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9
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1 #!/usr/bin/python
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2
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3 import re
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4 import sys
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5 import optparse
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6 import csv
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7 import re
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8 import pprint
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9 from decimal import *
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10 from rpy import *
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11
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12 def main():
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13 csv.field_size_limit(1000000000)
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14
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15 parser = optparse.OptionParser()
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16 parser.add_option('-v', '--sample_vcf', dest = 'sample_vcf', action = 'store', type = 'string', default = None, help = "Sample VCF from GATK Unified Genotyper")
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17 parser.add_option('-l', '--loess_span', dest = 'loess_span', action = 'store', type = 'float', default = .1, help = "Loess span")
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18 parser.add_option('-d', '--d_yaxis', dest = 'd_yaxis', action = 'store', type = 'float', default = 1, help = "y-axis upper limit for dot plot")
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19 parser.add_option('-y', '--h_yaxis', dest = 'h_yaxis', action = 'store', type = 'int', default = 0, help = "y-axis upper limit for histogram plot")
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20 parser.add_option('-c', '--points_color', dest = 'points_color', action = 'store', type = 'string', default = "gray27", help = "Color for data points")
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21 parser.add_option('-k', '--loess_color', dest = 'loess_color', action = 'store', type = 'string', default = "green2", help = "Color for loess regression line")
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22 parser.add_option('-z', '--standardize', dest = 'standardize', default= 'true', help = "Standardize X-axis")
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23 parser.add_option('-b', '--break_file', dest = 'break_file', action = 'store', type = 'string', default = 'C.elegans', help = "File defining the breaks per chromosome")
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24 parser.add_option('-x', '--bin_size', dest = 'bin_size', action = 'store', type = 'int', default = 1000000, help = "Size of histogram bins, default is 1mb")
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25 parser.add_option('-n', '--normalize_bins', dest = 'normalize_bins', default= 'true', help = "Normalize histograms")
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26
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27 parser.add_option('-o', '--output', dest = 'output', action = 'store', type = 'string', default = None, help = "Output file name")
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28 parser.add_option('-s', '--location_plot_output', dest = 'location_plot_output', action = 'store', type = 'string', default = "SNP_Mapping_Plot.pdf", help = "Output file name of SNP plots by chromosomal location")
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29
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30 (options, args) = parser.parse_args()
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31
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32 vcf_info = parse_vcf(sample_vcf = options.sample_vcf)
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33
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34 output_vcf_info(output = options.output, vcf_info = vcf_info)
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35
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36 #output plot with all ratios
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37 rounded_bin_size = int(round((float(options.bin_size) / 1000000), 1) * 1000000)
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38
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39 normalized_histogram_bins_per_mb = calculate_normalized_histogram_bins_per_xbase(vcf_info = vcf_info, xbase = rounded_bin_size, normalize_bins = options.normalize_bins)
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40 max_y_hist_mb = normalized_histogram_bins_per_mb[max(normalized_histogram_bins_per_mb, key = lambda x: normalized_histogram_bins_per_mb.get(x) )]
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41
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42 normalized_histogram_bins_per_5kb = calculate_normalized_histogram_bins_per_xbase(vcf_info = vcf_info, xbase = (rounded_bin_size / 2), normalize_bins = options.normalize_bins)
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43 max_y_hist_5kb = normalized_histogram_bins_per_5kb[max(normalized_histogram_bins_per_5kb, key = lambda x: normalized_histogram_bins_per_5kb.get(x) )]
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44
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45 max_y_hist_overall = myround(max(max_y_hist_mb, max_y_hist_5kb) + int(round(round(max(max_y_hist_mb, max_y_hist_5kb)) * .1)))
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46
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47
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48 break_dict = parse_breaks(break_file = options.break_file)
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49
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50 output_scatter_plots_by_location(location_plot_output = options.location_plot_output, vcf_info = vcf_info, loess_span=options.loess_span, d_yaxis=options.d_yaxis, h_yaxis=options.h_yaxis, points_color=options.points_color, loess_color=options.loess_color, standardize =options.standardize, normalized_hist_per_mb = normalized_histogram_bins_per_mb, normalized_hist_per_5kb = normalized_histogram_bins_per_5kb, breaks = break_dict, rounded_bin_size = rounded_bin_size, max_y_hist_overall = max_y_hist_overall)
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51
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52 def myround(x, base=10):
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53 return int(base * round(float(x)/base))
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54
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55 def skip_headers(reader = None, i_file = None):
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56 # count headers
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57 comment = 0
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58 while reader.next()[0].startswith('#'):
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59 comment = comment + 1
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60
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61 # skip headers
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62 i_file.seek(0)
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63 for i in range(0, comment):
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64 reader.next()
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65
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66 def parse_breaks(break_file = None):
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67 if break_file == 'C.elegans':
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68 break_dict = { 'I' : 16 , 'II' : 16, 'III' : 14, 'IV' : 18, 'V' : 21, 'X' : 18 }
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69 return break_dict
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70 elif break_file == 'Brachypodium':
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71 break_dict = { '1' : 75 , '2' : 60, '3' : 60, '4' : 50, '5' : 30 }
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72 return break_dict
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73 elif break_file == 'Arabadopsis':
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74 break_dict = { '1' : 31 , '2' : 20, '3' : 24, '4' : 19, '5' : 27 }
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75 return break_dict
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76 else:
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77 i_file = open(break_file, 'rU')
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78 break_dict = {}
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79 reader = csv.reader(i_file, delimiter = '\t')
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80 for row in reader:
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81 chromosome = row[0].upper()
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82 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
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83 chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE)
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84 break_count = row[1]
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85 break_dict[chromosome] = int(break_count)
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86 return break_dict
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87
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88
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89 def location_comparer(location_1, location_2):
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90 chr_loc_1 = location_1.split(':')[0]
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91 pos_loc_1 = int(location_1.split(':')[1])
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92
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93 chr_loc_2 = location_2.split(':')[0]
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94 pos_loc_2 = int(location_2.split(':')[1])
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95
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96 if chr_loc_1 == chr_loc_2:
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97 if pos_loc_1 < pos_loc_2:
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98 return -1
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99 elif pos_loc_1 == pos_loc_1:
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100 return 0
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101 elif pos_loc_1 > pos_loc_2:
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102 return 1
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103 elif chr_loc_1 < chr_loc_2:
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104 return -1
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105 elif chr_loc_1 > chr_loc_2:
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106 return 1
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107
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108 def output_vcf_info(output = None, vcf_info = None):
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109 o_file = open(output, 'wb')
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110 writer = csv.writer(o_file, delimiter = '\t')
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111
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112 writer.writerow(["#Chr\t", "Pos\t", "Alt Count\t", "Ref Count\t", "Read Depth\t", "Ratio\t"])
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113
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114 location_sorted_vcf_info_keys = sorted(vcf_info.keys(), cmp=location_comparer)
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115
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116 for location in location_sorted_vcf_info_keys:
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117 alt_allele_count, ref_allele_count, read_depth, ratio = vcf_info[location]
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118
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119 location_info = location.split(':')
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120 chromosome = location_info[0]
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121 position = location_info[1]
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122
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123 writer.writerow([chromosome, position, alt_allele_count, ref_allele_count, read_depth, ratio])
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124
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125 o_file.close()
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126
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127 def output_scatter_plots_by_location(location_plot_output = None, vcf_info = None, loess_span="", d_yaxis="", h_yaxis="", points_color="", loess_color="", standardize=None, normalized_hist_per_mb = None, normalized_hist_per_5kb = None, breaks = None, rounded_bin_size = 1000000, max_y_hist_overall = ""):
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128 positions = {}
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129 current_chr = ""
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130 prev_chr = ""
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131
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132 x_label = "Location (Mb)"
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133 filtered_label = ''
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134
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135 location_sorted_vcf_info_keys = sorted(vcf_info.keys(), cmp=location_comparer)
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136
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137 break_unit = Decimal(rounded_bin_size) / Decimal(1000000)
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138 max_breaks = max(breaks.values())
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139
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140 try:
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141 r.pdf(location_plot_output, 8, 8)
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142
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143 for location in location_sorted_vcf_info_keys:
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144 current_chr = location.split(':')[0]
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145 position = location.split(':')[1]
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146
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147 alt_allele_count, ref_allele_count, read_depth, ratio = vcf_info[location]
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148
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149 if prev_chr != current_chr:
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150 if prev_chr != "":
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151 hist_dict_mb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_mb, chr = prev_chr)
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152 hist_dict_5kb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_5kb, chr = prev_chr)
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153
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154 if h_yaxis == 0:
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155 plot_data(chr_dict = positions, hist_dict_mb = hist_dict_mb, hist_dict_5kb = hist_dict_5kb, chr = prev_chr + filtered_label, x_label = "Location (Mb)", divide_position = True, draw_secondary_grid_lines = True, loess_span=loess_span, d_yaxis=d_yaxis, h_yaxis=max_y_hist_overall, points_color=points_color, loess_color=loess_color, breaks = breaks[prev_chr], standardize=standardize, max_breaks = max_breaks, break_unit = break_unit)
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156 else:
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157 plot_data(chr_dict = positions, hist_dict_mb = hist_dict_mb, hist_dict_5kb = hist_dict_5kb, chr = prev_chr + filtered_label, x_label = "Location (Mb)", divide_position = True, draw_secondary_grid_lines = True, loess_span=loess_span, d_yaxis=d_yaxis, h_yaxis=h_yaxis, points_color=points_color, loess_color=loess_color, breaks = breaks[prev_chr], standardize=standardize, max_breaks = max_breaks, break_unit = break_unit)
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158
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159 prev_chr = current_chr
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160 positions = {}
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161
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162 positions[position] = ratio
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163
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164 hist_dict_mb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_mb, chr = current_chr)
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165 hist_dict_5kb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_5kb, chr = current_chr)
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166
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167 if h_yaxis == 0:
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168 plot_data(chr_dict = positions, hist_dict_mb = hist_dict_mb, hist_dict_5kb = hist_dict_5kb, chr = current_chr + filtered_label, x_label = "Location (Mb)", divide_position = True, draw_secondary_grid_lines = True, loess_span=loess_span, d_yaxis=d_yaxis, h_yaxis=max_y_hist_overall, points_color=points_color, loess_color=loess_color, breaks = breaks[current_chr], standardize=standardize, max_breaks = max_breaks, break_unit = break_unit)
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169 else:
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170 plot_data(chr_dict = positions, hist_dict_mb = hist_dict_mb, hist_dict_5kb = hist_dict_5kb, chr = current_chr + filtered_label, x_label = "Location (Mb)", divide_position = True, draw_secondary_grid_lines = True, loess_span=loess_span, d_yaxis=d_yaxis, h_yaxis=h_yaxis, points_color=points_color, loess_color=loess_color, breaks = breaks[current_chr], standardize=standardize, max_breaks = max_breaks, break_unit = break_unit)
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171
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172 r.dev_off()
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173
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174 except Exception as inst:
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175 print inst
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176 print "There was an error creating the location plot pdf... Please try again"
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177
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178 def get_hist_dict_by_chr(normalized_hist_per_xbase = None, chr = ''):
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179 hist_dict = {}
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180
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181 for location in normalized_hist_per_xbase:
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182 chromosome = location.split(':')[0]
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183 if chromosome == chr:
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184 position = int(location.split(':')[1])
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185 hist_dict[position] = normalized_hist_per_xbase[location]
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186
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187 max_location = max(hist_dict.keys(), key=int)
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188 for i in range(1, max_location):
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189 if i not in hist_dict:
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190 hist_dict[i] = 0
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191
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192 return hist_dict
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193
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194 def plot_data(chr_dict = None, hist_dict_mb = None, hist_dict_5kb = None, chr = "", x_label = "", divide_position = False, draw_secondary_grid_lines = False, loess_span=None, d_yaxis=None, h_yaxis=None, points_color="", loess_color="", breaks = None, standardize= None, max_breaks = 1, break_unit = 1):
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195 ratios = "c("
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196 positions = "c("
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197
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198 for position in chr_dict:
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199 ratio = chr_dict[position]
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200 if divide_position:
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201 position = float(position) / 1000000.0
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202 positions = positions + str(position) + ", "
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203 ratios = ratios + str(ratio) + ", "
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204
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205 if len(ratios) == 2:
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206 ratios = ratios + ")"
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207 else:
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208 ratios = ratios[0:len(ratios) - 2] + ")"
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209
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210 if len(positions) == 2:
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211 positions = positions + ")"
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212 else:
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213 positions = positions[0:len(positions) - 2] + ")"
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214
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215 r("x <- " + positions)
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216 r("y <- " + ratios)
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217
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218 hist_mb_values = "c("
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219 for position in sorted(hist_dict_mb):
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220 hist_mb_values = hist_mb_values + str(hist_dict_mb[position]) + ", "
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221
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222 if len(hist_mb_values) == 2:
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223 hist_mb_values = hist_mb_values + ")"
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224 else:
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225 hist_mb_values = hist_mb_values[0:len(hist_mb_values) - 2] + ")"
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226
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227 hist_5kb_values = "c("
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228 for position in sorted(hist_dict_5kb):
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229 hist_5kb_values = hist_5kb_values + str(hist_dict_5kb[position]) + ", "
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230
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231 if len(hist_5kb_values) == 2:
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232 hist_5kb_values = hist_5kb_values + ")"
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233 else:
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234 hist_5kb_values = hist_5kb_values[0:len(hist_5kb_values) - 2] + ")"
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235
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236 r("xz <- " + hist_mb_values)
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237 r("yz <- " + hist_5kb_values)
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238
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239
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240 max_break_str = str(max_breaks)
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241 break_unit_str = str(Decimal(break_unit))
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242 half_break_unit_str = str(Decimal(break_unit) / Decimal(2))
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243 break_penta_unit_str = str(Decimal(break_unit) * Decimal(5))
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244
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245 if (standardize=='true'):
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246 r("plot(x, y, ,cex=0.60, xlim=c(0," + max_break_str + "), main='LG " + chr + " (Variant Discovery Mapping)', xlab= '" + x_label + "', ylim = c(0, %f " %d_yaxis + "), ylab='Ratios of variant reads/total reads (at variant positions)', pch=10, col='"+ points_color +"')")
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247 r("lines(loess.smooth(x, y, span = %f "%loess_span + "), lwd=5, col='"+ loess_color +"')")
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248 r("axis(1, at=seq(0, " + max_break_str + ", by=" + break_unit_str + "), labels=FALSE, tcl=-0.5)")
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249 r("axis(1, at=seq(0, " + max_break_str + ", by=" + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
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250 r("axis(2, at=seq(floor(min(y)), 1, by=0.1), labels=FALSE, tcl=-0.2)")
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251 elif (standardize=='false'):
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252 r("plot(x, y, cex=0.60, main='LG " + chr + " (Variant Discovery Mapping)', xlab= '" + x_label + "', ylim = c(0, %f " %d_yaxis + "), ylab='Ratios of variant reads/total reads (at variant positions)', pch=10, col='"+ points_color +"')")
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253 r("lines(loess.smooth(x, y, span = %f "%loess_span + "), lwd=5, col='"+ loess_color +"')")
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254 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)")
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255 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
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256 r("axis(2, at=seq(floor(min(y)), 1, by=0.1), labels=FALSE, tcl=-0.2)")
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257
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258 if draw_secondary_grid_lines:
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259 r("abline(h = seq(floor(min(y)), 1, by=0.1), v = seq(floor(min(x)), length(x), by= 1), col='gray')")
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260 else:
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261 r("grid(lty = 1, col = 'gray')")
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262
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263 if (standardize=='true'):
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264 r("barplot(xz, xlim=c(0, " + max_break_str + "), ylim = c(0, " + str(h_yaxis) + "), yaxp=c(0, " + str(h_yaxis) + ", 1), space = 0, col='darkgray', width = " + break_unit_str + ", xlab='Location (Mb)', ylab='Normalized frequency of pure parental alleles ', main='LG " + chr + " (Variant Discovery Mapping)')")
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265 r("barplot(yz, space = 0, add=TRUE, width = " + half_break_unit_str + ", col='green2')")
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266 r("axis(1, hadj = 1, at=seq(0, " + max_break_str + ", by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)")
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267 r("axis(1, at=seq(0, " + max_break_str + ", by= " + break_penta_unit_str + "), labels=TRUE, tcl=-0.5)")
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268 r("axis(1, at=seq(0, " + max_break_str + ", by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
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269 elif (standardize=='false'):
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270 r("barplot(xz, ylim = c(0, " + str(h_yaxis) + "), yaxp=c(0, " + str(h_yaxis) + ", 1), space = 0, col='darkgray', width = 1, xlab='Location (Mb)', ylab='Normalized frequency of pure parental alleles ', main='LG " + chr + " (Variant Discovery Mapping)')")
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271 r("barplot(yz, space = 0, add=TRUE, width = 0.5, col='green2')")
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272 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)")
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273 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_penta_unit_str + "), labels=TRUE, tcl=-0.5)")
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274 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
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275
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276
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277
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278 def calculate_normalized_histogram_bins_per_xbase(vcf_info = None, xbase = 1000000, normalize_bins = None):
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279 normalized_histogram_bins_per_xbase = {}
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280
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281 ref_snp_count_per_xbase = get_ref_snp_count_per_xbase(vcf_info = vcf_info, xbase = xbase)
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282 mean_one_ratio_snp_count_per_chromosome = get_mean_one_ratio_snp_count_per_chromosome(vcf_info = vcf_info, xbase = xbase)
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283 one_ratio_snp_count_per_xbase = get_one_ratio_snp_count_per_xbase(vcf_info = vcf_info, xbase = xbase)
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284
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285 for location in ref_snp_count_per_xbase:
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286 chromosome = location.split(':')[0]
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287 mean_one_ratio_snp_count = mean_one_ratio_snp_count_per_chromosome[chromosome]
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288 ref_snp_count = ref_snp_count_per_xbase[location]
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289
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290 one_ratio_snp_count = 0
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291 if location in one_ratio_snp_count_per_xbase:
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292 one_ratio_snp_count = one_ratio_snp_count_per_xbase[location]
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293
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294 if normalize_bins == 'true':
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295 if one_ratio_snp_count == 0:
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296 normalized_histogram_bins_per_xbase[location] = 0
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297 elif one_ratio_snp_count == ref_snp_count:
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298 normalized_histogram_bins_per_xbase[location] = (Decimal(one_ratio_snp_count**2) * Decimal(mean_one_ratio_snp_count))
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299 else:
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300 normalized_histogram_bins_per_xbase[location] = (Decimal(one_ratio_snp_count**2) / (Decimal(ref_snp_count)-Decimal(one_ratio_snp_count))) * Decimal(mean_one_ratio_snp_count)
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301 else:
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302 normalized_histogram_bins_per_xbase[location] = one_ratio_snp_count
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303
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304 return normalized_histogram_bins_per_xbase
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305
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306
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307 def get_ref_snp_count_per_xbase(vcf_info = None, xbase = 1000000):
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308 ref_snps_per_xbase = {}
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309
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310 for location in vcf_info:
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311 location_info = location.split(':')
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312
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313 chromosome = location_info[0].upper()
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314 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
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315 chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE)
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316
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317 position = location_info[1]
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318 xbase_position = (int(position) / xbase) + 1
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319
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320 location = chromosome + ":" + str(xbase_position)
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321 if location in ref_snps_per_xbase:
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322 ref_snps_per_xbase[location] = ref_snps_per_xbase[location] + 1
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323 else:
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324 ref_snps_per_xbase[location] = 1
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325
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326 return ref_snps_per_xbase
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327
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328
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329
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330 def get_mean_one_ratio_snp_count_per_chromosome(vcf_info, xbase = 1000000):
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331 sample_snp_count_per_xbase = {}
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332
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333 for location in vcf_info:
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334 alt_allele_count, ref_allele_count, read_depth, ratio = vcf_info[location]
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335
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336 location_info = location.split(':')
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337 chromosome = location_info[0]
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338 position = location_info[1]
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339 xbase_position = (int(position) / xbase) + 1
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340 xbase_location = chromosome + ":" + str(xbase_position)
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341
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342 if ratio == 1:
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343 if xbase_location in sample_snp_count_per_xbase:
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344 sample_snp_count_per_xbase[xbase_location] = sample_snp_count_per_xbase[xbase_location] + 1
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345 else:
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346 sample_snp_count_per_xbase[xbase_location] = 1
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347
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348 elif ratio != 1 and xbase_location not in sample_snp_count_per_xbase:
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349 sample_snp_count_per_xbase[xbase_location] = 0
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350
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351 mean_one_ratio_snp_count_per_chromosome = {}
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352 for location in sample_snp_count_per_xbase:
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353 chromosome = location.split(':')[0]
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354 sample_count = sample_snp_count_per_xbase[location]
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355 if chromosome in mean_one_ratio_snp_count_per_chromosome:
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356 mean_one_ratio_snp_count_per_chromosome[chromosome].append(sample_count)
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357 else:
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358 mean_one_ratio_snp_count_per_chromosome[chromosome] = [sample_count]
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359
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360 for chromosome in mean_one_ratio_snp_count_per_chromosome:
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361 summa = sum(mean_one_ratio_snp_count_per_chromosome[chromosome])
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362 count = len(mean_one_ratio_snp_count_per_chromosome[chromosome])
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363
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364 mean_one_ratio_snp_count_per_chromosome[chromosome] = Decimal(summa) / Decimal(count)
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365
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366 return mean_one_ratio_snp_count_per_chromosome
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367
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368
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369 def get_one_ratio_snp_count_per_xbase(vcf_info = None, xbase = 1000000):
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370 one_ratio_snp_count_per_xbase = {}
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371
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372 for location in vcf_info:
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373 alt_allele_count, ref_allele_count, read_depth, ratio = vcf_info[location]
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374
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375 location_info = location.split(':')
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376 chromosome = location_info[0]
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377 position = location_info[1]
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378 xbase_position = (int(position) / xbase) + 1
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379 xbase_location = chromosome + ":" + str(xbase_position)
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380
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381 if ratio == 1:
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382 if xbase_location in one_ratio_snp_count_per_xbase:
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383 one_ratio_snp_count_per_xbase[xbase_location] = one_ratio_snp_count_per_xbase[xbase_location] + 1
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384 else:
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385 one_ratio_snp_count_per_xbase[xbase_location] = 1
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386
|
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387 elif ratio != 1 and xbase_location not in one_ratio_snp_count_per_xbase:
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388 one_ratio_snp_count_per_xbase[xbase_location] = 0
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389
|
|
|
390 return one_ratio_snp_count_per_xbase
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391
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|
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392
|
|
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393 def parse_vcf(sample_vcf = None):
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|
394 i_file = open(sample_vcf, 'rU')
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|
395 reader = csv.reader(i_file, delimiter = '\t', quoting = csv.QUOTE_NONE)
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396
|
|
|
397 skip_headers(reader = reader, i_file = i_file)
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|
398 vcf_info = {}
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|
399
|
|
|
400 for row in reader:
|
|
|
401 chromosome = row[0].upper()
|
|
|
402 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
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|
|
403 chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE)
|
|
|
404
|
|
|
405
|
|
|
406 if chromosome != 'MTDNA':
|
|
|
407 position = row[1]
|
|
|
408 #ref_allele = row[2]
|
|
|
409 #read_depth = row[3]
|
|
|
410 #read_bases = row[4]
|
|
|
411
|
|
|
412 vcf_format_info = row[8].split(":")
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|
|
413 vcf_allele_freq_data = row[9]
|
|
|
414
|
|
|
415 read_depth_data_index = vcf_format_info.index("DP")
|
|
|
416 read_depth = vcf_allele_freq_data.split(":")[read_depth_data_index]
|
|
|
417
|
|
|
418 ref_and_alt_counts_data_index = vcf_format_info.index("AD")
|
|
|
419 ref_and_alt_counts = vcf_allele_freq_data.split(":")[ref_and_alt_counts_data_index]
|
|
|
420 ref_allele_count = ref_and_alt_counts.split(",")[0]
|
|
|
421 alt_allele_count = ref_and_alt_counts.split(",")[1]
|
|
|
422
|
|
|
423 location = chromosome + ":" + position
|
|
|
424
|
|
|
425 if Decimal(read_depth!=0):
|
|
|
426 getcontext().prec = 6
|
|
|
427 ratio = Decimal(alt_allele_count) / Decimal(read_depth)
|
|
|
428
|
|
|
429 vcf_info[location] = (alt_allele_count, ref_allele_count, read_depth, ratio)
|
|
|
430
|
|
|
431 #debug line
|
|
|
432 #print chromosome, position, read_depth, ref_allele_count, alt_allele_count, ratio, id
|
|
|
433
|
|
|
434 i_file.close()
|
|
|
435
|
|
|
436 return vcf_info
|
|
|
437
|
|
|
438 def parse_read_bases(read_bases = None, alt_allele = None):
|
|
|
439 read_bases = re.sub('\$', '', read_bases)
|
|
|
440 read_bases = re.sub('\^[^\s]', '', read_bases)
|
|
|
441
|
|
|
442 ref_allele_matches = re.findall("\.|\,", read_bases)
|
|
|
443 ref_allele_count = len(ref_allele_matches)
|
|
|
444
|
|
|
445 alt_allele_matches = re.findall(alt_allele, read_bases, flags = re.IGNORECASE)
|
|
|
446 alt_allele_count = len(alt_allele_matches)
|
|
|
447
|
|
|
448 #debug line
|
|
|
449 #print read_bases, alt_allele, alt_allele_count, ref_allele_count
|
|
|
450
|
|
|
451 return ref_allele_count, alt_allele_count
|
|
|
452
|
|
|
453 if __name__ == "__main__":
|
|
|
454 main()
|
