elif fliC_choice!="-" and fljB_choice!="-":
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cstrittmatter
parents:
diff changeset
889 break
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cstrittmatter
parents:
diff changeset
890 #now remove contigs not in middle core part
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cstrittmatter
parents:
diff changeset
891 first_allele="NA"
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cstrittmatter
parents:
diff changeset
892 first_allele_percentage=0
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cstrittmatter
parents:
diff changeset
893 for x in Final_list:
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cstrittmatter
parents:
diff changeset
894 if x[0].startswith("fliC") or x[0].startswith("fljB"):
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cstrittmatter
parents:
diff changeset
895 first_allele=x[0].split("__")[0] #used to filter those un-middle contigs
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cstrittmatter
parents:
diff changeset
896 first_allele_percentage=x[2]
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cstrittmatter
parents:
diff changeset
897 break
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cstrittmatter
parents:
diff changeset
898 additional_contigs=[]
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cstrittmatter
parents:
diff changeset
899 for x in Final_list:
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cstrittmatter
parents:
diff changeset
900 if first_allele in x[0]:
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cstrittmatter
parents:
diff changeset
901 if (fliC_contig == x[0].split("___")[-1]):
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cstrittmatter
parents:
diff changeset
902 fliC_region=x[3]
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cstrittmatter
parents:
diff changeset
903 elif fljB_contig!="NA" and (fljB_contig == x[0].split("___")[-1]):
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cstrittmatter
parents:
diff changeset
904 fljB_region=x[3]
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cstrittmatter
parents:
diff changeset
905 else:
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cstrittmatter
parents:
diff changeset
906 if x[1]*1.1>int(x[0].split("___")[1].split("_")[3]):#loose threshold by multiplying 1.1
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cstrittmatter
parents:
diff changeset
907 additional_contigs.append(x)
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cstrittmatter
parents:
diff changeset
908 #else:
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cstrittmatter
parents:
diff changeset
909 #print x[:3]
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cstrittmatter
parents:
diff changeset
910 #we can just use the fljB region (or fliC depends on size), no matter set() or contain a large locations (without middle part); however, if none of them is fully assembled, use 500 and 1200 as conservative cut-off
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cstrittmatter
parents:
diff changeset
911 if first_allele_percentage>0.9:
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cstrittmatter
parents:
diff changeset
912 if len(fliC_region)>len(fljB_region) and (max(fljB_region)-min(fljB_region))>1000:
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cstrittmatter
parents:
diff changeset
913 target_region=fljB_region|(fliC_region-set(range(min(fljB_region),max(fljB_region)))) #fljB_region|(fliC_region-set(range(min(fljB_region),max(fljB_region))))
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cstrittmatter
parents:
diff changeset
914 elif len(fliC_region)<len(fljB_region) and (max(fliC_region)-min(fliC_region))>1000:
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cstrittmatter
parents:
diff changeset
915 target_region=fliC_region|(fljB_region-set(range(min(fliC_region),max(fliC_region)))) #fljB_region|(fliC_region-set(range(min(fljB_region),max(fljB_region))))
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cstrittmatter
parents:
diff changeset
916 else:
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cstrittmatter
parents:
diff changeset
917 target_region=set()#doesn't do anything
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cstrittmatter
parents:
diff changeset
918 else:
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cstrittmatter
parents:
diff changeset
919 target_region=set()#doesn't do anything
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cstrittmatter
parents:
diff changeset
920 #print(target_region)
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cstrittmatter
parents:
diff changeset
921 #print(additional_contigs)
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cstrittmatter
parents:
diff changeset
922 target_region2=set(list(range(0,525))+list(range(1200,1700)))#I found to use 500 to 1200 as special region would be best
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cstrittmatter
parents:
diff changeset
923 target_region=target_region2|target_region
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cstrittmatter
parents:
diff changeset
924 for x in additional_contigs:
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cstrittmatter
parents:
diff changeset
925 removal=0
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cstrittmatter
parents:
diff changeset
926 contig_length=int(x[0].split("___")[1].split("length_")[-1].split("_")[0])
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cstrittmatter
parents:
diff changeset
927 if fljB_contig not in x[0] and fliC_contig not in x[0] and len(target_region&x[3])/float(len(x[3]))>0.65 and contig_length*0.5<len(x[3])<contig_length*1.5: #consider length and alignment length for now, but very loose,0.5 and 1.5 as cut-off
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cstrittmatter
parents:
diff changeset
928 removal=1
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cstrittmatter
parents:
diff changeset
929 else:
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cstrittmatter
parents:
diff changeset
930 if first_allele_percentage > 0.9 and float(x[0].split("__")[1].split("___")[0])*x[2]/len(x[-1])>0.96:#if high similiarity with middle part of first allele (first allele >0.9, already cover middle part)
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cstrittmatter
parents:
diff changeset
931 removal=1
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cstrittmatter
parents:
diff changeset
932 else:
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cstrittmatter
parents:
diff changeset
933 pass
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cstrittmatter
parents:
diff changeset
934 if removal==1:
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cstrittmatter
parents:
diff changeset
935 for y in H_contig_roles:
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cstrittmatter
parents:
diff changeset
936 if y[1] in x[0]:
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cstrittmatter
parents:
diff changeset
937 H_contig_roles.remove(y)
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cstrittmatter
parents:
diff changeset
938 else:
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cstrittmatter
parents:
diff changeset
939 pass
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cstrittmatter
parents:
diff changeset
940 #print(x[:3],contig_length,len(target_region&x[3])/float(len(x[3])),contig_length*0.5,len(x[3]),contig_length*1.5)
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cstrittmatter
parents:
diff changeset
941 #end of removing none-middle contigs
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cstrittmatter
parents:
diff changeset
942 #print("H_contigs:")
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cstrittmatter
parents:
diff changeset
943 log_file.write("H_contigs:\n")
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cstrittmatter
parents:
diff changeset
944 extract_file.write("#H_contigs:\n")
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cstrittmatter
parents:
diff changeset
945 H_contig_stat=[]
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cstrittmatter
parents:
diff changeset
946 H1_cont_stat={}
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cstrittmatter
parents:
diff changeset
947 H2_cont_stat={}
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cstrittmatter
parents:
diff changeset
948 for i in range(len(H_contig_roles)):
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cstrittmatter
parents:
diff changeset
949 x=H_contig_roles[i]
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cstrittmatter
parents:
diff changeset
950 a=0
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cstrittmatter
parents:
diff changeset
951 for y in Final_list_passed:
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cstrittmatter
parents:
diff changeset
952 if x[1] in y[0] and y[0].startswith(x[0]):
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cstrittmatter
parents:
diff changeset
953 if "first" in y[0] or "last" in y[0]: #this is the final filter to decide it's fliC or fljB, if can't pass, then can't decide
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cstrittmatter
parents:
diff changeset
954 for y in Final_list_passed: #it's impossible to has the "first" and "last" allele as prediction, so re-do it
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cstrittmatter
parents:
diff changeset
955 if x[1] in y[0]:#it's very possible to be third phase allele, so no need to make it must be fliC or fljB
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cstrittmatter
parents:
diff changeset
956 #print(x[1],"can't_decide_fliC_or_fljB",y[0].split("_")[1],"blast_score:",y[1],"identity%:",str(round(y[2]*100,2))+"%",str(min(y[-1]))+" to "+str(max(y[-1])))
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cstrittmatter
parents:
diff changeset
957 log_file.write(x[1]+" "+x[0]+" "+y[0].split("_")[1]+"; "+"blast score: "+str(y[1])+" identity%: "+str(round(y[2]*100,2))+"%; alignment from "+str(min(y[-1]))+" to "+str(max(y[-1]))+" of antigen\n")
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cstrittmatter
parents:
diff changeset
958 H_contig_roles[i]="can't decide fliC or fljB, may be third phase"
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cstrittmatter
parents:
diff changeset
959 title=">"+x[1]+" "+x[0]+" "+y[0].split("_")[1]+"; "+"blast score: "+str(y[1])+" identity%: "+str(round(y[2]*100,2))+"%; alignment from "+str(min(y[-1]))+" to "+str(max(y[-1]))+" of antiten\n"
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cstrittmatter
parents:
diff changeset
960 seqs=""
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cstrittmatter
parents:
diff changeset
961 for z in handle_fasta:
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cstrittmatter
parents:
diff changeset
962 if x[1]==z.description:
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cstrittmatter
parents:
diff changeset
963 seqs=str(z.seq)
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cstrittmatter
parents:
diff changeset
964 extract_file.write(title+seqs+"\n")
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cstrittmatter
parents:
diff changeset
965 break
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cstrittmatter
parents:
diff changeset
966 else:
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cstrittmatter
parents:
diff changeset
967 #print(x[1],x[0],y[0].split("_")[1],"blast_score:",y[1],"identity%:",str(round(y[2]*100,2))+"%",str(min(y[-1]))+" to "+str(max(y[-1])))
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cstrittmatter
parents:
diff changeset
968 log_file.write(x[1]+" "+x[0]+" "+y[0].split("_")[1]+"; "+"blast score: "+str(y[1])+" identity%: "+str(round(y[2]*100,2))+"%; alignment from "+str(min(y[-1]))+" to "+str(max(y[-1]))+" of antigen\n")
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cstrittmatter
parents:
diff changeset
969 title=">"+x[1]+" "+x[0]+" "+y[0].split("_")[1]+"; "+"blast score: "+str(y[1])+" identity%: "+str(round(y[2]*100,2))+"%; alignment from "+str(min(y[-1]))+" to "+str(max(y[-1]))+" of antigen\n"
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cstrittmatter
parents:
diff changeset
970 seqs=""
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cstrittmatter
parents:
diff changeset
971 for z in handle_fasta:
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cstrittmatter
parents:
diff changeset
972 if x[1]==z.description:
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cstrittmatter
parents:
diff changeset
973 seqs=str(z.seq)
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cstrittmatter
parents:
diff changeset
974 extract_file.write(title+seqs+"\n")
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cstrittmatter
parents:
diff changeset
975 if x[0]=="fliC":
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cstrittmatter
parents:
diff changeset
976 if y[0].split("_")[1] not in H1_cont_stat:
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cstrittmatter
parents:
diff changeset
977 H1_cont_stat[y[0].split("_")[1]]=y[2]
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cstrittmatter
parents:
diff changeset
978 else:
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cstrittmatter
parents:
diff changeset
979 H1_cont_stat[y[0].split("_")[1]]+=y[2]
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cstrittmatter
parents:
diff changeset
980 if x[0]=="fljB":
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cstrittmatter
parents:
diff changeset
981 if y[0].split("_")[1] not in H2_cont_stat:
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cstrittmatter
parents:
diff changeset
982 H2_cont_stat[y[0].split("_")[1]]=y[2]
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cstrittmatter
parents:
diff changeset
983 else:
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cstrittmatter
parents:
diff changeset
984 H2_cont_stat[y[0].split("_")[1]]+=y[2]
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cstrittmatter
parents:
diff changeset
985 break
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cstrittmatter
parents:
diff changeset
986 #detect contaminations
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cstrittmatter
parents:
diff changeset
987 #print(H1_cont_stat)
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parents:
diff changeset
988 #print(H2_cont_stat)
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parents:
diff changeset
989 H1_cont_stat_list=[x for x in H1_cont_stat if H1_cont_stat[x]>0.2]
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cstrittmatter
parents:
diff changeset
990 H2_cont_stat_list=[x for x in H2_cont_stat if H2_cont_stat[x]>0.2]
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cstrittmatter
parents:
diff changeset
991 contamination_H=""
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diff changeset
992 if len(H1_cont_stat_list)>1 or len(H2_cont_stat_list)>1:
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parents:
diff changeset
993 contamination_H="potential contamination from H antigen signals"
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cstrittmatter
parents:
diff changeset
994 elif len(H2_cont_stat_list)==1 and fljB_contig=="NA":
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cstrittmatter
parents:
diff changeset
995 contamination_H="potential contamination from H antigen signals, uncommon weak fljB signals detected"
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cstrittmatter
parents:
diff changeset
996 #get additional antigens
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diff changeset
997 """
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cstrittmatter
parents:
diff changeset
998 if ("O-9,46_wbaV" in O_list or "O-9,46_wbaV-from-II-9,12:z29:1,5-SRR1346254" in O_list) and O_list_less_contamination[0].startswith("O-9,"):#not sure should use and float(O9_wbaV)/float(num_1) > 0.1
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cstrittmatter
parents:
diff changeset
999 if "O-9,46_wzy" in O_list:#and float(O946_wzy)/float(num_1) > 0.1
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parents:
diff changeset
1000 O_choice="O-9,46"
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parents:
diff changeset
1001 #print "$$$Most possilble Otype: O-9,46"
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parents:
diff changeset
1002 elif "O-9,46,27_partial_wzy" in O_list:#and float(O94627)/float(num_1) > 0.1
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cstrittmatter
parents:
diff changeset
1003 O_choice="O-9,46,27"
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cstrittmatter
parents:
diff changeset
1004 #print "$$$Most possilble Otype: O-9,46,27"
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cstrittmatter
parents:
diff changeset
1005 elif ("O-3,10_wzx" in O_list) and ("O-9,46_wzy" in O_list) and (O_list[0].startswith("O-3,10") or O_list_less_contamination[0].startswith("O-9,46_wzy")):#and float(O310_wzx)/float(num_1) > 0.1 and float(O946_wzy)/float(num_1) > 0.1
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parents:
diff changeset
1006 if "O-3,10_not_in_1,3,19" in O_list:#and float(O310_no_1319)/float(num_1) > 0.1
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cstrittmatter
parents:
diff changeset
1007 O_choice="O-3,10"
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parents:
diff changeset
1008 #print "$$$Most possilble Otype: O-3,10 (contain O-3,10_not_in_1,3,19)"
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diff changeset
1009 else:
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diff changeset
1010 O_choice="O-1,3,19"
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cstrittmatter
parents:
diff changeset
1011 #print "$$$Most possilble Otype: O-1,3,19 (not contain O-3,10_not_in_1,3,19)"
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cstrittmatter
parents:
diff changeset
1012 ### end of special test for O9,46 and O3,10 family
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parents:
diff changeset
1013
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diff changeset
1014 if O_choice=="O-9,46,27" or O_choice=="O-3,10" or O_choice=="O-1,3,19":
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parents:
diff changeset
1015 if len(Otypes_uniq)>2:
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parents:
diff changeset
1016 contamination_O="potential contamination from O antigen signals"
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parents:
diff changeset
1017 else:
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parents:
diff changeset
1018 if len(Otypes_uniq)>1:
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cstrittmatter
parents:
diff changeset
1019 if O_choice=="O-4" and len(Otypes_uniq)==2 and "O-9,46,27" in Otypes_uniq: #for special 4,12,27 case such as Bredeney and Schwarzengrund
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parents:
diff changeset
1020 contamination_O=""
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parents:
diff changeset
1021 elif O_choice=="O-9,46" and len(Otypes_uniq)==2 and "O-9,46_wbaV" in Otypes_uniq and "O-9,46_wzy" in Otypes_uniq: #for special 4,12,27 case such as Bredeney and Schwarzengrund
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parents:
diff changeset
1022 contamination_O=""
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parents:
diff changeset
1023 """
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parents:
diff changeset
1024 additonal_antigents=[]
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parents:
diff changeset
1025 #print(contamination_O)
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parents:
diff changeset
1026 #print(contamination_H)
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parents:
diff changeset
1027 log_file.write(contamination_O+"\n")
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parents:
diff changeset
1028 log_file.write(contamination_H+"\n")
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parents:
diff changeset
1029 log_file.close()
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diff changeset
1030 return O_choice,fliC_choice,fljB_choice,special_gene_list,contamination_O,contamination_H,Otypes_uniq,H1_cont_stat_list,H2_cont_stat_list
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parents:
diff changeset
1031
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diff changeset
1032 def get_input_K(input_file,lib_dict,data_type,k_size):
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cstrittmatter
parents:
diff changeset
1033 #kmer mode; get input_Ks from dict and data_type
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parents:
diff changeset
1034 kmers = []
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diff changeset
1035 for h in lib_dict:
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diff changeset
1036 kmers += lib_dict[h]
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parents:
diff changeset
1037 if data_type == '4':
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diff changeset
1038 input_Ks = target_multifasta_kmerizer(input_file, k_size, set(kmers))
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parents:
diff changeset
1039 elif data_type == '1' or data_type == '2' or data_type == '3':#set it for now, will change later
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cstrittmatter
parents:
diff changeset
1040 input_Ks = target_read_kmerizer(input_file, k_size, set(kmers))
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parents:
diff changeset
1041 elif data_type == '5':#minion_2d_fasta
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parents:
diff changeset
1042 input_Ks = minion_fasta_kmerizer(input_file, k_size, set(kmers))
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cstrittmatter
parents:
diff changeset
1043 if data_type == '6':#minion_2d_fastq
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parents:
diff changeset
1044 input_Ks = minion_fastq_kmerizer(input_file, k_size, set(kmers))
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parents:
diff changeset
1045 return input_Ks
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parents:
diff changeset
1046
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diff changeset
1047 def get_kmer_dict(lib_dict,input_Ks):
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cstrittmatter
parents:
diff changeset
1048 #kmer mode; get predicted types
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parents:
diff changeset
1049 O_dict = {}
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diff changeset
1050 H_dict = {}
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diff changeset
1051 Special_dict = {}
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diff changeset
1052 for h in lib_dict:
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parents:
diff changeset
1053 score = (len(lib_dict[h] & input_Ks) / len(lib_dict[h])) * 100
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parents:
diff changeset
1054 if score > 1: # Arbitrary cut-off for similarity score very low but seems necessary to detect O-3,10 in some cases
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cstrittmatter
parents:
diff changeset
1055 if h.startswith('O-') and score > 25:
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cstrittmatter
parents:
diff changeset
1056 O_dict[h] = score
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cstrittmatter
parents:
diff changeset
1057 if h.startswith('fl') and score > 40:
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parents:
diff changeset
1058 H_dict[h] = score
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cstrittmatter
parents:
diff changeset
1059 if (h[:2] != 'fl') and (h[:2] != 'O-'):
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diff changeset
1060 Special_dict[h] = score
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diff changeset
1061 return O_dict,H_dict,Special_dict
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diff changeset
1062
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diff changeset
1063 def call_O_and_H_type(O_dict,H_dict,Special_dict,make_dir):
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cstrittmatter
parents:
diff changeset
1064 log_file=open("SeqSero_log.txt","a")
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cstrittmatter
parents:
diff changeset
1065 log_file.write("O_scores:\n")
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cstrittmatter
parents:
diff changeset
1066 #call O:
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cstrittmatter
parents:
diff changeset
1067 highest_O = '-'
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parents:
diff changeset
1068 if len(O_dict) == 0:
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cstrittmatter
parents:
diff changeset
1069 pass
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cstrittmatter
parents:
diff changeset
1070 else:
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cstrittmatter
parents:
diff changeset
1071 for x in O_dict:
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diff changeset
1072 log_file.write(x+"\t"+str(O_dict[x])+"\n")
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cstrittmatter
parents:
diff changeset
1073 if ('O-9,46_wbaV__1002' in O_dict and O_dict['O-9,46_wbaV__1002']>70) or ("O-9,46_wbaV-from-II-9,12:z29:1,5-SRR1346254__1002" in O_dict and O_dict['O-9,46_wbaV-from-II-9,12:z29:1,5-SRR1346254__1002']>70): # not sure should use and float(O9_wbaV)/float(num_1) > 0.1
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cstrittmatter
parents:
diff changeset
1074 #if 'O-9,46_wzy__1191' in O_dict or "O-9,46_wzy_partial__216" in O_dict: # and float(O946_wzy)/float(num_1) > 0.1
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cstrittmatter
parents:
diff changeset
1075 #modified to fix miscall of O-9,46
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cstrittmatter
parents:
diff changeset
1076 if ('O-9,46_wzy__1191' in O_dict and O_dict['O-9,46_wzy__1191']>40) or ("O-9,46_wzy_partial__216" in O_dict and O_dict["O-9,46_wzy_partial__216"]>40): # and float(O946_wzy)/float(num_1) > 0.1
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diff changeset
1077 highest_O = "O-9,46"
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diff changeset
1078 elif "O-9,46,27_partial_wzy__1019" in O_dict: # and float(O94627)/float(num_1) > 0.1
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diff changeset
1079 highest_O = "O-9,46,27"
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diff changeset
1080 else:
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diff changeset
1081 highest_O = "O-9" # next, detect O9 vs O2?
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parents:
diff changeset
1082 O2 = 0
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diff changeset
1083 O9 = 0
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diff changeset
1084 for z in Special_dict:
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1085 if "tyr-O-9" in z:
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diff changeset
1086 O9 = float(Special_dict[z])
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diff changeset
1087 if "tyr-O-2" in z:
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diff changeset
1088 O2 = float(Special_dict[z])
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parents:
diff changeset
1089 if O2 > O9:
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diff changeset
1090 highest_O = "O-2"
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diff changeset
1091 elif ("O-3,10_wzx__1539" in O_dict) and (
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cstrittmatter
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diff changeset
1092 "O-9,46_wzy__1191" in O_dict
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diff changeset
1093 ): # and float(O310_wzx)/float(num_1) > 0.1 and float(O946_wzy)/float(num_1) > 0.1
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diff changeset
1094 if "O-3,10_not_in_1,3,19__1519" in O_dict: # and float(O310_no_1319)/float(num_1) > 0.1
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diff changeset
1095 highest_O = "O-3,10"
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diff changeset
1096 else:
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diff changeset
1097 highest_O = "O-1,3,19"
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diff changeset
1098 ### end of special test for O9,46 and O3,10 family
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diff changeset
1099 else:
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diff changeset
1100 try:
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diff changeset
1101 max_score = 0
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diff changeset
1102 for x in O_dict:
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diff changeset
1103 if float(O_dict[x]) >= max_score:
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diff changeset
1104 max_score = float(O_dict[x])
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diff changeset
1105 #highest_O = x.split("_")[0]
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diff changeset
1106 # ed_SL_12182019: modified to fix the O-9,46 error example1
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diff changeset
1107 if (x == 'O-9,46_wbaV__1002' or x == 'O-9,46_wbaV-from-II-9,12:z29:1,5-SRR1346254__1002') and ('O-9,46_wzy__1191' not in O_dict and 'O-9,46_wzy_partial__216' not in O_dict):
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diff changeset
1108 highest_O = "O-9"
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diff changeset
1109 else:
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diff changeset
1110 highest_O = x.split("_")[0]
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diff changeset
1111 if highest_O == "O-1,3,19":
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diff changeset
1112 highest_O = '-'
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diff changeset
1113 max_score = 0
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diff changeset
1114 for x in O_dict:
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diff changeset
1115 if x == 'O-1,3,19_not_in_3,10__130':
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diff changeset
1116 pass
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diff changeset
1117 else:
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1118 if float(O_dict[x]) >= max_score:
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diff changeset
1119 max_score = float(O_dict[x])
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diff changeset
1120 #highest_O = x.split("_")[0]
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diff changeset
1121 # ed_SL_12182019: modified to fix the O-9,46 error example1
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diff changeset
1122 if (x == 'O-9,46_wbaV__1002' or x == 'O-9,46_wbaV-from-II-9,12:z29:1,5-SRR1346254__1002') and ('O-9,46_wzy__1191' not in O_dict and 'O-9,46_wzy_partial__216' not in O_dict):
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diff changeset
1123 highest_O = "O-9"
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diff changeset
1124 else:
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diff changeset
1125 highest_O = x.split("_")[0]
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diff changeset
1126 except:
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diff changeset
1127 pass
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diff changeset
1128 #call_fliC:
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diff changeset
1129 if len(H_dict)!=0:
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diff changeset
1130 highest_H_score_both_BC=H_dict[max(H_dict.keys(), key=(lambda k: H_dict[k]))] #used to detect whether fljB existed or not
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diff changeset
1131 else:
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diff changeset
1132 highest_H_score_both_BC=0
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parents:
diff changeset
1133 highest_fliC = '-'
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diff changeset
1134 highest_fliC_raw = '-'
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parents:
diff changeset
1135 highest_Score = 0
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diff changeset
1136 log_file.write("\nH_scores:\n")
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parents:
diff changeset
1137 for s in H_dict:
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diff changeset
1138 log_file.write(s+"\t"+str(H_dict[s])+"\n")
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parents:
diff changeset
1139 if s.startswith('fliC'):
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diff changeset
1140 if float(H_dict[s]) > highest_Score:
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parents:
diff changeset
1141 highest_fliC = s.split('_')[1]
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parents:
diff changeset
1142 highest_fliC_raw = s
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diff changeset
1143 highest_Score = float(H_dict[s])
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parents:
diff changeset
1144 #call_fljB
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diff changeset
1145 highest_fljB = '-'
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diff changeset
1146 highest_fljB_raw = '-'
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diff changeset
1147 highest_Score = 0
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diff changeset
1148 for s in H_dict:
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diff changeset
1149 if s.startswith('fljB'):
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diff changeset
1150 if float(H_dict[s]) > highest_Score and float(H_dict[s]) > highest_H_score_both_BC * 0.65: #fljB is special, so use highest_H_score_both_BC to give a general estimate of coverage, currently 0.65 seems pretty good; the reason use a high (0.65) is some fliC and fljB shared with each other
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parents:
diff changeset
1151 #highest_fljB = s.split('_')[1]
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parents:
diff changeset
1152 #highest_fljB_raw = s
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diff changeset
1153 #highest_Score = float(H_dict[s])
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diff changeset
1154 if s.split('_')[1]!=highest_fliC:
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parents:
diff changeset
1155 highest_fljB = s.split('_')[1]
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parents:
diff changeset
1156 highest_fljB_raw = s
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diff changeset
1157 highest_Score = float(H_dict[s])
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diff changeset
1158 log_file.write("\nSpecial_scores:\n")
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parents:
diff changeset
1159 for s in Special_dict:
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diff changeset
1160 log_file.write(s+"\t"+str(Special_dict[s])+"\n")
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parents:
diff changeset
1161 log_file.close()
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diff changeset
1162 return highest_O,highest_fliC,highest_fljB
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parents:
diff changeset
1163
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diff changeset
1164 def get_temp_file_names(for_fq,rev_fq):
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cstrittmatter
parents:
diff changeset
1165 #seqsero2 -a; get temp file names
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parents:
diff changeset
1166 sam=for_fq+".sam"
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cstrittmatter
parents:
diff changeset
1167 bam=for_fq+".bam"
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cstrittmatter
parents:
diff changeset
1168 sorted_bam=for_fq+"_sorted.bam"
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cstrittmatter
parents:
diff changeset
1169 mapped_fq1=for_fq+"_mapped.fq"
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cstrittmatter
parents:
diff changeset
1170 mapped_fq2=rev_fq+"_mapped.fq"
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cstrittmatter
parents:
diff changeset
1171 combined_fq=for_fq+"_combined.fq"
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parents:
diff changeset
1172 for_sai=for_fq+".sai"
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cstrittmatter
parents:
diff changeset
1173 rev_sai=rev_fq+".sai"
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diff changeset
1174 return sam,bam,sorted_bam,mapped_fq1,mapped_fq2,combined_fq,for_sai,rev_sai
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diff changeset
1175
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diff changeset
1176 def map_and_sort(threads,database,fnameA,fnameB,sam,bam,for_sai,rev_sai,sorted_bam,mapping_mode):
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diff changeset
1177 #seqsero2 -a; do mapping and sort
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diff changeset
1178 print("building database...")
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diff changeset
1179 subprocess.check_call("bwa index "+database+ " 2>> data_log.txt",shell=True)
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diff changeset
1180 print("mapping...")
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diff changeset
1181 if mapping_mode=="mem":
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diff changeset
1182 subprocess.check_call("bwa mem -k 17 -t "+threads+" "+database+" "+fnameA+" "+fnameB+" > "+sam+ " 2>> data_log.txt",shell=True)
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1183 elif mapping_mode=="sam":
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diff changeset
1184 if fnameB!="":
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diff changeset
1185 subprocess.check_call("bwa aln -t "+threads+" "+database+" "+fnameA+" > "+for_sai+ " 2>> data_log.txt",shell=True)
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diff changeset
1186 subprocess.check_call("bwa aln -t "+threads+" "+database+" "+fnameB+" > "+rev_sai+ " 2>> data_log.txt",shell=True)
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diff changeset
1187 subprocess.check_call("bwa sampe "+database+" "+for_sai+" "+ rev_sai+" "+fnameA+" "+fnameB+" > "+sam+ " 2>> data_log.txt",shell=True)
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diff changeset
1188 else:
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diff changeset
1189 subprocess.check_call("bwa aln -t "+threads+" "+database+" "+fnameA+" > "+for_sai+ " 2>> data_log.txt",shell=True)
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diff changeset
1190 subprocess.check_call("bwa samse "+database+" "+for_sai+" "+for_fq+" > "+sam)
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diff changeset
1191 subprocess.check_call("samtools view -@ "+threads+" -F 4 -Sh "+sam+" > "+bam,shell=True)
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diff changeset
1192 ### check the version of samtools then use differnt commands
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diff changeset
1193 samtools_version=subprocess.Popen(["samtools"],stdout=subprocess.PIPE,stderr=subprocess.PIPE)
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1194 out, err = samtools_version.communicate()
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diff changeset
1195 version = str(err).split("ersion:")[1].strip().split(" ")[0].strip()
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diff changeset
1196 print("check samtools version:",version)
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diff changeset
1197 ### end of samtools version check and its analysis
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1198 if LooseVersion(version)<=LooseVersion("1.2"):
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diff changeset
1199 subprocess.check_call("samtools sort -@ "+threads+" -n "+bam+" "+fnameA+"_sorted",shell=True)
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1200 else:
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diff changeset
1201 subprocess.check_call("samtools sort -@ "+threads+" -n "+bam+" >"+sorted_bam,shell=True)
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diff changeset
1202
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diff changeset
1203 def extract_mapped_reads_and_do_assembly_and_blast(current_time,sorted_bam,combined_fq,mapped_fq1,mapped_fq2,threads,fnameA,fnameB,database,mapping_mode):
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diff changeset
1204 #seqsero2 -a; extract, assembly and blast
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diff changeset
1205 subprocess.check_call("bamToFastq -i "+sorted_bam+" -fq "+combined_fq,shell=True)
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diff changeset
1206 #print("fnameA:",fnameA)
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diff changeset
1207 #print("fnameB:",fnameB)
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1208 if fnameB!="":
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diff changeset
1209 subprocess.check_call("bamToFastq -i "+sorted_bam+" -fq "+mapped_fq1+" -fq2 "+mapped_fq2 + " 2>> data_log.txt",shell=True)#2> /dev/null if want no output
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1210 else:
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diff changeset
1211 pass
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1212 outdir=current_time+"_temp"
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diff changeset
1213 print("assembling...")
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diff changeset
1214 if int(threads)>4:
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diff changeset
1215 t="4"
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1216 else:
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diff changeset
1217 t=threads
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diff changeset
1218 if os.path.getsize(combined_fq)>100 and (fnameB=="" or os.path.getsize(mapped_fq1)>100):#if not, then it's "-:-:-"
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diff changeset
1219 if fnameB!="":
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diff changeset
1220 subprocess.check_call("spades.py --careful --pe1-s "+combined_fq+" --pe1-1 "+mapped_fq1+" --pe1-2 "+mapped_fq2+" -t "+t+" -o "+outdir+ " >> data_log.txt 2>&1",shell=True)
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diff changeset
1221 else:
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diff changeset
1222 subprocess.check_call("spades.py --careful --pe1-s "+combined_fq+" -t "+t+" -o "+outdir+ " >> data_log.txt 2>&1",shell=True)
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diff changeset
1223 new_fasta=fnameA+"_"+database+"_"+mapping_mode+".fasta"
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cstrittmatter
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diff changeset
1224 #new_fasta=fnameA+"_"+database.split('/')[-1]+"_"+mapping_mode+".fasta" # change path to databse for packaging
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diff changeset
1225 subprocess.check_call("mv "+outdir+"/contigs.fasta "+new_fasta+ " 2> /dev/null",shell=True)
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diff changeset
1226 #os.system("mv "+outdir+"/scaffolds.fasta "+new_fasta+ " 2> /dev/null") contigs.fasta
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diff changeset
1227 subprocess.check_call("rm -rf "+outdir+ " 2> /dev/null",shell=True)
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diff changeset
1228 print("blasting...","\n")
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diff changeset
1229 xmlfile="blasted_output.xml"#fnameA+"-extracted_vs_"+database+"_"+mapping_mode+".xml"
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diff changeset
1230 subprocess.check_call('makeblastdb -in '+new_fasta+' -out '+new_fasta+'_db '+'-dbtype nucl >> data_log.txt 2>&1',shell=True) #temp.txt is to forbid the blast result interrupt the output of our program###1/27/2015
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diff changeset
1231 subprocess.check_call("blastn -query "+database+" -db "+new_fasta+"_db -out "+xmlfile+" -outfmt 5 >> data_log.txt 2>&1",shell=True)###1/27/2015; 08272018, remove "-word_size 10"
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diff changeset
1232 else:
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diff changeset
1233 xmlfile="NA"
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diff changeset
1234 return xmlfile,new_fasta
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diff changeset
1235
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diff changeset
1236 def judge_subspecies(fnameA):
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cstrittmatter
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diff changeset
1237 #seqsero2 -a; judge subspecies on just forward raw reads fastq
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diff changeset
1238 salmID_output=subprocess.Popen("SalmID.py -i "+fnameA,shell=True,stdout=subprocess.PIPE,stderr=subprocess.PIPE)
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diff changeset
1239 out, err = salmID_output.communicate()
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diff changeset
1240 out=out.decode("utf-8")
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diff changeset
1241 file=open("data_log.txt","a")
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diff changeset
1242 file.write(out)
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diff changeset
1243 file.close()
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diff changeset
1244 salm_species_scores=out.split("\n")[1].split("\t")[6:]
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diff changeset
1245 salm_species_results=out.split("\n")[0].split("\t")[6:]
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diff changeset
1246 max_score=0
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1247 max_score_index=1 #default is 1, means "I"
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diff changeset
1248 for i in range(len(salm_species_scores)):
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1249 if max_score<float(salm_species_scores[i]):
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diff changeset
1250 max_score=float(salm_species_scores[i])
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diff changeset
1251 max_score_index=i
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diff changeset
1252 prediction=salm_species_results[max_score_index].split(".")[1].strip().split(" ")[0]
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diff changeset
1253 #if float(out.split("\n")[1].split("\t")[4]) > float(out.split("\n")[1].split("\t")[5]): #bongori and enterica compare
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diff changeset
1254 if float(out.split("\n")[1].split("\t")[4]) > 10 and float(out.split("\n")[1].split("\t")[4]) > float(out.split("\n")[1].split("\t")[5]): ## ed_SL_0318: change SalmID_ssp_threshold
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diff changeset
1255 prediction="bongori" #if not, the prediction would always be enterica, since they are located in the later part
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parents:
diff changeset
1256 #if max_score<10: ## ed_SL_0318: change SalmID_ssp_threshold
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diff changeset
1257 if max_score<60:
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diff changeset
1258 prediction="-"
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diff changeset
1259 return prediction
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diff changeset
1260
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1261 def judge_subspecies_Kmer(Special_dict):
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diff changeset
1262 #seqsero2 -k;
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diff changeset
1263 max_score=0
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diff changeset
1264 prediction="-" #default should be I
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diff changeset
1265 for x in Special_dict:
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diff changeset
1266 #if "mer" in x: ## ed_SL_0318: change ssp_threshold
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diff changeset
1267 if "mer" in x and float(Special_dict[x]) > 60:
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diff changeset
1268 if max_score<float(Special_dict[x]):
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diff changeset
1269 max_score=float(Special_dict[x])
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diff changeset
1270 prediction=x.split("_")[-1].strip()
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diff changeset
1271 if x.split("_")[-1].strip()=="bongori" and float(Special_dict[x])>95:#if bongori already, then no need to test enterica
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diff changeset
1272 prediction="bongori"
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diff changeset
1273 break
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diff changeset
1274 return prediction
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diff changeset
1275
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diff changeset
1276 ## ed_SL_11232019: add notes for missing antigen
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parents:
diff changeset
1277 def check_antigens(ssp,O_antigen,H1_antigen,H2_antigen,NA_note):
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diff changeset
1278 antigen_note = ''
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diff changeset
1279 if ssp != '-':
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diff changeset
1280 if O_antigen != '-' and H1_antigen == '-' and H2_antigen == '-': # O:-:-
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parents:
diff changeset
1281 antigen_note = 'H antigens were not detected. This is an atypical result that should be further investigated. Most Salmonella strains have at least fliC, encoding the Phase 1 H antigen, even if it is not expressed. '
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cstrittmatter
parents:
diff changeset
1282 NA_note = ''
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cstrittmatter
parents:
diff changeset
1283 elif O_antigen != '-' and H1_antigen == '-' and H2_antigen != '-': # O:-:H2
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cstrittmatter
parents:
diff changeset
1284 antigen_note = 'fliC was not detected. This is an atypical result that should be further investigated. Most Salmonella strains have fliC, encoding the Phase 1 H antigen, even if it is not expressed. '
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cstrittmatter
parents:
diff changeset
1285 NA_note = ''
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cstrittmatter
parents:
diff changeset
1286 elif O_antigen == '-' and H1_antigen != '-': # -:H1:X
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cstrittmatter
parents:
diff changeset
1287 antigen_note = 'O antigen was not detected. This result may be due to a rough strain that has deleted the rfb region. For raw reads input, the k-mer workflow is sometimes more sensitive than the microassembly workflow in detecting O antigen. Caution should be used with this approach because the k-mer result may be due to low levels of contamination. '
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cstrittmatter
parents:
diff changeset
1288 NA_note = ''
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cstrittmatter
parents:
diff changeset
1289 elif O_antigen == '-' and H1_antigen == '-' and H2_antigen == '-': # -:-:-
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cstrittmatter
parents:
diff changeset
1290 antigen_note = 'No serotype antigens were detected. This is an atypical result that should be further investigated. '
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cstrittmatter
parents:
diff changeset
1291 NA_note = ''
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cstrittmatter
parents:
diff changeset
1292 else:
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cstrittmatter
parents:
diff changeset
1293 antigen_note = 'The input genome cannot be identified as Salmonella. Check the input for taxonomic ID, contamination, or sequencing quality. '
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cstrittmatter
parents:
diff changeset
1294 NA_note = ''
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cstrittmatter
parents:
diff changeset
1295 # if [O_antigen, H1_antigen, H2_antigen].count('-') >= 2:
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cstrittmatter
parents:
diff changeset
1296 # antigen_note = 'No subspecies marker was detected and less than 2 serotype antigens were detected; further, this genome was not identified as Salmonella. This is an atypical result that should be further investigated. '
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cstrittmatter
parents:
diff changeset
1297 # else:
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cstrittmatter
parents:
diff changeset
1298 # antigen_note = 'No subspecies marker was detected. This genome may not be Salmonella. This is an atypical result that should be further investigated. '
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cstrittmatter
parents:
diff changeset
1299 return (antigen_note,NA_note)
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cstrittmatter
parents:
diff changeset
1300
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cstrittmatter
parents:
diff changeset
1301 def main():
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cstrittmatter
parents:
diff changeset
1302 #combine SeqSeroK and SeqSero2, also with SalmID
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cstrittmatter
parents:
diff changeset
1303 args = parse_args()
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cstrittmatter
parents:
diff changeset
1304 input_file = args.i
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cstrittmatter
parents:
diff changeset
1305 data_type = args.t
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cstrittmatter
parents:
diff changeset
1306 analysis_mode = args.m
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cstrittmatter
parents:
diff changeset
1307 mapping_mode=args.b
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cstrittmatter
parents:
diff changeset
1308 threads=args.p
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cstrittmatter
parents:
diff changeset
1309 make_dir=args.d
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cstrittmatter
parents:
diff changeset
1310 clean_mode=args.c
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cstrittmatter
parents:
diff changeset
1311 sample_name=args.n
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cstrittmatter
parents:
diff changeset
1312 ingore_header=args.s
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cstrittmatter
parents:
diff changeset
1313 k_size=27 #will change for bug fixing
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cstrittmatter
parents:
diff changeset
1314 dirpath = os.path.abspath(os.path.dirname(os.path.realpath(__file__)))
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cstrittmatter
parents:
diff changeset
1315 ex_dir = os.path.abspath(os.path.join(os.path.dirname(os.path.dirname(__file__)),'seqsero2_db')) # ed_SL_09152019: add ex_dir for packaging
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cstrittmatter
parents:
diff changeset
1316 seqsero2_db=ex_dir+"/H_and_O_and_specific_genes.fasta" # ed_SL_11092019: change path to database for packaging
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cstrittmatter
parents:
diff changeset
1317 database="H_and_O_and_specific_genes.fasta"
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cstrittmatter
parents:
diff changeset
1318 note="Note: "
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cstrittmatter
parents:
diff changeset
1319 NA_note="This predicted serotype is not in the Kauffman-White scheme. " # ed_SL_09272019: add for new output format
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cstrittmatter
parents:
diff changeset
1320 if len(sys.argv)==1:
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cstrittmatter
parents:
diff changeset
1321 subprocess.check_call(dirpath+"/SeqSero2_package.py -h",shell=True)#change name of python file
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cstrittmatter
parents:
diff changeset
1322 else:
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cstrittmatter
parents:
diff changeset
1323 request_id = time.strftime("%m_%d_%Y_%H_%M_%S", time.localtime())
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cstrittmatter
parents:
diff changeset
1324 request_id += str(random.randint(1, 10000000))
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cstrittmatter
parents:
diff changeset
1325 if make_dir is None:
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cstrittmatter
parents:
diff changeset
1326 make_dir="SeqSero_result_"+request_id
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cstrittmatter
parents:
diff changeset
1327 make_dir=os.path.abspath(make_dir)
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cstrittmatter
parents:
diff changeset
1328 if os.path.isdir(make_dir):
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cstrittmatter
parents:
diff changeset
1329 pass
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cstrittmatter
parents:
diff changeset
1330 else:
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cstrittmatter
parents:
diff changeset
1331 subprocess.check_call("mkdir -p "+make_dir,shell=True)
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cstrittmatter
parents:
diff changeset
1332 #subprocess.check_call("cp "+dirpath+"/"+database+" "+" ".join(input_file)+" "+make_dir,shell=True)
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cstrittmatter
parents:
diff changeset
1333 #subprocess.check_call("ln -sr "+dirpath+"/"+database+" "+" ".join(input_file)+" "+make_dir,shell=True)
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cstrittmatter
parents:
diff changeset
1334 subprocess.check_call("ln -f -s "+seqsero2_db+" "+" ".join(input_file)+" "+make_dir,shell=True) # ed_SL_11092019: change path to database for packaging
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cstrittmatter
parents:
diff changeset
1335 #subprocess.check_call("ln -f -s "+dirpath+"/"+database+" "+" ".join(input_file)+" "+make_dir,shell=True) ### use -f option to force the replacement of links, remove -r and use absolute path instead to avoid link issue (use 'type=os.path.abspath' in -i argument).
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cstrittmatter
parents:
diff changeset
1336 ############################begin the real analysis
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cstrittmatter
parents:
diff changeset
1337 if analysis_mode=="a":
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cstrittmatter
parents:
diff changeset
1338 if data_type in ["1","2","3"]:#use allele mode
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cstrittmatter
parents:
diff changeset
1339 for_fq,rev_fq=get_input_files(make_dir,input_file,data_type,dirpath)
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cstrittmatter
parents:
diff changeset
1340 os.chdir(make_dir)
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cstrittmatter
parents:
diff changeset
1341 ###add a function to tell input files
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cstrittmatter
parents:
diff changeset
1342 fnameA=for_fq.split("/")[-1]
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cstrittmatter
parents:
diff changeset
1343 fnameB=rev_fq.split("/")[-1]
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cstrittmatter
parents:
diff changeset
1344 current_time=time.strftime("%Y_%m_%d_%H_%M_%S", time.localtime())
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cstrittmatter
parents:
diff changeset
1345 sam,bam,sorted_bam,mapped_fq1,mapped_fq2,combined_fq,for_sai,rev_sai=get_temp_file_names(fnameA,fnameB) #get temp files id
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cstrittmatter
parents:
diff changeset
1346 map_and_sort(threads,database,fnameA,fnameB,sam,bam,for_sai,rev_sai,sorted_bam,mapping_mode) #do mapping and sort
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cstrittmatter
parents:
diff changeset
1347 ### avoid error out when micro assembly fails. ed_SL_03172020
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cstrittmatter
parents:
diff changeset
1348 try:
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cstrittmatter
parents:
diff changeset
1349 xmlfile,new_fasta=extract_mapped_reads_and_do_assembly_and_blast(current_time,sorted_bam,combined_fq,mapped_fq1,mapped_fq2,threads,fnameA,fnameB,database,mapping_mode) #extract the mapped reads and do micro assembly and blast
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cstrittmatter
parents:
diff changeset
1350 except (UnboundLocalError, subprocess.CalledProcessError):
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parents:
diff changeset
1351 xmlfile="NA"
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parents:
diff changeset
1352 H1_cont_stat_list=[]
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cstrittmatter
parents:
diff changeset
1353 H2_cont_stat_list=[]
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cstrittmatter
parents:
diff changeset
1354 ###
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parents:
diff changeset
1355 if xmlfile=="NA":
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cstrittmatter
parents:
diff changeset
1356 O_choice,fliC_choice,fljB_choice,special_gene_list,contamination_O,contamination_H=("-","-","-",[],"","")
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cstrittmatter
parents:
diff changeset
1357 else:
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parents:
diff changeset
1358 Final_list=xml_parse_score_comparision_seqsero(xmlfile) #analyze xml and get parsed results
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cstrittmatter
parents:
diff changeset
1359 file=open("data_log.txt","a")
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cstrittmatter
parents:
diff changeset
1360 for x in Final_list:
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cstrittmatter
parents:
diff changeset
1361 file.write("\t".join(str(y) for y in x)+"\n")
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cstrittmatter
parents:
diff changeset
1362 file.close()
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cstrittmatter
parents:
diff changeset
1363 Final_list_passed=[x for x in Final_list if float(x[0].split("_cov_")[1].split("_")[0])>=0.9 and (x[1]>=int(x[0].split("__")[1]) or x[1]>=int(x[0].split("___")[1].split("_")[3]) or x[1]>1000)]
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cstrittmatter
parents:
diff changeset
1364 O_choice,fliC_choice,fljB_choice,special_gene_list,contamination_O,contamination_H,Otypes_uniq,H1_cont_stat_list,H2_cont_stat_list=predict_O_and_H_types(Final_list,Final_list_passed,new_fasta) #predict O, fliC and fljB
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cstrittmatter
parents:
diff changeset
1365 subspecies=judge_subspecies(fnameA) #predict subspecies
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cstrittmatter
parents:
diff changeset
1366 ###output
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cstrittmatter
parents:
diff changeset
1367 predict_form,predict_sero,star,star_line,claim=seqsero_from_formula_to_serotypes(O_choice,fliC_choice,fljB_choice,special_gene_list,subspecies)
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cstrittmatter
parents:
diff changeset
1368 claim="" #04132019, disable claim for new report requirement
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cstrittmatter
parents:
diff changeset
1369 contamination_report=""
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cstrittmatter
parents:
diff changeset
1370 H_list=["fliC_"+x for x in H1_cont_stat_list if len(x)>0]+["fljB_"+x for x in H2_cont_stat_list if len(x)>0]
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cstrittmatter
parents:
diff changeset
1371 if contamination_O!="" and contamination_H=="":
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cstrittmatter
parents:
diff changeset
1372 contamination_report="#Potential inter-serotype contamination detected from O antigen signals. All O-antigens detected:"+"\t".join(Otypes_uniq)+"."
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cstrittmatter
parents:
diff changeset
1373 elif contamination_O=="" and contamination_H!="":
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cstrittmatter
parents:
diff changeset
1374 contamination_report="#Potential inter-serotype contamination detected or potential thrid H phase from H antigen signals. All H-antigens detected:"+"\t".join(H_list)+"."
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cstrittmatter
parents:
diff changeset
1375 elif contamination_O!="" and contamination_H!="":
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cstrittmatter
parents:
diff changeset
1376 contamination_report="#Potential inter-serotype contamination detected from both O and H antigen signals.All O-antigens detected:"+"\t".join(Otypes_uniq)+". All H-antigens detected:"+"\t".join(H_list)+"."
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cstrittmatter
parents:
diff changeset
1377 if contamination_report!="":
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cstrittmatter
parents:
diff changeset
1378 #contamination_report="potential inter-serotype contamination detected (please refer below antigen signal report for details)." #above contamination_reports are for back-up and bug fixing #web-based mode need to be re-used, 04132019
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cstrittmatter
parents:
diff changeset
1379 contamination_report="Co-existence of multiple serotypes detected, indicating potential inter-serotype contamination. See 'Extracted_antigen_alleles.fasta' for detected serotype determinant alleles. "
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cstrittmatter
parents:
diff changeset
1380 #claim="\n"+open("Extracted_antigen_alleles.fasta","r").read()#used to store H and O antigen sequeences #04132019, need to change if using web-version
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cstrittmatter
parents:
diff changeset
1381 #if contamination_report+star_line+claim=="": #0413, new output style
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cstrittmatter
parents:
diff changeset
1382 # note=""
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cstrittmatter
parents:
diff changeset
1383 #else:
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cstrittmatter
parents:
diff changeset
1384 # note="Note:"
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cstrittmatter
parents:
diff changeset
1385
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cstrittmatter
parents:
diff changeset
1386 ### ed_SL_11232019: add notes for missing antigen
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cstrittmatter
parents:
diff changeset
1387 if O_choice=="":
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cstrittmatter
parents:
diff changeset
1388 O_choice="-"
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cstrittmatter
parents:
diff changeset
1389 antigen_note,NA_note=check_antigens(subspecies,O_choice,fliC_choice,fljB_choice,NA_note)
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cstrittmatter
parents:
diff changeset
1390 if sample_name:
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cstrittmatter
parents:
diff changeset
1391 print ("Sample name:\t"+sample_name)
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cstrittmatter
parents:
diff changeset
1392 ###
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cstrittmatter
parents:
diff changeset
1393
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cstrittmatter
parents:
diff changeset
1394 if clean_mode:
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cstrittmatter
parents:
diff changeset
1395 subprocess.check_call("rm -rf ../"+make_dir,shell=True)
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cstrittmatter
parents:
diff changeset
1396 make_dir="none-output-directory due to '-c' flag"
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cstrittmatter
parents:
diff changeset
1397 else:
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cstrittmatter
parents:
diff changeset
1398 new_file=open("SeqSero_result.txt","w")
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cstrittmatter
parents:
diff changeset
1399 ### ed_SL_01152020: add new output
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cstrittmatter
parents:
diff changeset
1400 conta_note="yes" if "inter-serotype contamination" in contamination_report else "no"
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cstrittmatter
parents:
diff changeset
1401 tsv_file=open("SeqSero_result.tsv","w")
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cstrittmatter
parents:
diff changeset
1402 if ingore_header:
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cstrittmatter
parents:
diff changeset
1403 pass
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cstrittmatter
parents:
diff changeset
1404 else:
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cstrittmatter
parents:
diff changeset
1405 tsv_file.write("Sample name\tOutput directory\tInput files\tO antigen prediction\tH1 antigen prediction(fliC)\tH2 antigen prediction(fljB)\tPredicted subspecies\tPredicted antigenic profile\tPredicted serotype\tPotential inter-serotype contamination\tNote\n")
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cstrittmatter
parents:
diff changeset
1406 if sample_name:
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cstrittmatter
parents:
diff changeset
1407 new_file.write("Sample name:\t"+sample_name+"\n")
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cstrittmatter
parents:
diff changeset
1408 tsv_file.write(sample_name+'\t')
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cstrittmatter
parents:
diff changeset
1409 else:
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cstrittmatter
parents:
diff changeset
1410 tsv_file.write(input_file[0].split('/')[-1]+'\t')
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cstrittmatter
parents:
diff changeset
1411 ###
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cstrittmatter
parents:
diff changeset
1412 if "N/A" not in predict_sero:
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cstrittmatter
parents:
diff changeset
1413 new_file.write("Output directory:\t"+make_dir+"\n"+
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cstrittmatter
parents:
diff changeset
1414 "Input files:\t"+"\t".join(input_file)+"\n"+
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cstrittmatter
parents:
diff changeset
1415 "O antigen prediction:\t"+O_choice+"\n"+
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cstrittmatter
parents:
diff changeset
1416 "H1 antigen prediction(fliC):\t"+fliC_choice+"\n"+
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cstrittmatter
parents:
diff changeset
1417 "H2 antigen prediction(fljB):\t"+fljB_choice+"\n"+
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cstrittmatter
parents:
diff changeset
1418 "Predicted subspecies:\t"+subspecies+"\n"+
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cstrittmatter
parents:
diff changeset
1419 "Predicted antigenic profile:\t"+predict_form+"\n"+
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cstrittmatter
parents:
diff changeset
1420 "Predicted serotype:\t"+predict_sero+"\n"+
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cstrittmatter
parents:
diff changeset
1421 note+contamination_report+star_line+claim+antigen_note+"\n")#+##
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cstrittmatter
parents:
diff changeset
1422 tsv_file.write(make_dir+"\t"+" ".join(input_file)+"\t"+O_choice+"\t"+fliC_choice+"\t"+fljB_choice+"\t"+subspecies+"\t"+predict_form+"\t"+predict_sero+"\t"+conta_note+"\t"+contamination_report+star_line+claim+antigen_note+"\n")
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cstrittmatter
parents:
diff changeset
1423 else:
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cstrittmatter
parents:
diff changeset
1424 #star_line=star_line.strip()+"\tNone such antigenic formula in KW.\n"
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cstrittmatter
parents:
diff changeset
1425 star_line="" #04132019, for new output requirement, diable star_line if "NA" in output
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cstrittmatter
parents:
diff changeset
1426 new_file.write("Output directory:\t"+make_dir+"\n"+
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cstrittmatter
parents:
diff changeset
1427 "Input files:\t"+"\t".join(input_file)+"\n"+
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cstrittmatter
parents:
diff changeset
1428 "O antigen prediction:\t"+O_choice+"\n"+
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cstrittmatter
parents:
diff changeset
1429 "H1 antigen prediction(fliC):\t"+fliC_choice+"\n"+
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cstrittmatter
parents:
diff changeset
1430 "H2 antigen prediction(fljB):\t"+fljB_choice+"\n"+
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cstrittmatter
parents:
diff changeset
1431 "Predicted subspecies:\t"+subspecies+"\n"+
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cstrittmatter
parents:
diff changeset
1432 "Predicted antigenic profile:\t"+predict_form+"\n"+
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cstrittmatter
parents:
diff changeset
1433 "Predicted serotype:\t"+subspecies+' '+predict_form+"\n"+ # add serotype output for "N/A" prediction, add subspecies
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cstrittmatter
parents:
diff changeset
1434 note+NA_note+contamination_report+star_line+claim+antigen_note+"\n")#+##
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cstrittmatter
parents:
diff changeset
1435 tsv_file.write(make_dir+"\t"+" ".join(input_file)+"\t"+O_choice+"\t"+fliC_choice+"\t"+fljB_choice+"\t"+subspecies+"\t"+predict_form+"\t"+subspecies+' '+predict_form+"\t"+conta_note+"\t"+NA_note+contamination_report+star_line+claim+antigen_note+"\n")
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cstrittmatter
parents:
diff changeset
1436 new_file.close()
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cstrittmatter
parents:
diff changeset
1437 tsv_file.close()
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cstrittmatter
parents:
diff changeset
1438 #subprocess.check_call("cat Seqsero_result.txt",shell=True)
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cstrittmatter
parents:
diff changeset
1439 #subprocess.call("rm H_and_O_and_specific_genes.fasta* *.sra *.bam *.sam *.fastq *.gz *.fq temp.txt *.xml "+fnameA+"*_db* 2> /dev/null",shell=True)
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cstrittmatter
parents:
diff changeset
1440 subprocess.call("rm H_and_O_and_specific_genes.fasta* *.sra *.bam *.sam *.fastq *.gz *.fq temp.txt "+fnameA+"*_db* 2> /dev/null",shell=True)
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cstrittmatter
parents:
diff changeset
1441 if "N/A" not in predict_sero:
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cstrittmatter
parents:
diff changeset
1442 #print("Output_directory:"+make_dir+"\nInput files:\t"+for_fq+" "+rev_fq+"\n"+"O antigen prediction:\t"+O_choice+"\n"+"H1 antigen prediction(fliC):\t"+fliC_choice+"\n"+"H2 antigen prediction(fljB):\t"+fljB_choice+"\n"+"Predicted antigenic profile:\t"+predict_form+"\n"+"Predicted subspecies:\t"+subspecies+"\n"+"Predicted serotype(s):\t"+predict_sero+star+"\nNote:"+contamination_report+star+star_line+claim+"\n")#+##
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cstrittmatter
parents:
diff changeset
1443 print("Output directory:\t"+make_dir+"\n"+
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cstrittmatter
parents:
diff changeset
1444 "Input files:\t"+"\t".join(input_file)+"\n"+
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cstrittmatter
parents:
diff changeset
1445 "O antigen prediction:\t"+O_choice+"\n"+
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cstrittmatter
parents:
diff changeset
1446 "H1 antigen prediction(fliC):\t"+fliC_choice+"\n"+
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cstrittmatter
parents:
diff changeset
1447 "H2 antigen prediction(fljB):\t"+fljB_choice+"\n"+
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cstrittmatter
parents:
diff changeset
1448 "Predicted subspecies:\t"+subspecies+"\n"+
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cstrittmatter
parents:
diff changeset
1449 "Predicted antigenic profile:\t"+predict_form+"\n"+
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cstrittmatter
parents:
diff changeset
1450 "Predicted serotype:\t"+predict_sero+"\n"+
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cstrittmatter
parents:
diff changeset
1451 note+contamination_report+star_line+claim+antigen_note+"\n")#+##
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cstrittmatter
parents:
diff changeset
1452 else:
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cstrittmatter
parents:
diff changeset
1453 print("Output directory:\t"+make_dir+"\n"+
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cstrittmatter
parents:
diff changeset
1454 "Input files:\t"+"\t".join(input_file)+"\n"+
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cstrittmatter
parents:
diff changeset
1455 "O antigen prediction:\t"+O_choice+"\n"+
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cstrittmatter
parents:
diff changeset
1456 "H1 antigen prediction(fliC):\t"+fliC_choice+"\n"+
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cstrittmatter
parents:
diff changeset
1457 "H2 antigen prediction(fljB):\t"+fljB_choice+"\n"+
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cstrittmatter
parents:
diff changeset
1458 "Predicted subspecies:\t"+subspecies+"\n"+
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cstrittmatter
parents:
diff changeset
1459 "Predicted antigenic profile:\t"+predict_form+"\n"+
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cstrittmatter
parents:
diff changeset
1460 "Predicted serotype:\t"+subspecies+' '+predict_form+"\n"+ # add serotype output for "N/A" prediction, subspecies
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cstrittmatter
parents:
diff changeset
1461 note+NA_note+contamination_report+star_line+claim+antigen_note+"\n")
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cstrittmatter
parents:
diff changeset
1462 else:
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cstrittmatter
parents:
diff changeset
1463 print("Allele modes only support raw reads datatype, i.e. '-t 1 or 2 or 3'; please use '-m k'")
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cstrittmatter
parents:
diff changeset
1464 elif analysis_mode=="k":
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cstrittmatter
parents:
diff changeset
1465 #ex_dir = os.path.dirname(os.path.realpath(__file__))
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cstrittmatter
parents:
diff changeset
1466 ex_dir = os.path.abspath(os.path.join(os.path.dirname(os.path.dirname(__file__)),'seqsero2_db')) # ed_SL_09152019: change ex_dir for packaging
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cstrittmatter
parents:
diff changeset
1467 #output_mode = args.mode
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cstrittmatter
parents:
diff changeset
1468 for_fq,rev_fq=get_input_files(make_dir,input_file,data_type,dirpath)
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cstrittmatter
parents:
diff changeset
1469 input_file = for_fq #-k will just use forward because not all reads were used
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cstrittmatter
parents:
diff changeset
1470 os.chdir(make_dir)
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cstrittmatter
parents:
diff changeset
1471 f = open(ex_dir + '/antigens.pickle', 'rb')
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cstrittmatter
parents:
diff changeset
1472 lib_dict = pickle.load(f)
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cstrittmatter
parents:
diff changeset
1473 f.close
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cstrittmatter
parents:
diff changeset
1474 input_Ks=get_input_K(input_file,lib_dict,data_type,k_size)
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cstrittmatter
parents:
diff changeset
1475 O_dict,H_dict,Special_dict=get_kmer_dict(lib_dict,input_Ks)
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cstrittmatter
parents:
diff changeset
1476 highest_O,highest_fliC,highest_fljB=call_O_and_H_type(O_dict,H_dict,Special_dict,make_dir)
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cstrittmatter
parents:
diff changeset
1477 subspecies=judge_subspecies_Kmer(Special_dict)
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cstrittmatter
parents:
diff changeset
1478 if subspecies=="IIb" or subspecies=="IIa":
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cstrittmatter
parents:
diff changeset
1479 subspecies="II"
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cstrittmatter
parents:
diff changeset
1480 predict_form,predict_sero,star,star_line,claim = seqsero_from_formula_to_serotypes(
e6437d423693 planemo upload commit 70dc513aa7d7ac6785847dfd86323687613b6b68-dirty
cstrittmatter
parents:
diff changeset
1481 highest_O.split('-')[1], highest_fliC, highest_fljB, Special_dict,subspecies)
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cstrittmatter
parents:
diff changeset
1482 claim="" #no claim any more based on new output requirement
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cstrittmatter
parents:
diff changeset
1483 #if star_line+claim=="": #0413, new output style
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cstrittmatter
parents:
diff changeset
1484 # note=""
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cstrittmatter
parents:
diff changeset
1485 #else:
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cstrittmatter
parents:
diff changeset
1486 # note="Note:"
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cstrittmatter
parents:
diff changeset
1487
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cstrittmatter
parents:
diff changeset
1488 ### ed_SL_11232019: add notes for missing antigen
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cstrittmatter
parents:
diff changeset
1489 if highest_O.split('-')[-1]=="":
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cstrittmatter
parents:
diff changeset
1490 O_choice="-"
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cstrittmatter
parents:
diff changeset
1491 else:
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cstrittmatter
parents:
diff changeset
1492 O_choice=highest_O.split('-')[-1]
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cstrittmatter
parents:
diff changeset
1493 antigen_note,NA_note=check_antigens(subspecies,O_choice,highest_fliC,highest_fljB,NA_note)
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cstrittmatter
parents:
diff changeset
1494 if sample_name:
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cstrittmatter
parents:
diff changeset
1495 print ("Sample name:\t"+sample_name)
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cstrittmatter
parents:
diff changeset
1496 ###
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cstrittmatter
parents:
diff changeset
1497
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cstrittmatter
parents:
diff changeset
1498 if clean_mode:
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1499 subprocess.check_call("rm -rf ../"+make_dir,shell=True)
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1500 make_dir="none-output-directory due to '-c' flag"
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1501 # ### ed_SL_05282019, fix the assignment issue of variable 'O_choice' using "-m k -c"
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1502 # if highest_O.split('-')[-1]=="":
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1503 # O_choice="-"
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1504 # else:
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1505 # O_choice=highest_O.split('-')[-1]
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1506 # ###
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1507 else:
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1508 # if highest_O.split('-')[-1]=="":
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1509 # O_choice="-"
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1510 # else:
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1511 # O_choice=highest_O.split('-')[-1]
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1512 #print("Output_directory:"+make_dir+"\tInput_file:"+input_file+"\tPredicted subpecies:"+subspecies + '\tPredicted antigenic profile:' + predict_form + '\tPredicted serotype(s):' + predict_sero)
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1513 new_file=open("SeqSero_result.txt","w")
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1514 #new_file.write("Output_directory:"+make_dir+"\nInput files:\t"+input_file+"\n"+"O antigen prediction:\t"+O_choice+"\n"+"H1 antigen prediction(fliC):\t"+highest_fliC+"\n"+"H2 antigen prediction(fljB):\t"+highest_fljB+"\n"+"Predicted antigenic profile:\t"+predict_form+"\n"+"Predicted subspecies:\t"+subspecies+"\n"+"Predicted serotype(s):\t"+predict_sero+star+"\n"+star+star_line+claim+"\n")#+##
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1515 ### ed_SL_01152020: add new output
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1516 tsv_file=open("SeqSero_result.tsv","w")
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1517 if ingore_header:
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1518 pass
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1519 else:
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1520 tsv_file.write("Sample name\tOutput directory\tInput files\tO antigen prediction\tH1 antigen prediction(fliC)\tH2 antigen prediction(fljB)\tPredicted subspecies\tPredicted antigenic profile\tPredicted serotype\tNote\n")
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1521 if sample_name:
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1522 new_file.write("Sample name:\t"+sample_name+"\n")
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1523 tsv_file.write(sample_name+'\t')
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1524 else:
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1525 tsv_file.write(input_file.split('/')[-1]+'\t')
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1526 ###
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1527 if "N/A" not in predict_sero:
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1528 new_file.write("Output directory:\t"+make_dir+"\n"+
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1529 "Input files:\t"+input_file+"\n"+
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1530 "O antigen prediction:\t"+O_choice+"\n"+
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1531 "H1 antigen prediction(fliC):\t"+highest_fliC+"\n"+
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1532 "H2 antigen prediction(fljB):\t"+highest_fljB+"\n"+
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1533 "Predicted subspecies:\t"+subspecies+"\n"+
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1534 "Predicted antigenic profile:\t"+predict_form+"\n"+
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1535 "Predicted serotype:\t"+predict_sero+"\n"+
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1536 note+star_line+claim+antigen_note+"\n")#+##
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1537 tsv_file.write(make_dir+"\t"+input_file+"\t"+O_choice+"\t"+highest_fliC+"\t"+highest_fljB+"\t"+subspecies+"\t"+predict_form+"\t"+predict_sero+"\t"+star_line+claim+antigen_note+"\n")
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1538 else:
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1539 #star_line=star_line.strip()+"\tNone such antigenic formula in KW.\n"
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1540 star_line = "" #changed for new output requirement, 04132019
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1541 new_file.write("Output directory:\t"+make_dir+"\n"+
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1542 "Input files:\t"+input_file+"\n"+
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1543 "O antigen prediction:\t"+O_choice+"\n"+
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1544 "H1 antigen prediction(fliC):\t"+highest_fliC+"\n"+
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1545 "H2 antigen prediction(fljB):\t"+highest_fljB+"\n"+
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1546 "Predicted subspecies:\t"+subspecies+"\n"+
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1547 "Predicted antigenic profile:\t"+predict_form+"\n"+
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1548 "Predicted serotype:\t"+subspecies+' '+predict_form+"\n"+ # add serotype output for "N/A" prediction, subspecies
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1549 note+NA_note+star_line+claim+antigen_note+"\n")#+##
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1550 tsv_file.write(make_dir+"\t"+input_file+"\t"+O_choice+"\t"+highest_fliC+"\t"+highest_fljB+"\t"+subspecies+"\t"+predict_form+"\t"+subspecies+' '+predict_form+"\t"+NA_note+star_line+claim+antigen_note+"\n")
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1551 new_file.close()
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1552 tsv_file.close()
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1553 subprocess.call("rm *.fasta* *.fastq *.gz *.fq temp.txt *.sra 2> /dev/null",shell=True)
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1554 if "N/A" not in predict_sero:
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1555 print("Output directory:\t"+make_dir+"\n"+
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1556 "Input files:\t"+input_file+"\n"+
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1557 "O antigen prediction:\t"+O_choice+"\n"+
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1558 "H1 antigen prediction(fliC):\t"+highest_fliC+"\n"+
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1559 "H2 antigen prediction(fljB):\t"+highest_fljB+"\n"+
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1560 "Predicted subspecies:\t"+subspecies+"\n"+
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1561 "Predicted antigenic profile:\t"+predict_form+"\n"+
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1562 "Predicted serotype:\t"+predict_sero+"\n"+
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1563 note+star_line+claim+antigen_note+"\n")#+##
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1564 else:
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1565 print("Output directory:\t"+make_dir+"\n"+
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1566 "Input files:\t"+input_file+"\n"+
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1567 "O antigen prediction:\t"+O_choice+"\n"+
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1568 "H1 antigen prediction(fliC):\t"+highest_fliC+"\n"+
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1569 "H2 antigen prediction(fljB):\t"+highest_fljB+"\n"+
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1570 "Predicted subspecies:\t"+subspecies+"\n"+
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1571 "Predicted antigenic profile:\t"+predict_form+"\n"+
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1572 "Predicted serotype:\t"+subspecies+' '+predict_form+"\n"+ # add serotype output for "N/A" prediction, subspecies
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1573 note+NA_note+star_line+claim+antigen_note+"\n")#+##
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1574
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1575 if __name__ == '__main__':
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1576 main()