Mercurial > repos > gregory-minevich > cloudmap_variant_discovery_mapping

comparison VDM_Mapping.py @ 9:3dba6603108e draft

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author gregory-minevich
date Fri, 09 May 2014 16:55:03 -0400
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8:985aacf4d157 9:3dba6603108e
1 #!/usr/bin/python
2
3 import re
4 import sys
5 import optparse
6 import csv
7 import re
8 import pprint
9 from decimal import *
10 from rpy import *
11
12 def main():
13 csv.field_size_limit(1000000000)
14
15 parser = optparse.OptionParser()
16 parser.add_option('-v', '--sample_vcf', dest = 'sample_vcf', action = 'store', type = 'string', default = None, help = "Sample VCF from GATK Unified Genotyper")
17 parser.add_option('-l', '--loess_span', dest = 'loess_span', action = 'store', type = 'float', default = .1, help = "Loess span")
18 parser.add_option('-d', '--d_yaxis', dest = 'd_yaxis', action = 'store', type = 'float', default = 1, help = "y-axis upper limit for dot plot")
19 parser.add_option('-y', '--h_yaxis', dest = 'h_yaxis', action = 'store', type = 'int', default = 0, help = "y-axis upper limit for histogram plot")
20 parser.add_option('-c', '--points_color', dest = 'points_color', action = 'store', type = 'string', default = "gray27", help = "Color for data points")
21 parser.add_option('-k', '--loess_color', dest = 'loess_color', action = 'store', type = 'string', default = "green2", help = "Color for loess regression line")
22 parser.add_option('-z', '--standardize', dest = 'standardize', default= 'true', help = "Standardize X-axis")
23 parser.add_option('-b', '--break_file', dest = 'break_file', action = 'store', type = 'string', default = 'C.elegans', help = "File defining the breaks per chromosome")
24 parser.add_option('-x', '--bin_size', dest = 'bin_size', action = 'store', type = 'int', default = 1000000, help = "Size of histogram bins, default is 1mb")
25 parser.add_option('-n', '--normalize_bins', dest = 'normalize_bins', default= 'true', help = "Normalize histograms")
26
27 parser.add_option('-o', '--output', dest = 'output', action = 'store', type = 'string', default = None, help = "Output file name")
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")
29
30 (options, args) = parser.parse_args()
31
32 vcf_info = parse_vcf(sample_vcf = options.sample_vcf)
33
34 output_vcf_info(output = options.output, vcf_info = vcf_info)
35
36 #output plot with all ratios
37 rounded_bin_size = int(round((float(options.bin_size) / 1000000), 1) * 1000000)
38
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)
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) )]
41
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)
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) )]
44
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)))
46
47
48 break_dict = parse_breaks(break_file = options.break_file)
49
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)
51
52 def myround(x, base=10):
53 return int(base * round(float(x)/base))
54
55 def skip_headers(reader = None, i_file = None):
56 # count headers
57 comment = 0
58 while reader.next()[0].startswith('#'):
59 comment = comment + 1
60
61 # skip headers
62 i_file.seek(0)
63 for i in range(0, comment):
64 reader.next()
65
66 def parse_breaks(break_file = None):
67 if break_file == 'C.elegans':
68 break_dict = { 'I' : 16 , 'II' : 16, 'III' : 14, 'IV' : 18, 'V' : 21, 'X' : 18 }
69 return break_dict
70 elif break_file == 'Brachypodium':
71 break_dict = { '1' : 75 , '2' : 60, '3' : 60, '4' : 50, '5' : 30 }
72 return break_dict
73 elif break_file == 'Arabadopsis':
74 break_dict = { '1' : 31 , '2' : 20, '3' : 24, '4' : 19, '5' : 27 }
75 return break_dict
76 else:
77 i_file = open(break_file, 'rU')
78 break_dict = {}
79 reader = csv.reader(i_file, delimiter = '\t')
80 for row in reader:
81 chromosome = row[0].upper()
82 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
83 chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE)
84 break_count = row[1]
85 break_dict[chromosome] = int(break_count)
86 return break_dict
87
88
89 def location_comparer(location_1, location_2):
90 chr_loc_1 = location_1.split(':')[0]
91 pos_loc_1 = int(location_1.split(':')[1])
92
93 chr_loc_2 = location_2.split(':')[0]
94 pos_loc_2 = int(location_2.split(':')[1])
95
96 if chr_loc_1 == chr_loc_2:
97 if pos_loc_1 < pos_loc_2:
98 return -1
99 elif pos_loc_1 == pos_loc_1:
100 return 0
101 elif pos_loc_1 > pos_loc_2:
102 return 1
103 elif chr_loc_1 < chr_loc_2:
104 return -1
105 elif chr_loc_1 > chr_loc_2:
106 return 1
107
108 def output_vcf_info(output = None, vcf_info = None):
109 o_file = open(output, 'wb')
110 writer = csv.writer(o_file, delimiter = '\t')
111
112 writer.writerow(["#Chr\t", "Pos\t", "Alt Count\t", "Ref Count\t", "Read Depth\t", "Ratio\t"])
113
114 location_sorted_vcf_info_keys = sorted(vcf_info.keys(), cmp=location_comparer)
115
116 for location in location_sorted_vcf_info_keys:
117 alt_allele_count, ref_allele_count, read_depth, ratio = vcf_info[location]
118
119 location_info = location.split(':')
120 chromosome = location_info[0]
121 position = location_info[1]
122
123 writer.writerow([chromosome, position, alt_allele_count, ref_allele_count, read_depth, ratio])
124
125 o_file.close()
126
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 = ""):
128 positions = {}
129 current_chr = ""
130 prev_chr = ""
131
132 x_label = "Location (Mb)"
133 filtered_label = ''
134
135 location_sorted_vcf_info_keys = sorted(vcf_info.keys(), cmp=location_comparer)
136
137 break_unit = Decimal(rounded_bin_size) / Decimal(1000000)
138 max_breaks = max(breaks.values())
139
140 try:
141 r.pdf(location_plot_output, 8, 8)
142
143 for location in location_sorted_vcf_info_keys:
144 current_chr = location.split(':')[0]
145 position = location.split(':')[1]
146
147 alt_allele_count, ref_allele_count, read_depth, ratio = vcf_info[location]
148
149 if prev_chr != current_chr:
150 if prev_chr != "":
151 hist_dict_mb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_mb, chr = prev_chr)
152 hist_dict_5kb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_5kb, chr = prev_chr)
153
154 if h_yaxis == 0:
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)
156 else:
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)
158
159 prev_chr = current_chr
160 positions = {}
161
162 positions[position] = ratio
163
164 hist_dict_mb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_mb, chr = current_chr)
165 hist_dict_5kb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_5kb, chr = current_chr)
166
167 if h_yaxis == 0:
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)
169 else:
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)
171
172 r.dev_off()
173
174 except Exception as inst:
175 print inst
176 print "There was an error creating the location plot pdf... Please try again"
177
178 def get_hist_dict_by_chr(normalized_hist_per_xbase = None, chr = ''):
179 hist_dict = {}
180
181 for location in normalized_hist_per_xbase:
182 chromosome = location.split(':')[0]
183 if chromosome == chr:
184 position = int(location.split(':')[1])
185 hist_dict[position] = normalized_hist_per_xbase[location]
186
187 max_location = max(hist_dict.keys(), key=int)
188 for i in range(1, max_location):
189 if i not in hist_dict:
190 hist_dict[i] = 0
191
192 return hist_dict
193
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):
195 ratios = "c("
196 positions = "c("
197
198 for position in chr_dict:
199 ratio = chr_dict[position]
200 if divide_position:
201 position = float(position) / 1000000.0
202 positions = positions + str(position) + ", "
203 ratios = ratios + str(ratio) + ", "
204
205 if len(ratios) == 2:
206 ratios = ratios + ")"
207 else:
208 ratios = ratios[0:len(ratios) - 2] + ")"
209
210 if len(positions) == 2:
211 positions = positions + ")"
212 else:
213 positions = positions[0:len(positions) - 2] + ")"
214
215 r("x <- " + positions)
216 r("y <- " + ratios)
217
218 hist_mb_values = "c("
219 for position in sorted(hist_dict_mb):
220 hist_mb_values = hist_mb_values + str(hist_dict_mb[position]) + ", "
221
222 if len(hist_mb_values) == 2:
223 hist_mb_values = hist_mb_values + ")"
224 else:
225 hist_mb_values = hist_mb_values[0:len(hist_mb_values) - 2] + ")"
226
227 hist_5kb_values = "c("
228 for position in sorted(hist_dict_5kb):
229 hist_5kb_values = hist_5kb_values + str(hist_dict_5kb[position]) + ", "
230
231 if len(hist_5kb_values) == 2:
232 hist_5kb_values = hist_5kb_values + ")"
233 else:
234 hist_5kb_values = hist_5kb_values[0:len(hist_5kb_values) - 2] + ")"
235
236 r("xz <- " + hist_mb_values)
237 r("yz <- " + hist_5kb_values)
238
239
240 max_break_str = str(max_breaks)
241 break_unit_str = str(Decimal(break_unit))
242 half_break_unit_str = str(Decimal(break_unit) / Decimal(2))
243 break_penta_unit_str = str(Decimal(break_unit) * Decimal(5))
244
245 if (standardize=='true'):
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 +"')")
247 r("lines(loess.smooth(x, y, span = %f "%loess_span + "), lwd=5, col='"+ loess_color +"')")
248 r("axis(1, at=seq(0, " + max_break_str + ", by=" + break_unit_str + "), labels=FALSE, tcl=-0.5)")
249 r("axis(1, at=seq(0, " + max_break_str + ", by=" + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
250 r("axis(2, at=seq(floor(min(y)), 1, by=0.1), labels=FALSE, tcl=-0.2)")
251 elif (standardize=='false'):
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 +"')")
253 r("lines(loess.smooth(x, y, span = %f "%loess_span + "), lwd=5, col='"+ loess_color +"')")
254 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)")
255 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
256 r("axis(2, at=seq(floor(min(y)), 1, by=0.1), labels=FALSE, tcl=-0.2)")
257
258 if draw_secondary_grid_lines:
259 r("abline(h = seq(floor(min(y)), 1, by=0.1), v = seq(floor(min(x)), length(x), by= 1), col='gray')")
260 else:
261 r("grid(lty = 1, col = 'gray')")
262
263 if (standardize=='true'):
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)')")
265 r("barplot(yz, space = 0, add=TRUE, width = " + half_break_unit_str + ", col='green2')")
266 r("axis(1, hadj = 1, at=seq(0, " + max_break_str + ", by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)")
267 r("axis(1, at=seq(0, " + max_break_str + ", by= " + break_penta_unit_str + "), labels=TRUE, tcl=-0.5)")
268 r("axis(1, at=seq(0, " + max_break_str + ", by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
269 elif (standardize=='false'):
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)')")
271 r("barplot(yz, space = 0, add=TRUE, width = 0.5, col='green2')")
272 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)")
273 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_penta_unit_str + "), labels=TRUE, tcl=-0.5)")
274 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
275
276
277
278 def calculate_normalized_histogram_bins_per_xbase(vcf_info = None, xbase = 1000000, normalize_bins = None):
279 normalized_histogram_bins_per_xbase = {}
280
281 ref_snp_count_per_xbase = get_ref_snp_count_per_xbase(vcf_info = vcf_info, xbase = xbase)
282 mean_one_ratio_snp_count_per_chromosome = get_mean_one_ratio_snp_count_per_chromosome(vcf_info = vcf_info, xbase = xbase)
283 one_ratio_snp_count_per_xbase = get_one_ratio_snp_count_per_xbase(vcf_info = vcf_info, xbase = xbase)
284
285 for location in ref_snp_count_per_xbase:
286 chromosome = location.split(':')[0]
287 mean_one_ratio_snp_count = mean_one_ratio_snp_count_per_chromosome[chromosome]
288 ref_snp_count = ref_snp_count_per_xbase[location]
289
290 one_ratio_snp_count = 0
291 if location in one_ratio_snp_count_per_xbase:
292 one_ratio_snp_count = one_ratio_snp_count_per_xbase[location]
293
294 if normalize_bins == 'true':
295 if one_ratio_snp_count == 0:
296 normalized_histogram_bins_per_xbase[location] = 0
297 elif one_ratio_snp_count == ref_snp_count:
298 normalized_histogram_bins_per_xbase[location] = (Decimal(one_ratio_snp_count**2) * Decimal(mean_one_ratio_snp_count))
299 else:
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)
301 else:
302 normalized_histogram_bins_per_xbase[location] = one_ratio_snp_count
303
304 return normalized_histogram_bins_per_xbase
305
306
307 def get_ref_snp_count_per_xbase(vcf_info = None, xbase = 1000000):
308 ref_snps_per_xbase = {}
309
310 for location in vcf_info:
311 location_info = location.split(':')
312
313 chromosome = location_info[0].upper()
314 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
315 chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE)
316
317 position = location_info[1]
318 xbase_position = (int(position) / xbase) + 1
319
320 location = chromosome + ":" + str(xbase_position)
321 if location in ref_snps_per_xbase:
322 ref_snps_per_xbase[location] = ref_snps_per_xbase[location] + 1
323 else:
324 ref_snps_per_xbase[location] = 1
325
326 return ref_snps_per_xbase
327
328
329
330 def get_mean_one_ratio_snp_count_per_chromosome(vcf_info, xbase = 1000000):
331 sample_snp_count_per_xbase = {}
332
333 for location in vcf_info:
334 alt_allele_count, ref_allele_count, read_depth, ratio = vcf_info[location]
335
336 location_info = location.split(':')
337 chromosome = location_info[0]
338 position = location_info[1]
339 xbase_position = (int(position) / xbase) + 1
340 xbase_location = chromosome + ":" + str(xbase_position)
341
342 if ratio == 1:
343 if xbase_location in sample_snp_count_per_xbase:
344 sample_snp_count_per_xbase[xbase_location] = sample_snp_count_per_xbase[xbase_location] + 1
345 else:
346 sample_snp_count_per_xbase[xbase_location] = 1
347
348 elif ratio != 1 and xbase_location not in sample_snp_count_per_xbase:
349 sample_snp_count_per_xbase[xbase_location] = 0
350
351 mean_one_ratio_snp_count_per_chromosome = {}
352 for location in sample_snp_count_per_xbase:
353 chromosome = location.split(':')[0]
354 sample_count = sample_snp_count_per_xbase[location]
355 if chromosome in mean_one_ratio_snp_count_per_chromosome:
356 mean_one_ratio_snp_count_per_chromosome[chromosome].append(sample_count)
357 else:
358 mean_one_ratio_snp_count_per_chromosome[chromosome] = [sample_count]
359
360 for chromosome in mean_one_ratio_snp_count_per_chromosome:
361 summa = sum(mean_one_ratio_snp_count_per_chromosome[chromosome])
362 count = len(mean_one_ratio_snp_count_per_chromosome[chromosome])
363
364 mean_one_ratio_snp_count_per_chromosome[chromosome] = Decimal(summa) / Decimal(count)
365
366 return mean_one_ratio_snp_count_per_chromosome
367
368
369 def get_one_ratio_snp_count_per_xbase(vcf_info = None, xbase = 1000000):
370 one_ratio_snp_count_per_xbase = {}
371
372 for location in vcf_info:
373 alt_allele_count, ref_allele_count, read_depth, ratio = vcf_info[location]
374
375 location_info = location.split(':')
376 chromosome = location_info[0]
377 position = location_info[1]
378 xbase_position = (int(position) / xbase) + 1
379 xbase_location = chromosome + ":" + str(xbase_position)
380
381 if ratio == 1:
382 if xbase_location in one_ratio_snp_count_per_xbase:
383 one_ratio_snp_count_per_xbase[xbase_location] = one_ratio_snp_count_per_xbase[xbase_location] + 1
384 else:
385 one_ratio_snp_count_per_xbase[xbase_location] = 1
386
387 elif ratio != 1 and xbase_location not in one_ratio_snp_count_per_xbase:
388 one_ratio_snp_count_per_xbase[xbase_location] = 0
389
390 return one_ratio_snp_count_per_xbase
391
392
393 def parse_vcf(sample_vcf = None):
394 i_file = open(sample_vcf, 'rU')
395 reader = csv.reader(i_file, delimiter = '\t', quoting = csv.QUOTE_NONE)
396
397 skip_headers(reader = reader, i_file = i_file)
398 vcf_info = {}
399
400 for row in reader:
401 chromosome = row[0].upper()
402 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
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(":")
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()