Mercurial > repos > gregory-minevich > snp_mapping_using_wgs

comparison SNP_Mapping.py @ 20:98d409af683c draft

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author gregory-minevich
date Thu, 28 Jun 2012 14:21:31 -0400
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19:bb66acc12ef1 20:98d409af683c
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('-p', '--sample_pileup', dest = 'sample_pileup', action = 'store', type = 'string', default = None, help = "Sample pileup from mpileup")
17 parser.add_option('-v', '--haw_vcf', dest = 'haw_vcf', action = 'store', type = 'string', default = None, help = "vcf file of Hawaiian SNPs")
18 parser.add_option('-l', '--loess_span', dest = 'loess_span', action = 'store', type = 'float', default = .01, help = "Loess span")
19 parser.add_option('-d', '--d_yaxis', dest = 'd_yaxis', action = 'store', type = 'float', default = .7, help = "y-axis upper limit for dot plot")
20 parser.add_option('-y', '--h_yaxis', dest = 'h_yaxis', action = 'store', type = 'int', default = 5, help = "y-axis upper limit for histogram plot")
21 parser.add_option('-c', '--points_color', dest = 'points_color', action = 'store', type = 'string', default = "gray27", help = "Color for data points")
22 parser.add_option('-k', '--loess_color', dest = 'loess_color', action = 'store', type = 'string', default = "red", help = "Color for loess regression line")
23 parser.add_option('-z', '--standardize', dest = 'standardize', default= 'true', help = "Standardize X-axis")
24 parser.add_option('-b', '--break_file', dest = 'break_file', action = 'store', type = 'string', default = 'C.elegans', help = "File defining the breaks per chromosome")
25 parser.add_option('-x', '--bin_size', dest = 'bin_size', action = 'store', type = 'int', default = 1000000, help = "Size of histogram bins, default is 1mb")
26 #parser.add_option('-n', '--normalize_bins', dest = 'normalize_bins', action = 'store_true', help = "Normalize histograms")
27 parser.add_option('-n', '--normalize_bins', dest = 'normalize_bins', default= 'true', help = "Normalize histograms")
28
29
30 parser.add_option('-o', '--output', dest = 'output', action = 'store', type = 'string', default = None, help = "Output file name")
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")
32
33 #For plotting with map units on the X-axis instead of physical distance
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")
35 (options, args) = parser.parse_args()
36
37 haw_snps = build_haw_snp_dictionary(haw_vcf = options.haw_vcf)
38 pileup_info = parse_pileup(sample_pileup = options.sample_pileup, haw_snps = haw_snps)
39
40 output_pileup_info(output = options.output, pileup_info = pileup_info)
41
42 #output plot with all ratios
43 rounded_bin_size = int(round((float(options.bin_size) / 1000000), 1) * 1000000)
44
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)
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)
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, 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)
51
52 #For plotting with map units on the X-axis instead of physical distance)
53 #output_scatter_plots_by_mapping_units(mpu_plot_output = options.mpu_plot_output, pileup_info = pileup_info)
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 == 'Arabadopsis':
71 break_dict = { '1' : 16 , '2' : 16, '3' : 21, '4' : 18, '5' : 21 }
72 return break_dict
73 else:
74 i_file = open(break_file, 'rU')
75 break_dict = {}
76 reader = csv.reader(i_file, delimiter = '\t')
77 for row in reader:
78 chromosome = row[0].upper()
79 chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE)
80 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
81 break_count = row[1]
82 break_dict[chromosome] = int(break_count)
83 return break_dict
84
85
86 def location_comparer(location_1, location_2):
87 chr_loc_1 = location_1.split(':')[0]
88 pos_loc_1 = int(location_1.split(':')[1])
89
90 chr_loc_2 = location_2.split(':')[0]
91 pos_loc_2 = int(location_2.split(':')[1])
92
93 if chr_loc_1 == chr_loc_2:
94 if pos_loc_1 < pos_loc_2:
95 return -1
96 elif pos_loc_1 == pos_loc_1:
97 return 0
98 elif pos_loc_1 > pos_loc_2:
99 return 1
100 elif chr_loc_1 < chr_loc_2:
101 return -1
102 elif chr_loc_1 > chr_loc_2:
103 return 1
104
105 def output_pileup_info(output = None, pileup_info = None):
106 o_file = open(output, 'wb')
107 writer = csv.writer(o_file, delimiter = '\t')
108
109 writer.writerow(["#Chr\t", "Pos\t", "ID\t", "Alt Count\t", "Ref Count\t", "Read Depth\t", "Ratio\t", "Mapping Unit"])
110
111 location_sorted_pileup_info_keys = sorted(pileup_info.keys(), cmp=location_comparer)
112
113 for location in location_sorted_pileup_info_keys:
114 alt_allele_count, ref_allele_count, read_depth, ratio, haw_snp_id, mapping_unit = pileup_info[location]
115
116 location_info = location.split(':')
117 chromosome = location_info[0]
118 position = location_info[1]
119
120 writer.writerow([chromosome, position, haw_snp_id, alt_allele_count, ref_allele_count, read_depth, ratio, mapping_unit])
121
122 o_file.close()
123
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):
125 positions = {}
126 current_chr = ""
127 prev_chr = ""
128
129 x_label = "Location (Mb)"
130 filtered_label = ''
131
132 location_sorted_pileup_info_keys = sorted(pileup_info.keys(), cmp=location_comparer)
133
134 break_unit = Decimal(rounded_bin_size) / Decimal(1000000)
135 max_breaks = max(breaks.values())
136
137 try:
138 r.pdf(location_plot_output, 8, 8)
139
140 for location in location_sorted_pileup_info_keys:
141 current_chr = location.split(':')[0]
142 position = location.split(':')[1]
143
144 alt_allele_count, ref_allele_count, read_depth, ratio, haw_snp_id, mapping_unit = pileup_info[location]
145
146 if prev_chr != current_chr:
147 if prev_chr != "":
148 hist_dict_mb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_mb, chr = prev_chr)
149 hist_dict_5kb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_5kb, chr = prev_chr)
150
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)
152
153 prev_chr = current_chr
154 positions = {}
155
156 positions[position] = ratio
157
158 hist_dict_mb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_mb, chr = current_chr)
159 hist_dict_5kb = get_hist_dict_by_chr(normalized_hist_per_xbase = normalized_hist_per_5kb, chr = current_chr)
160
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)
162
163 r.dev_off()
164
165 except Exception as inst:
166 print inst
167 print "There was an error creating the location plot pdf... Please try again"
168
169 def get_hist_dict_by_chr(normalized_hist_per_xbase = None, chr = ''):
170 hist_dict = {}
171
172 for location in normalized_hist_per_xbase:
173 chromosome = location.split(':')[0]
174 if chromosome == chr:
175 position = int(location.split(':')[1])
176 hist_dict[position] = normalized_hist_per_xbase[location]
177
178 return hist_dict
179
180 '''
181 def output_scatter_plots_by_mapping_units(mpu_plot_output = None, pileup_info = None):
182 i = {}
183 ii = {}
184 iii = {}
185 iv = {}
186 v = {}
187 x = {}
188
189 for location in pileup_info:
190 chromosome = location.split(':')[0]
191 position = location.split(':')[1]
192
193 alt_allele_count, ref_allele_count, read_depth, ratio, haw_snp_id, mapping_unit = pileup_info[location]
194
195 if chromosome == "I":
196 i[mapping_unit] = ratio
197 elif chromosome == "II":
198 ii[mapping_unit] = ratio
199 elif chromosome == "III":
200 iii[mapping_unit] = ratio
201 elif chromosome == "IV":
202 iv[mapping_unit] = ratio
203 elif chromosome == "V":
204 v[mapping_unit] = ratio
205 elif chromosome == "X":
206 x[mapping_unit] = ratio
207
208 x_label = "Map Units"
209
210 try:
211 r.pdf(mpu_plot_output, 8, 8)
212 plot_data(chr_dict = i, chr = "I", x_label = "Map Units")
213 plot_data(chr_dict = ii, chr = "II", x_label = "Map Units")
214 plot_data(chr_dict = iii, chr = "III", x_label = "Map Units")
215 plot_data(chr_dict = iv, chr = "IV", x_label = "Map Units")
216 plot_data(chr_dict = v, chr = "V", x_label = "Map Units")
217 plot_data(chr_dict = x, chr = "X", x_label = "Map Units")
218 r.dev_off()
219 except Exception as inst:
220 print inst
221 print "There was an error creating the map unit plot pdf... Please try again"
222 '''
223
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):
225 ratios = "c("
226 positions = "c("
227
228 for position in chr_dict:
229 ratio = chr_dict[position]
230 if divide_position:
231 position = float(position) / 1000000.0
232 positions = positions + str(position) + ", "
233 ratios = ratios + str(ratio) + ", "
234
235 if len(ratios) == 2:
236 ratios = ratios + ")"
237 else:
238 ratios = ratios[0:len(ratios) - 2] + ")"
239
240 if len(positions) == 2:
241 positions = positions + ")"
242 else:
243 positions = positions[0:len(positions) - 2] + ")"
244
245 r("x <- " + positions)
246 r("y <- " + ratios)
247
248 hist_mb_values = "c("
249 for position in sorted(hist_dict_mb):
250 hist_mb_values = hist_mb_values + str(hist_dict_mb[position]) + ", "
251
252 if len(hist_mb_values) == 2:
253 hist_mb_values = hist_mb_values + ")"
254 else:
255 hist_mb_values = hist_mb_values[0:len(hist_mb_values) - 2] + ")"
256
257 hist_5kb_values = "c("
258 for position in sorted(hist_dict_5kb):
259 hist_5kb_values = hist_5kb_values + str(hist_dict_5kb[position]) + ", "
260
261 if len(hist_5kb_values) == 2:
262 hist_5kb_values = hist_5kb_values + ")"
263 else:
264 hist_5kb_values = hist_5kb_values[0:len(hist_5kb_values) - 2] + ")"
265
266 r("xz <- " + hist_mb_values)
267 r("yz <- " + hist_5kb_values)
268
269 max_break_str = str(max_breaks)
270 break_unit_str = str(Decimal(break_unit))
271 half_break_unit_str = str(Decimal(break_unit) / Decimal(2))
272 break_penta_unit_str = str(Decimal(break_unit) * Decimal(5))
273
274 if (standardize=='true'):
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 +"')")
276 r("lines(loess.smooth(x, y, span = %f "%loess_span + "), lwd=5, col='"+ loess_color +"')")
277 r("axis(1, at=seq(0, " + max_break_str + ", by=" + break_unit_str + "), labels=FALSE, tcl=-0.5)")
278 r("axis(1, at=seq(0, " + max_break_str + ", by=" + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
279 r("axis(2, at=seq(floor(min(y)), 1, by=0.1), labels=FALSE, tcl=-0.2)")
280 elif (standardize=='false'):
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 +"')")
282 r("lines(loess.smooth(x, y, span = %f "%loess_span + "), lwd=5, col='"+ loess_color +"')")
283 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)")
284 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
285 r("axis(2, at=seq(floor(min(y)), 1, by=0.1), labels=FALSE, tcl=-0.2)")
286
287 if draw_secondary_grid_lines:
288 r("abline(h = seq(floor(min(y)), 1, by=0.1), v = seq(floor(min(x)), length(x), by= 1), col='gray')")
289 else:
290 r("grid(lty = 1, col = 'gray')")
291
292 if (standardize=='true'):
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 + "')")
294 r("barplot(yz, space = 0, add=TRUE, width = " + half_break_unit_str + ", col=rgb(1, 0, 0, 1))")
295 r("axis(1, hadj = 1, at=seq(0, " + max_break_str + ", by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)")
296 r("axis(1, at=seq(0, " + max_break_str + ", by= " + break_penta_unit_str + "), labels=TRUE, tcl=-0.5)")
297 r("axis(1, at=seq(0, " + max_break_str + ", by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
298 elif (standardize=='false'):
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 + "')")
300 r("barplot(yz, space = 0, add=TRUE, width = 0.5, col=rgb(1, 0, 0, 1))")
301 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_unit_str + "), labels=FALSE, tcl=-0.5)")
302 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + break_penta_unit_str + "), labels=TRUE, tcl=-0.5)")
303 r("axis(1, at=seq(0, as.integer( ' " + str(breaks) + " '), by= " + half_break_unit_str + "), labels=FALSE, tcl=-0.25)")
304
305
306 def build_haw_snp_dictionary(haw_vcf = None):
307 haw_snps = {}
308
309 i_file = open(haw_vcf, 'rU')
310 reader = csv.reader(i_file, delimiter = '\t')
311
312 skip_headers(reader = reader, i_file = i_file)
313
314 for row in reader:
315 #print row
316 chromosome = row[0].upper()
317 chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE)
318 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
319
320 if chromosome != 'MTDNA':
321 position = row[1]
322 haw_snp_id = row[2]
323 ref_allele = row[3]
324 alt_allele = row[4]
325
326 info = row[7]
327
328 mapping_unit = info.replace("MPU=", "")
329
330 location = chromosome + ":" + position
331 haw_snps[location] = (alt_allele, haw_snp_id, mapping_unit)
332
333 i_file.close()
334
335 return haw_snps
336
337 def calculate_normalized_histogram_bins_per_xbase(pileup_info = None, xbase = 1000000, normalize_bins = None):
338 normalized_histogram_bins_per_xbase = {}
339
340 ref_snp_count_per_xbase = get_ref_snp_count_per_xbase(pileup_info = pileup_info, xbase = xbase)
341 mean_zero_snp_count_per_chromosome = get_mean_zero_snp_count_per_chromosome(pileup_info = pileup_info, xbase = xbase)
342 zero_snp_count_per_xbase = get_zero_snp_count_per_xbase(pileup_info = pileup_info, xbase = xbase)
343
344 for location in ref_snp_count_per_xbase:
345 chromosome = location.split(':')[0]
346 mean_zero_snp_count = mean_zero_snp_count_per_chromosome[chromosome]
347 ref_snp_count = ref_snp_count_per_xbase[location]
348
349 zero_snp_count = 0
350 if location in zero_snp_count_per_xbase:
351 zero_snp_count = zero_snp_count_per_xbase[location]
352
353 if normalize_bins == 'true':
354 if zero_snp_count == 0 or ref_snp_count == 0:
355 normalized_histogram_bins_per_xbase[location] = 0
356 elif zero_snp_count == ref_snp_count:
357 normalized_histogram_bins_per_xbase[location] = 0
358 else:
359 normalized_histogram_bins_per_xbase[location] = (Decimal(zero_snp_count) / (Decimal(ref_snp_count)-Decimal(zero_snp_count))) * Decimal(mean_zero_snp_count)
360 else:
361 normalized_histogram_bins_per_xbase[location] = zero_snp_count
362
363 return normalized_histogram_bins_per_xbase
364
365 def get_ref_snp_count_per_xbase(pileup_info = None, xbase = 1000000):
366 ref_snps_per_xbase = {}
367
368 for location in pileup_info:
369 location_info = location.split(':')
370
371 chromosome = location_info[0].upper()
372 chromosome = re.sub("chr", "", chromosome, flags = re.IGNORECASE)
373 chromosome = re.sub("CHROMOSOME_", "", chromosome, flags = re.IGNORECASE)
374
375 position = location_info[1]
376 xbase_position = (int(position) / xbase) + 1
377
378 location = chromosome + ":" + str(xbase_position)
379 if location in ref_snps_per_xbase:
380 ref_snps_per_xbase[location] = ref_snps_per_xbase[location] + 1
381 else:
382 ref_snps_per_xbase[location] = 1
383
384 return ref_snps_per_xbase
385
386 def get_mean_zero_snp_count_per_chromosome(pileup_info, xbase = 1000000):
387 sample_snp_count_per_xbase = {}
388
389 for location in pileup_info:
390 alt_allele_count, ref_allele_count, read_depth, ratio, haw_snp_id, mapping_unit = pileup_info[location]
391
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()