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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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10
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8 import pprint
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0
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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', '--do_not_normalize_bin', dest = 'do_not_normalize_bin', action = 'store_true', help = "Do not Normalize histograms")
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27
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28 parser.add_option('-o', '--output', dest = 'output', action = 'store', type = 'string', default = None, help = "Output file name")
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29 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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30
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31 #For plotting with map units on the X-axis instead of physical distance
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32 #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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33 (options, args) = parser.parse_args()
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34
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35 haw_snps = build_haw_snp_dictionary(haw_vcf = options.haw_vcf)
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36 pileup_info = parse_pileup(sample_pileup = options.sample_pileup, haw_snps = haw_snps)
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37
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38 output_pileup_info(output = options.output, pileup_info = pileup_info)
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39
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40 #output plot with all ratios
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41 rounded_bin_size = int(round((float(options.bin_size) / 1000000), 1) * 1000000)
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42
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43 normalized_histogram_bins_per_mb = calculate_normalized_histogram_bins_per_xbase(pileup_info = pileup_info, xbase = rounded_bin_size, do_not_normalize = options.do_not_normalize_bin)
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44 normalized_histogram_bins_per_5kb = calculate_normalized_histogram_bins_per_xbase(pileup_info = pileup_info, xbase = (rounded_bin_size / 2), do_not_normalize = options.do_not_normalize_bin)
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45
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46 break_dict = parse_breaks(break_file = options.break_file)
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47
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48 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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49
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50 #For plotting with map units on the X-axis instead of physical distance)
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51 #output_scatter_plots_by_mapping_units(mpu_plot_output = options.mpu_plot_output, pileup_info = pileup_info)
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52
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53 def skip_headers(reader = None, i_file = None):
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54 # count headers
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55 comment = 0
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56 while reader.next()[0].startswith('#'):
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57 comment = comment + 1
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58
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59 # skip headers
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60 i_file.seek(0)
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61 for i in range(0, comment):
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62 reader.next()
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63
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64 def parse_breaks(break_file = None):
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65 if break_file == 'C.elegans':
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66 break_dict = { 'I' : 16 , 'II' : 16, 'III' : 14, 'IV' : 18, 'V' : 21, 'X' : 18 }
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67 return break_dict
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68 elif break_file == 'Arabadopsis':
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69 break_dict = { '1' : 16 , '2' : 16, '3' : 21, '4' : 18, '5' : 21 }
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70 return break_dict
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71 else:
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72 i_file = open(break_file, 'rU')
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73 break_dict = {}
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74 reader = csv.reader(i_file, delimiter = '\t')
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75 for row in reader:
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76 chromosome = row[0].upper()
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77 chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE)
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78 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
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79 break_count = row[1]
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80 break_dict[chromosome] = int(break_count)
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81 return break_dict
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82
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83
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84 def location_comparer(location_1, location_2):
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85 chr_loc_1 = location_1.split(':')[0]
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86 pos_loc_1 = int(location_1.split(':')[1])
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87
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88 chr_loc_2 = location_2.split(':')[0]
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89 pos_loc_2 = int(location_2.split(':')[1])
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90
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91 if chr_loc_1 == chr_loc_2:
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92 if pos_loc_1 < pos_loc_2:
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93 return -1
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94 elif pos_loc_1 == pos_loc_1:
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95 return 0
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96 elif pos_loc_1 > pos_loc_2:
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97 return 1
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98 elif chr_loc_1 < chr_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
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103 def output_pileup_info(output = None, pileup_info = None):
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104 o_file = open(output, 'wb')
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105 writer = csv.writer(o_file, delimiter = '\t')
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106
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107 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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108
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109 location_sorted_pileup_info_keys = sorted(pileup_info.keys(), cmp=location_comparer)
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110
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111 for location in location_sorted_pileup_info_keys:
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112 alt_allele_count, ref_allele_count, read_depth, ratio, haw_snp_id, mapping_unit = pileup_info[location]
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113
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114 location_info = location.split(':')
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115 chromosome = location_info[0]
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116 position = location_info[1]
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117
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118 writer.writerow([chromosome, position, haw_snp_id, alt_allele_count, ref_allele_count, read_depth, ratio, mapping_unit])
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119
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120 o_file.close()
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121
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122 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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123 positions = {}
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124 current_chr = ""
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125 prev_chr = ""
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126
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127 x_label = "Location (Mb)"
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128 filtered_label = ''
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129
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130 location_sorted_pileup_info_keys = sorted(pileup_info.keys(), cmp=location_comparer)
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131
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132 break_unit = Decimal(rounded_bin_size) / Decimal(1000000)
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133 max_breaks = max(breaks.values())
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134
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135 try:
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136 r.pdf(location_plot_output, 8, 8)
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137
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138 for location in location_sorted_pileup_info_keys:
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139 current_chr = location.split(':')[0]
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140 position = location.split(':')[1]
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141
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142 alt_allele_count, ref_allele_count, read_depth, ratio, haw_snp_id, mapping_unit = pileup_info[location]
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143
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144 if prev_chr != current_chr:
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145 if prev_chr != "":
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146 hist_dict_mb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_mb, chr = prev_chr)
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147 hist_dict_5kb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_5kb, chr = prev_chr)
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148
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149 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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150
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151 prev_chr = current_chr
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152 positions = {}
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153
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154 positions[position] = ratio
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155
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156 hist_dict_mb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_mb, chr = current_chr)
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157 hist_dict_5kb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_5kb, chr = current_chr)
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158
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159 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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160
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161 r.dev_off()
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162
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163 except Exception as inst:
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164 print inst
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165 print "There was an error creating the location plot pdf... Please try again"
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166
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167 def get_hist_dict_by_chr(normalized_hist_per_xbase = None, chr = ''):
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168 hist_dict = {}
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169
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170 for location in normalized_hist_per_xbase:
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171 chromosome = location.split(':')[0]
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172 if chromosome == chr:
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173 position = int(location.split(':')[1])
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174 hist_dict[position] = normalized_hist_per_xbase[location]
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175
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176 return hist_dict
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177
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178 '''
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179 def output_scatter_plots_by_mapping_units(mpu_plot_output = None, pileup_info = None):
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180 i = {}
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181 ii = {}
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182 iii = {}
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183 iv = {}
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184 v = {}
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185 x = {}
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186
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187 for location in pileup_info:
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188 chromosome = location.split(':')[0]
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189 position = location.split(':')[1]
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190
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191 alt_allele_count, ref_allele_count, read_depth, ratio, haw_snp_id, mapping_unit = pileup_info[location]
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192
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193 if chromosome == "I":
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194 i[mapping_unit] = ratio
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195 elif chromosome == "II":
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196 ii[mapping_unit] = ratio
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197 elif chromosome == "III":
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198 iii[mapping_unit] = ratio
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199 elif chromosome == "IV":
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200 iv[mapping_unit] = ratio
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201 elif chromosome == "V":
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202 v[mapping_unit] = ratio
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203 elif chromosome == "X":
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204 x[mapping_unit] = ratio
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205
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206 x_label = "Map Units"
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207
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208 try:
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209 r.pdf(mpu_plot_output, 8, 8)
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210 plot_data(chr_dict = i, chr = "I", x_label = "Map Units")
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211 plot_data(chr_dict = ii, chr = "II", x_label = "Map Units")
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212 plot_data(chr_dict = iii, chr = "III", x_label = "Map Units")
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213 plot_data(chr_dict = iv, chr = "IV", x_label = "Map Units")
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214 plot_data(chr_dict = v, chr = "V", x_label = "Map Units")
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215 plot_data(chr_dict = x, chr = "X", x_label = "Map Units")
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216 r.dev_off()
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217 except Exception as inst:
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218 print inst
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219 print "There was an error creating the map unit plot pdf... Please try again"
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220 '''
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221
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10
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222 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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223 ratios = "c("
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224 positions = "c("
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225
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226 for position in chr_dict:
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227 ratio = chr_dict[position]
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228 if divide_position:
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229 position = float(position) / 1000000.0
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230 positions = positions + str(position) + ", "
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231 ratios = ratios + str(ratio) + ", "
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232
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233 if len(ratios) == 2:
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234 ratios = ratios + ")"
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235 else:
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236 ratios = ratios[0:len(ratios) - 2] + ")"
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237
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238 if len(positions) == 2:
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239 positions = positions + ")"
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240 else:
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241 positions = positions[0:len(positions) - 2] + ")"
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242
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243 r("x <- " + positions)
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244 r("y <- " + ratios)
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245
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246 hist_mb_values = "c("
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247 for position in sorted(hist_dict_mb):
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248 hist_mb_values = hist_mb_values + str(hist_dict_mb[position]) + ", "
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249
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250 if len(hist_mb_values) == 2:
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251 hist_mb_values = hist_mb_values + ")"
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252 else:
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253 hist_mb_values = hist_mb_values[0:len(hist_mb_values) - 2] + ")"
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254
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255 hist_5kb_values = "c("
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256 for position in sorted(hist_dict_5kb):
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257 hist_5kb_values = hist_5kb_values + str(hist_dict_5kb[position]) + ", "
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0
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258
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10
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259 if len(hist_5kb_values) == 2:
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260 hist_5kb_values = hist_5kb_values + ")"
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261 else:
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262 hist_5kb_values = hist_5kb_values[0:len(hist_5kb_values) - 2] + ")"
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263
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264 r("xz <- " + hist_mb_values)
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265 r("yz <- " + hist_5kb_values)
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266
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267 max_break_str = str(max_breaks)
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268 break_unit_str = str(Decimal(break_unit))
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269 half_break_unit_str = str(Decimal(break_unit) / Decimal(2))
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270 break_penta_unit_str = str(Decimal(break_unit) * Decimal(5))
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271
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272 if (standardize=='true'):
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273 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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274 r("lines(loess.smooth(x, y, span = %f "%loess_span + "), lwd=5, col='"+ loess_color +"')")
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275 r("axis(1, at=seq(0, " + max_break_str + ", by=" + break_unit_str + "), labels=FALSE, tcl=-0.5)")
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276 r("axis(1, at=seq(0, " + max_break_str + ", by=" + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
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277 r("axis(2, at=seq(floor(min(y)), 1, by=0.1), labels=FALSE, tcl=-0.2)")
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278 elif (standardize=='false'):
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10
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279 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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280 r("lines(loess.smooth(x, y, span = %f "%loess_span + "), lwd=5, col='"+ loess_color +"')")
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10
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281 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)")
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282 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
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283 r("axis(2, at=seq(floor(min(y)), 1, by=0.1), labels=FALSE, tcl=-0.2)")
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284
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285 if draw_secondary_grid_lines:
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286 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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287 else:
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288 r("grid(lty = 1, col = 'gray')")
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289
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290 if (standardize=='true'):
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10
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291 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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292 r("barplot(yz, space = 0, add=TRUE, width = " + half_break_unit_str + ", col=rgb(1, 0, 0, 1))")
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293 r("axis(1, hadj = 1, at=seq(0, " + max_break_str + ", by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)")
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294 r("axis(1, at=seq(0, " + max_break_str + ", by= " + break_penta_unit_str + "), labels=TRUE, tcl=-0.5)")
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295 r("axis(1, at=seq(0, " + max_break_str + ", by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
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0
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296 elif (standardize=='false'):
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10
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297 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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298 r("barplot(yz, space = 0, add=TRUE, width = 0.5, col=rgb(1, 0, 0, 1))")
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299 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)")
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300 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_penta_unit_str + ", labels=TRUE, tcl=-0.5)")
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301 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_half_unit_str + "), labels=FALSE, tcl=-0.25)")
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0
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302
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303
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304 def build_haw_snp_dictionary(haw_vcf = None):
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305 haw_snps = {}
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306
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307 i_file = open(haw_vcf, 'rU')
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308 reader = csv.reader(i_file, delimiter = '\t')
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309
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310 skip_headers(reader = reader, i_file = i_file)
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311
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312 for row in reader:
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313 #print row
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314 chromosome = row[0].upper()
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315 chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE)
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316 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
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317
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318 position = row[1]
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319 haw_snp_id = row[2]
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320 ref_allele = row[3]
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321 alt_allele = row[4]
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10
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322
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323 info = row[7]
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0
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324
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325 mapping_unit = info.replace("MPU=", "")
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326
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327 location = chromosome + ":" + position
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328 haw_snps[location] = (alt_allele, haw_snp_id, mapping_unit)
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329
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330 i_file.close()
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331
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332 return haw_snps
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10
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333
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334 def calculate_normalized_histogram_bins_per_xbase(pileup_info = None, xbase = 1000000, do_not_normalize = False):
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335 normalized_histogram_bins_per_xbase = {}
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336
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337 ref_snp_count_per_xbase = get_ref_snp_count_per_xbase(pileup_info = pileup_info, xbase = xbase)
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338 mean_zero_snp_count_per_chromosome = get_mean_zero_snp_count_per_chromosome(pileup_info = pileup_info, xbase = xbase)
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339 zero_snp_count_per_xbase = get_zero_snp_count_per_xbase(pileup_info = pileup_info, xbase = xbase)
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340
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341 for location in ref_snp_count_per_xbase:
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342 chromosome = location.split(':')[0]
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343 mean_zero_snp_count = mean_zero_snp_count_per_chromosome[chromosome]
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344 ref_snp_count = ref_snp_count_per_xbase[location]
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345
|
|
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346 zero_snp_count = 0
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|
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347 if location in zero_snp_count_per_xbase:
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348 zero_snp_count = zero_snp_count_per_xbase[location]
|
|
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349
|
|
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350 if do_not_normalize == True:
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351 normalized_histogram_bins_per_xbase[location] = zero_snp_count
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352 else:
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353 if zero_snp_count == 0 or ref_snp_count == 0:
|
|
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354 normalized_histogram_bins_per_xbase[location] = 0
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|
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355 elif zero_snp_count == ref_snp_count:
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356 normalized_histogram_bins_per_xbase[location] = 0
|
|
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357 else:
|
|
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358 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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359
|
|
|
360 return normalized_histogram_bins_per_xbase
|
|
|
361
|
|
|
362 def get_ref_snp_count_per_xbase(pileup_info = None, xbase = 1000000):
|
|
|
363 ref_snps_per_xbase = {}
|
|
|
364
|
|
|
365 for location in pileup_info:
|
|
|
366 location_info = location.split(':')
|
|
|
367
|
|
|
368 chromosome = location_info[0].upper()
|
|
|
369 chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE)
|
|
|
370 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
|
|
|
371
|
|
|
372 position = location_info[1]
|
|
|
373 xbase_position = (int(position) / xbase) + 1
|
|
|
374
|
|
|
375 location = chromosome + ":" + str(xbase_position)
|
|
|
376 if location in ref_snps_per_xbase:
|
|
|
377 ref_snps_per_xbase[location] = ref_snps_per_xbase[location] + 1
|
|
|
378 else:
|
|
|
379 ref_snps_per_xbase[location] = 1
|
|
|
380
|
|
|
381 return ref_snps_per_xbase
|
|
|
382
|
|
|
383 def get_mean_zero_snp_count_per_chromosome(pileup_info, xbase = 1000000):
|
|
|
384 sample_snp_count_per_xbase = {}
|
|
|
385
|
|
|
386 for location in pileup_info:
|
|
|
387 alt_allele_count, ref_allele_count, read_depth, ratio, haw_snp_id, mapping_unit = pileup_info[location]
|
|
|
388
|
|
|
389 location_info = location.split(':')
|
|
|
390 chromosome = location_info[0]
|
|
|
391 position = location_info[1]
|
|
|
392 xbase_position = (int(position) / xbase) + 1
|
|
|
393 xbase_location = chromosome + ":" + str(xbase_position)
|
|
|
394
|
|
|
395 if alt_allele_count == 0:
|
|
|
396 if xbase_location in sample_snp_count_per_xbase:
|
|
|
397 sample_snp_count_per_xbase[xbase_location] = sample_snp_count_per_xbase[xbase_location] + 1
|
|
|
398 else:
|
|
|
399 sample_snp_count_per_xbase[xbase_location] = 1
|
|
|
400
|
|
|
401 elif alt_allele_count != 0 and xbase_location not in sample_snp_count_per_xbase:
|
|
|
402 sample_snp_count_per_xbase[xbase_location] = 0
|
|
|
403
|
|
|
404 mean_zero_snp_count_per_chromosome = {}
|
|
|
405 for location in sample_snp_count_per_xbase:
|
|
|
406 chromosome = location.split(':')[0]
|
|
|
407 sample_count = sample_snp_count_per_xbase[location]
|
|
|
408 if chromosome in mean_zero_snp_count_per_chromosome:
|
|
|
409 mean_zero_snp_count_per_chromosome[chromosome].append(sample_count)
|
|
|
410 else:
|
|
|
411 mean_zero_snp_count_per_chromosome[chromosome] = [sample_count]
|
|
|
412
|
|
|
413 for chromosome in mean_zero_snp_count_per_chromosome:
|
|
|
414 summa = sum(mean_zero_snp_count_per_chromosome[chromosome])
|
|
|
415 count = len(mean_zero_snp_count_per_chromosome[chromosome])
|
|
|
416
|
|
|
417 mean_zero_snp_count_per_chromosome[chromosome] = Decimal(summa) / Decimal(count)
|
|
|
418
|
|
|
419 return mean_zero_snp_count_per_chromosome
|
|
|
420
|
|
|
421 def get_zero_snp_count_per_xbase(pileup_info = None, xbase = 1000000):
|
|
|
422 zero_snp_count_per_xbase = {}
|
|
|
423
|
|
|
424 for location in pileup_info:
|
|
|
425 alt_allele_count, ref_allele_count, read_depth, ratio, haw_snp_id, mapping_unit = pileup_info[location]
|
|
|
426
|
|
|
427 location_info = location.split(':')
|
|
|
428 chromosome = location_info[0]
|
|
|
429 position = location_info[1]
|
|
|
430 xbase_position = (int(position) / xbase) + 1
|
|
|
431 xbase_location = chromosome + ":" + str(xbase_position)
|
|
|
432
|
|
|
433 if alt_allele_count == 0:
|
|
|
434 if xbase_location in zero_snp_count_per_xbase:
|
|
|
435 zero_snp_count_per_xbase[xbase_location] = zero_snp_count_per_xbase[xbase_location] + 1
|
|
|
436 else:
|
|
|
437 zero_snp_count_per_xbase[xbase_location] = 1
|
|
|
438
|
|
|
439 elif alt_allele_count != 0 and xbase_location not in zero_snp_count_per_xbase:
|
|
|
440 zero_snp_count_per_xbase[xbase_location] = 0
|
|
|
441
|
|
|
442 return zero_snp_count_per_xbase
|
|
0
|
443
|
|
|
444 def parse_pileup(sample_pileup = None, haw_snps = None):
|
|
|
445 i_file = open(sample_pileup, 'rU')
|
|
|
446 reader = csv.reader(i_file, delimiter = '\t', quoting = csv.QUOTE_NONE)
|
|
|
447
|
|
|
448 pileup_info = {}
|
|
|
449
|
|
|
450 for row in reader:
|
|
|
451 chromosome = row[0].upper()
|
|
|
452 chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE)
|
|
|
453 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
|
|
|
454
|
|
|
455 position = row[1]
|
|
|
456 ref_allele = row[2]
|
|
|
457 read_depth = row[3]
|
|
|
458 read_bases = row[4]
|
|
|
459
|
|
|
460 location = chromosome + ":" + position
|
|
|
461 if location in haw_snps:
|
|
|
462 alt_allele, haw_snp_id, mapping_unit = haw_snps[location]
|
|
|
463 ref_allele_count, alt_allele_count = parse_read_bases(read_bases = read_bases, alt_allele = alt_allele)
|
|
10
|
464
|
|
|
465 if Decimal(read_depth!=0):
|
|
|
466 getcontext().prec = 6
|
|
|
467 ratio = Decimal(alt_allele_count) / Decimal(read_depth)
|
|
|
468 #ratio = Decimal(alt_allele_count) / Decimal(ref_allele_count)
|
|
|
469
|
|
|
470 pileup_info[location] = (alt_allele_count, ref_allele_count, read_depth, ratio, haw_snp_id, mapping_unit)
|
|
0
|
471
|
|
10
|
472 #debug line
|
|
|
473 #print chromosome, position, read_depth, ref_allele_count, alt_allele_count, ratio, id
|
|
0
|
474
|
|
|
475 i_file.close()
|
|
|
476
|
|
|
477 return pileup_info
|
|
|
478
|
|
|
479 def parse_read_bases(read_bases = None, alt_allele = None):
|
|
|
480 read_bases = re.sub('\$', '', read_bases)
|
|
|
481 read_bases = re.sub('\^[^\s]', '', read_bases)
|
|
|
482
|
|
|
483 ref_allele_matches = re.findall("\.|\,", read_bases)
|
|
|
484 ref_allele_count = len(ref_allele_matches)
|
|
|
485
|
|
|
486 alt_allele_matches = re.findall(alt_allele, read_bases, flags = re.IGNORECASE)
|
|
|
487 alt_allele_count = len(alt_allele_matches)
|
|
|
488
|
|
|
489 #debug line
|
|
|
490 #print read_bases, alt_allele, alt_allele_count, ref_allele_count
|
|
|
491
|
|
|
492 return ref_allele_count, alt_allele_count
|
|
|
493
|
|
|
494 if __name__ == "__main__":
|
|
|
495 main()
|
