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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('-p', '--sample_pileup', dest = 'sample_pileup', action = 'store', type = 'string', default = None, help = "Sample pileup from mpileup")
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17 parser.add_option('-v', '--haw_vcf', dest = 'haw_vcf', action = 'store', type = 'string', default = None, help = "vcf file of Hawaiian SNPs")
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18 parser.add_option('-l', '--loess_span', dest = 'loess_span', action = 'store', type = 'float', default = .01, help = "Loess span")
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19 parser.add_option('-d', '--d_yaxis', dest = 'd_yaxis', action = 'store', type = 'float', default = .7, help = "y-axis upper limit for dot plot")
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20 parser.add_option('-y', '--h_yaxis', dest = 'h_yaxis', action = 'store', type = 'int', default = 5, help = "y-axis upper limit for histogram plot")
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21 parser.add_option('-c', '--points_color', dest = 'points_color', action = 'store', type = 'string', default = "gray27", help = "Color for data points")
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22 parser.add_option('-k', '--loess_color', dest = 'loess_color', action = 'store', type = 'string', default = "red", help = "Color for loess regression line")
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23 parser.add_option('-z', '--standardize', dest = 'standardize', default= 'true', help = "Standardize X-axis")
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24 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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25 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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26 #parser.add_option('-n', '--normalize_bins', dest = 'normalize_bins', action = 'store_true', help = "Normalize histograms")
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27 parser.add_option('-n', '--normalize_bins', dest = 'normalize_bins', default= 'true', help = "Normalize histograms")
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28
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29
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30 parser.add_option('-o', '--output', dest = 'output', action = 'store', type = 'string', default = None, help = "Output file name")
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31 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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32
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33 #For plotting with map units on the X-axis instead of physical distance
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34 #parser.add_option('-u', '--mpu_plot_output', dest = 'mpu_plot_output', action = 'store', type = 'string', default = None, help = "Output file name of SNP plots by map unit location")
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35 (options, args) = parser.parse_args()
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36
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37 haw_snps = build_haw_snp_dictionary(haw_vcf = options.haw_vcf)
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38 pileup_info = parse_pileup(sample_pileup = options.sample_pileup, haw_snps = haw_snps)
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39
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40 output_pileup_info(output = options.output, pileup_info = pileup_info)
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41
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42 #output plot with all ratios
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43 rounded_bin_size = int(round((float(options.bin_size) / 1000000), 1) * 1000000)
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44
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45 normalized_histogram_bins_per_mb = calculate_normalized_histogram_bins_per_xbase(pileup_info = pileup_info, xbase = rounded_bin_size, normalize_bins = options.normalize_bins)
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46 normalized_histogram_bins_per_5kb = calculate_normalized_histogram_bins_per_xbase(pileup_info = pileup_info, xbase = (rounded_bin_size / 2), normalize_bins = options.normalize_bins)
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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, pileup_info = pileup_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)
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51
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52 #For plotting with map units on the X-axis instead of physical distance)
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53 #output_scatter_plots_by_mapping_units(mpu_plot_output = options.mpu_plot_output, pileup_info = pileup_info)
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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 == 'Arabadopsis':
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71 break_dict = { '1' : 16 , '2' : 16, '3' : 21, '4' : 18, '5' : 21 }
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72 return break_dict
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73 else:
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74 i_file = open(break_file, 'rU')
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75 break_dict = {}
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76 reader = csv.reader(i_file, delimiter = '\t')
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77 for row in reader:
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78 chromosome = row[0].upper()
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79 chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE)
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80 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
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81 break_count = row[1]
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82 break_dict[chromosome] = int(break_count)
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83 return break_dict
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84
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85
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86 def location_comparer(location_1, location_2):
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87 chr_loc_1 = location_1.split(':')[0]
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88 pos_loc_1 = int(location_1.split(':')[1])
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89
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90 chr_loc_2 = location_2.split(':')[0]
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91 pos_loc_2 = int(location_2.split(':')[1])
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92
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93 if chr_loc_1 == chr_loc_2:
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94 if pos_loc_1 < pos_loc_2:
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95 return -1
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96 elif pos_loc_1 == pos_loc_1:
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97 return 0
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98 elif pos_loc_1 > pos_loc_2:
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99 return 1
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100 elif chr_loc_1 < chr_loc_2:
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101 return -1
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102 elif chr_loc_1 > chr_loc_2:
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103 return 1
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104
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105 def output_pileup_info(output = None, pileup_info = None):
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106 o_file = open(output, 'wb')
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107 writer = csv.writer(o_file, delimiter = '\t')
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108
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109 writer.writerow(["#Chr\t", "Pos\t", "ID\t", "Alt Count\t", "Ref Count\t", "Read Depth\t", "Ratio\t", "Mapping Unit"])
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110
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111 location_sorted_pileup_info_keys = sorted(pileup_info.keys(), cmp=location_comparer)
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112
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113 for location in location_sorted_pileup_info_keys:
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114 alt_allele_count, ref_allele_count, read_depth, ratio, haw_snp_id, mapping_unit = pileup_info[location]
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115
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116 location_info = location.split(':')
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117 chromosome = location_info[0]
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118 position = location_info[1]
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119
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120 writer.writerow([chromosome, position, haw_snp_id, alt_allele_count, ref_allele_count, read_depth, ratio, mapping_unit])
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121
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122 o_file.close()
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123
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124 def output_scatter_plots_by_location(location_plot_output = None, pileup_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):
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125 positions = {}
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126 current_chr = ""
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127 prev_chr = ""
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128
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129 x_label = "Location (Mb)"
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130 filtered_label = ''
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131
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132 location_sorted_pileup_info_keys = sorted(pileup_info.keys(), cmp=location_comparer)
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133
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134 break_unit = Decimal(rounded_bin_size) / Decimal(1000000)
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135 max_breaks = max(breaks.values())
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136
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137 try:
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138 r.pdf(location_plot_output, 8, 8)
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139
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140 for location in location_sorted_pileup_info_keys:
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141 current_chr = location.split(':')[0]
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142 position = location.split(':')[1]
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143
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144 alt_allele_count, ref_allele_count, read_depth, ratio, haw_snp_id, mapping_unit = pileup_info[location]
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145
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146 if prev_chr != current_chr:
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147 if prev_chr != "":
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148 hist_dict_mb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_mb, chr = prev_chr)
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149 hist_dict_5kb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_5kb, chr = prev_chr)
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150
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151 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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152
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153 prev_chr = current_chr
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154 positions = {}
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155
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156 positions[position] = ratio
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157
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158 hist_dict_mb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_mb, chr = current_chr)
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159 hist_dict_5kb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_5kb, chr = current_chr)
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160
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161 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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162
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163 r.dev_off()
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164
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165 except Exception as inst:
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166 print inst
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167 print "There was an error creating the location plot pdf... Please try again"
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168
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169 def get_hist_dict_by_chr(normalized_hist_per_xbase = None, chr = ''):
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170 hist_dict = {}
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171
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172 for location in normalized_hist_per_xbase:
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173 chromosome = location.split(':')[0]
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174 if chromosome == chr:
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175 position = int(location.split(':')[1])
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176 hist_dict[position] = normalized_hist_per_xbase[location]
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177
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178 return hist_dict
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179
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180 '''
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181 def output_scatter_plots_by_mapping_units(mpu_plot_output = None, pileup_info = None):
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182 i = {}
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183 ii = {}
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184 iii = {}
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185 iv = {}
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186 v = {}
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187 x = {}
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188
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189 for location in pileup_info:
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190 chromosome = location.split(':')[0]
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191 position = location.split(':')[1]
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192
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193 alt_allele_count, ref_allele_count, read_depth, ratio, haw_snp_id, mapping_unit = pileup_info[location]
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194
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195 if chromosome == "I":
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196 i[mapping_unit] = ratio
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197 elif chromosome == "II":
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198 ii[mapping_unit] = ratio
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199 elif chromosome == "III":
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200 iii[mapping_unit] = ratio
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201 elif chromosome == "IV":
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202 iv[mapping_unit] = ratio
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203 elif chromosome == "V":
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204 v[mapping_unit] = ratio
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205 elif chromosome == "X":
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206 x[mapping_unit] = ratio
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207
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208 x_label = "Map Units"
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209
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210 try:
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211 r.pdf(mpu_plot_output, 8, 8)
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212 plot_data(chr_dict = i, chr = "I", x_label = "Map Units")
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213 plot_data(chr_dict = ii, chr = "II", x_label = "Map Units")
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214 plot_data(chr_dict = iii, chr = "III", x_label = "Map Units")
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215 plot_data(chr_dict = iv, chr = "IV", x_label = "Map Units")
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216 plot_data(chr_dict = v, chr = "V", x_label = "Map Units")
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217 plot_data(chr_dict = x, chr = "X", x_label = "Map Units")
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218 r.dev_off()
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219 except Exception as inst:
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220 print inst
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221 print "There was an error creating the map unit plot pdf... Please try again"
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222 '''
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223
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224 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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225 ratios = "c("
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226 positions = "c("
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227
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228 for position in chr_dict:
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229 ratio = chr_dict[position]
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230 if divide_position:
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231 position = float(position) / 1000000.0
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232 positions = positions + str(position) + ", "
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233 ratios = ratios + str(ratio) + ", "
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234
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235 if len(ratios) == 2:
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236 ratios = ratios + ")"
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237 else:
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238 ratios = ratios[0:len(ratios) - 2] + ")"
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239
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240 if len(positions) == 2:
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241 positions = positions + ")"
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242 else:
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243 positions = positions[0:len(positions) - 2] + ")"
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244
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245 r("x <- " + positions)
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246 r("y <- " + ratios)
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247
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248 hist_mb_values = "c("
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249 for position in sorted(hist_dict_mb):
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250 hist_mb_values = hist_mb_values + str(hist_dict_mb[position]) + ", "
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251
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252 if len(hist_mb_values) == 2:
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253 hist_mb_values = hist_mb_values + ")"
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254 else:
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255 hist_mb_values = hist_mb_values[0:len(hist_mb_values) - 2] + ")"
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256
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257 hist_5kb_values = "c("
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258 for position in sorted(hist_dict_5kb):
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259 hist_5kb_values = hist_5kb_values + str(hist_dict_5kb[position]) + ", "
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260
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261 if len(hist_5kb_values) == 2:
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262 hist_5kb_values = hist_5kb_values + ")"
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263 else:
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264 hist_5kb_values = hist_5kb_values[0:len(hist_5kb_values) - 2] + ")"
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265
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266 r("xz <- " + hist_mb_values)
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267 r("yz <- " + hist_5kb_values)
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268
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269 max_break_str = str(max_breaks)
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270 break_unit_str = str(Decimal(break_unit))
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271 half_break_unit_str = str(Decimal(break_unit) / Decimal(2))
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272 break_penta_unit_str = str(Decimal(break_unit) * Decimal(5))
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273
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274 if (standardize=='true'):
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275 r("plot(x, y, ,cex=0.60, xlim=c(0," + max_break_str + "), main='LG " + chr + "', xlab= '" + x_label + "', ylim = c(0, %f " %d_yaxis + "), ylab='Ratios of mapping strain alleles/total reads (at SNP positions)', pch=18, col='"+ points_color +"')")
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276 r("lines(loess.smooth(x, y, span = %f "%loess_span + "), lwd=5, col='"+ loess_color +"')")
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277 r("axis(1, at=seq(0, " + max_break_str + ", by=" + break_unit_str + "), labels=FALSE, tcl=-0.5)")
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278 r("axis(1, at=seq(0, " + max_break_str + ", by=" + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
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279 r("axis(2, at=seq(floor(min(y)), 1, by=0.1), labels=FALSE, tcl=-0.2)")
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280 elif (standardize=='false'):
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281 r("plot(x, y, cex=0.60, main='LG " + chr + "', xlab= '" + x_label + "', ylim = c(0, %f " %d_yaxis + "), ylab='Ratios of mapping strain alleles/total reads (at SNP positions)', pch=18, col='"+ points_color +"')")
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282 r("lines(loess.smooth(x, y, span = %f "%loess_span + "), lwd=5, col='"+ loess_color +"')")
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283 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)")
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284 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
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285 r("axis(2, at=seq(floor(min(y)), 1, by=0.1), labels=FALSE, tcl=-0.2)")
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286
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287 if draw_secondary_grid_lines:
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288 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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289 else:
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290 r("grid(lty = 1, col = 'gray')")
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291
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292 if (standardize=='true'):
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293 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 + "')")
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294 r("barplot(yz, space = 0, add=TRUE, width = " + half_break_unit_str + ", col=rgb(1, 0, 0, 1))")
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295 r("axis(1, hadj = 1, at=seq(0, " + max_break_str + ", by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)")
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296 r("axis(1, at=seq(0, " + max_break_str + ", by= " + break_penta_unit_str + "), labels=TRUE, tcl=-0.5)")
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297 r("axis(1, at=seq(0, " + max_break_str + ", by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
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298 elif (standardize=='false'):
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299 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 + "')")
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300 r("barplot(yz, space = 0, add=TRUE, width = 0.5, col=rgb(1, 0, 0, 1))")
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301 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)")
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302 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_penta_unit_str + "), labels=TRUE, tcl=-0.5)")
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303 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
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304
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305
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306 def build_haw_snp_dictionary(haw_vcf = None):
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307 haw_snps = {}
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308
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309 i_file = open(haw_vcf, 'rU')
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310 reader = csv.reader(i_file, delimiter = '\t')
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311
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312 skip_headers(reader = reader, i_file = i_file)
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313
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314 for row in reader:
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315 #print row
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316 chromosome = row[0].upper()
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317 chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE)
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318 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
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319
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320 if chromosome != 'MTDNA':
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321 position = row[1]
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322 haw_snp_id = row[2]
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323 ref_allele = row[3]
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324 alt_allele = row[4]
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325
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326 info = row[7]
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327
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328 mapping_unit = info.replace("MPU=", "")
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329
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330 location = chromosome + ":" + position
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331 haw_snps[location] = (alt_allele, haw_snp_id, mapping_unit)
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332
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333 i_file.close()
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334
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335 return haw_snps
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336
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337 def calculate_normalized_histogram_bins_per_xbase(pileup_info = None, xbase = 1000000, normalize_bins = None):
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338 normalized_histogram_bins_per_xbase = {}
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339
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340 ref_snp_count_per_xbase = get_ref_snp_count_per_xbase(pileup_info = pileup_info, xbase = xbase)
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341 mean_zero_snp_count_per_chromosome = get_mean_zero_snp_count_per_chromosome(pileup_info = pileup_info, xbase = xbase)
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342 zero_snp_count_per_xbase = get_zero_snp_count_per_xbase(pileup_info = pileup_info, xbase = xbase)
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343
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344 for location in ref_snp_count_per_xbase:
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345 chromosome = location.split(':')[0]
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346 mean_zero_snp_count = mean_zero_snp_count_per_chromosome[chromosome]
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347 ref_snp_count = ref_snp_count_per_xbase[location]
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348
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349 zero_snp_count = 0
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350 if location in zero_snp_count_per_xbase:
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351 zero_snp_count = zero_snp_count_per_xbase[location]
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352
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353 if normalize_bins == 'true':
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354 if zero_snp_count == 0 or ref_snp_count == 0:
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355 normalized_histogram_bins_per_xbase[location] = 0
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356 elif zero_snp_count == ref_snp_count:
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357 normalized_histogram_bins_per_xbase[location] = 0
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358 else:
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359 normalized_histogram_bins_per_xbase[location] = (Decimal(zero_snp_count) / (Decimal(ref_snp_count)-Decimal(zero_snp_count))) * Decimal(mean_zero_snp_count)
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360 else:
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361 normalized_histogram_bins_per_xbase[location] = zero_snp_count
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362
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363 return normalized_histogram_bins_per_xbase
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364
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365 def get_ref_snp_count_per_xbase(pileup_info = None, xbase = 1000000):
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366 ref_snps_per_xbase = {}
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367
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368 for location in pileup_info:
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369 location_info = location.split(':')
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370
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371 chromosome = location_info[0].upper()
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372 chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE)
|
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373 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
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374
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375 position = location_info[1]
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376 xbase_position = (int(position) / xbase) + 1
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377
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378 location = chromosome + ":" + str(xbase_position)
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379 if location in ref_snps_per_xbase:
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380 ref_snps_per_xbase[location] = ref_snps_per_xbase[location] + 1
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381 else:
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382 ref_snps_per_xbase[location] = 1
|
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383
|
|
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384 return ref_snps_per_xbase
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385
|
|
|
386 def get_mean_zero_snp_count_per_chromosome(pileup_info, xbase = 1000000):
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|
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387 sample_snp_count_per_xbase = {}
|
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388
|
|
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389 for location in pileup_info:
|
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390 alt_allele_count, ref_allele_count, read_depth, ratio, haw_snp_id, mapping_unit = pileup_info[location]
|
|
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391
|
|
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392 location_info = location.split(':')
|
|
|
393 chromosome = location_info[0]
|
|
|
394 position = location_info[1]
|
|
|
395 xbase_position = (int(position) / xbase) + 1
|
|
|
396 xbase_location = chromosome + ":" + str(xbase_position)
|
|
|
397
|
|
|
398 if alt_allele_count == 0:
|
|
|
399 if xbase_location in sample_snp_count_per_xbase:
|
|
|
400 sample_snp_count_per_xbase[xbase_location] = sample_snp_count_per_xbase[xbase_location] + 1
|
|
|
401 else:
|
|
|
402 sample_snp_count_per_xbase[xbase_location] = 1
|
|
|
403
|
|
|
404 elif alt_allele_count != 0 and xbase_location not in sample_snp_count_per_xbase:
|
|
|
405 sample_snp_count_per_xbase[xbase_location] = 0
|
|
|
406
|
|
|
407 mean_zero_snp_count_per_chromosome = {}
|
|
|
408 for location in sample_snp_count_per_xbase:
|
|
|
409 chromosome = location.split(':')[0]
|
|
|
410 sample_count = sample_snp_count_per_xbase[location]
|
|
|
411 if chromosome in mean_zero_snp_count_per_chromosome:
|
|
|
412 mean_zero_snp_count_per_chromosome[chromosome].append(sample_count)
|
|
|
413 else:
|
|
|
414 mean_zero_snp_count_per_chromosome[chromosome] = [sample_count]
|
|
|
415
|
|
|
416 for chromosome in mean_zero_snp_count_per_chromosome:
|
|
|
417 summa = sum(mean_zero_snp_count_per_chromosome[chromosome])
|
|
|
418 count = len(mean_zero_snp_count_per_chromosome[chromosome])
|
|
|
419
|
|
|
420 mean_zero_snp_count_per_chromosome[chromosome] = Decimal(summa) / Decimal(count)
|
|
|
421
|
|
|
422 return mean_zero_snp_count_per_chromosome
|
|
|
423
|
|
|
424 def get_zero_snp_count_per_xbase(pileup_info = None, xbase = 1000000):
|
|
|
425 zero_snp_count_per_xbase = {}
|
|
|
426
|
|
|
427 for location in pileup_info:
|
|
|
428 alt_allele_count, ref_allele_count, read_depth, ratio, haw_snp_id, mapping_unit = pileup_info[location]
|
|
|
429
|
|
|
430 location_info = location.split(':')
|
|
|
431 chromosome = location_info[0]
|
|
|
432 position = location_info[1]
|
|
|
433 xbase_position = (int(position) / xbase) + 1
|
|
|
434 xbase_location = chromosome + ":" + str(xbase_position)
|
|
|
435
|
|
|
436 if alt_allele_count == 0:
|
|
|
437 if xbase_location in zero_snp_count_per_xbase:
|
|
|
438 zero_snp_count_per_xbase[xbase_location] = zero_snp_count_per_xbase[xbase_location] + 1
|
|
|
439 else:
|
|
|
440 zero_snp_count_per_xbase[xbase_location] = 1
|
|
|
441
|
|
|
442 elif alt_allele_count != 0 and xbase_location not in zero_snp_count_per_xbase:
|
|
|
443 zero_snp_count_per_xbase[xbase_location] = 0
|
|
|
444
|
|
|
445 return zero_snp_count_per_xbase
|
|
|
446
|
|
|
447 def parse_pileup(sample_pileup = None, haw_snps = None):
|
|
|
448 i_file = open(sample_pileup, 'rU')
|
|
|
449 reader = csv.reader(i_file, delimiter = '\t', quoting = csv.QUOTE_NONE)
|
|
|
450
|
|
|
451 pileup_info = {}
|
|
|
452
|
|
|
453 for row in reader:
|
|
|
454 chromosome = row[0].upper()
|
|
|
455 chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE)
|
|
|
456 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
|
|
|
457
|
|
|
458 position = row[1]
|
|
|
459 ref_allele = row[2]
|
|
|
460 read_depth = row[3]
|
|
|
461 read_bases = row[4]
|
|
|
462
|
|
|
463 location = chromosome + ":" + position
|
|
|
464 if location in haw_snps:
|
|
|
465 alt_allele, haw_snp_id, mapping_unit = haw_snps[location]
|
|
|
466 ref_allele_count, alt_allele_count = parse_read_bases(read_bases = read_bases, alt_allele = alt_allele)
|
|
|
467
|
|
|
468 if Decimal(read_depth!=0):
|
|
|
469 getcontext().prec = 6
|
|
|
470 ratio = Decimal(alt_allele_count) / Decimal(read_depth)
|
|
|
471 #ratio = Decimal(alt_allele_count) / Decimal(ref_allele_count)
|
|
|
472
|
|
|
473 pileup_info[location] = (alt_allele_count, ref_allele_count, read_depth, ratio, haw_snp_id, mapping_unit)
|
|
|
474
|
|
|
475 #debug line
|
|
|
476 #print chromosome, position, read_depth, ref_allele_count, alt_allele_count, ratio, id
|
|
|
477
|
|
|
478 i_file.close()
|
|
|
479
|
|
|
480 return pileup_info
|
|
|
481
|
|
|
482 def parse_read_bases(read_bases = None, alt_allele = None):
|
|
|
483 read_bases = re.sub('\$', '', read_bases)
|
|
|
484 read_bases = re.sub('\^[^\s]', '', read_bases)
|
|
|
485
|
|
|
486 ref_allele_matches = re.findall("\.|\,", read_bases)
|
|
|
487 ref_allele_count = len(ref_allele_matches)
|
|
|
488
|
|
|
489 alt_allele_matches = re.findall(alt_allele, read_bases, flags = re.IGNORECASE)
|
|
|
490 alt_allele_count = len(alt_allele_matches)
|
|
|
491
|
|
|
492 #debug line
|
|
|
493 #print read_bases, alt_allele, alt_allele_count, ref_allele_count
|
|
|
494
|
|
|
495 return ref_allele_count, alt_allele_count
|
|
|
496
|
|
|
497 if __name__ == "__main__":
|
|
|
498 main()
|
