Mercurial > repos > devteam > microsats_mutability
comparison microsats_mutability.py @ 0:0530d2a49487 draft
Imported from capsule None
author | devteam |
---|---|
date | Tue, 01 Apr 2014 09:13:04 -0400 |
parents | |
children |
comparison
equal
deleted
inserted
replaced
-1:000000000000 | 0:0530d2a49487 |
---|---|
1 #!/usr/bin/env python | |
2 #Guruprasad Ananda | |
3 """ | |
4 This tool computes microsatellite mutability for the orthologous microsatellites fetched from 'Extract Orthologous Microsatellites from pair-wise alignments' tool. | |
5 """ | |
6 import fileinput | |
7 import string | |
8 import sys | |
9 import tempfile | |
10 from galaxy.tools.util.galaxyops import * | |
11 from bx.intervals.io import * | |
12 from bx.intervals.operations import quicksect | |
13 | |
14 fout = open(sys.argv[2],'w') | |
15 p_group = int(sys.argv[3]) #primary "group-by" feature | |
16 p_bin_size = int(sys.argv[4]) | |
17 s_group = int(sys.argv[5]) #sub-group by feature | |
18 s_bin_size = int(sys.argv[6]) | |
19 mono_threshold = 9 | |
20 non_mono_threshold = 4 | |
21 p_group_cols = [p_group, p_group+7] | |
22 s_group_cols = [s_group, s_group+7] | |
23 num_generations = int(sys.argv[7]) | |
24 region = sys.argv[8] | |
25 int_file = sys.argv[9] | |
26 if int_file != "None": #User has specified an interval file | |
27 try: | |
28 fint = open(int_file, 'r') | |
29 dbkey_i = sys.argv[10] | |
30 chr_col_i, start_col_i, end_col_i, strand_col_i = parse_cols_arg( sys.argv[11] ) | |
31 except: | |
32 stop_err("Unable to open input Interval file") | |
33 | |
34 | |
35 def stop_err(msg): | |
36 sys.stderr.write(msg) | |
37 sys.exit() | |
38 | |
39 | |
40 def reverse_complement(text): | |
41 DNA_COMP = string.maketrans( "ACGTacgt", "TGCAtgca" ) | |
42 comp = [ch for ch in text.translate(DNA_COMP)] | |
43 comp.reverse() | |
44 return "".join(comp) | |
45 | |
46 | |
47 def get_unique_elems(elems): | |
48 seen = set() | |
49 return[x for x in elems if x not in seen and not seen.add(x)] | |
50 | |
51 | |
52 def get_binned_lists(uniqlist, binsize): | |
53 binnedlist = [] | |
54 uniqlist.sort() | |
55 start = int(uniqlist[0]) | |
56 bin_ind = 0 | |
57 l_ind = 0 | |
58 binnedlist.append([]) | |
59 while l_ind < len(uniqlist): | |
60 elem = int(uniqlist[l_ind]) | |
61 if elem in range(start, start+binsize): | |
62 binnedlist[bin_ind].append(elem) | |
63 else: | |
64 start += binsize | |
65 bin_ind += 1 | |
66 binnedlist.append([]) | |
67 binnedlist[bin_ind].append(elem) | |
68 l_ind += 1 | |
69 return binnedlist | |
70 | |
71 | |
72 def fetch_weight(H, C, t): | |
73 if (H-(C-H)) < t: | |
74 return 2.0 | |
75 else: | |
76 return 1.0 | |
77 | |
78 | |
79 def mutabilityEstimator(repeats1, repeats2, thresholds): | |
80 mut_num = 0.0 #Mutability Numerator | |
81 mut_den = 0.0 #Mutability denominator | |
82 for ind, H in enumerate(repeats1): | |
83 C = repeats2[ind] | |
84 t = thresholds[ind] | |
85 w = fetch_weight(H, C, t) | |
86 mut_num += ((H-C)*(H-C)*w) | |
87 mut_den += w | |
88 return [mut_num, mut_den] | |
89 | |
90 | |
91 def output_writer(blk, blk_lines): | |
92 global winspecies, speciesind | |
93 all_elems_1 = [] | |
94 all_elems_2 = [] | |
95 all_s_elems_1 = [] | |
96 all_s_elems_2 = [] | |
97 for bline in blk_lines: | |
98 if not(bline): | |
99 continue | |
100 items = bline.split('\t') | |
101 seq1 = items[1] | |
102 seq2 = items[8] | |
103 if p_group_cols[0] == 6: | |
104 items[p_group_cols[0]] = int(items[p_group_cols[0]]) | |
105 items[p_group_cols[1]] = int(items[p_group_cols[1]]) | |
106 if s_group_cols[0] == 6: | |
107 items[s_group_cols[0]] = int(items[s_group_cols[0]]) | |
108 items[s_group_cols[1]] = int(items[s_group_cols[1]]) | |
109 all_elems_1.append(items[p_group_cols[0]]) #primary col elements for species 1 | |
110 all_elems_2.append(items[p_group_cols[1]]) #primary col elements for species 2 | |
111 if s_group_cols[0] != -1: #sub-group is not None | |
112 all_s_elems_1.append(items[s_group_cols[0]]) #secondary col elements for species 1 | |
113 all_s_elems_2.append(items[s_group_cols[1]]) #secondary col elements for species 2 | |
114 uniq_elems_1 = get_unique_elems(all_elems_1) | |
115 uniq_elems_2 = get_unique_elems(all_elems_2) | |
116 if s_group_cols[0] != -1: | |
117 uniq_s_elems_1 = get_unique_elems(all_s_elems_1) | |
118 uniq_s_elems_2 = get_unique_elems(all_s_elems_2) | |
119 mut1 = {} | |
120 mut2 = {} | |
121 count1 = {} | |
122 count2 = {} | |
123 """ | |
124 if p_group_cols[0] == 7: #i.e. the option chosen is group-by unit(AG, GTC, etc) | |
125 uniq_elems_1 = get_unique_units(j.sort(lambda x, y: len(x)-len(y))) | |
126 """ | |
127 if p_group_cols[0] == 6: #i.e. the option chosen is group-by repeat number. | |
128 uniq_elems_1 = get_binned_lists( uniq_elems_1, p_bin_size ) | |
129 uniq_elems_2 = get_binned_lists( uniq_elems_2, p_bin_size ) | |
130 | |
131 if s_group_cols[0] == 6: #i.e. the option chosen is subgroup-by repeat number. | |
132 uniq_s_elems_1 = get_binned_lists( uniq_s_elems_1, s_bin_size ) | |
133 uniq_s_elems_2 = get_binned_lists( uniq_s_elems_2, s_bin_size ) | |
134 | |
135 for pitem1 in uniq_elems_1: | |
136 #repeats1 = [] | |
137 #repeats2 = [] | |
138 thresholds = [] | |
139 if s_group_cols[0] != -1: #Sub-group by feature is not None | |
140 for sitem1 in uniq_s_elems_1: | |
141 repeats1 = [] | |
142 repeats2 = [] | |
143 if type(sitem1) == type(''): | |
144 sitem1 = sitem1.strip() | |
145 for bline in blk_lines: | |
146 belems = bline.split('\t') | |
147 if type(pitem1) == list: | |
148 if p_group_cols[0] == 6: | |
149 belems[p_group_cols[0]] = int(belems[p_group_cols[0]]) | |
150 if belems[p_group_cols[0]] in pitem1: | |
151 if belems[s_group_cols[0]] == sitem1: | |
152 repeats1.append(int(belems[6])) | |
153 repeats2.append(int(belems[13])) | |
154 if belems[4] == 'mononucleotide': | |
155 thresholds.append(mono_threshold) | |
156 else: | |
157 thresholds.append(non_mono_threshold) | |
158 mut1[str(pitem1)+'\t'+str(sitem1)] = mutabilityEstimator( repeats1, repeats2, thresholds ) | |
159 if region == 'align': | |
160 count1[str(pitem1)+'\t'+str(sitem1)] = min( sum(repeats1), sum(repeats2) ) | |
161 else: | |
162 if winspecies == 1: | |
163 count1["%s\t%s" % ( pitem1, sitem1 )] = sum(repeats1) | |
164 elif winspecies == 2: | |
165 count1["%s\t%s" % ( pitem1, sitem1 )] = sum(repeats2) | |
166 else: | |
167 if type(sitem1) == list: | |
168 if s_group_cols[0] == 6: | |
169 belems[s_group_cols[0]] = int(belems[s_group_cols[0]]) | |
170 if belems[p_group_cols[0]] == pitem1 and belems[s_group_cols[0]] in sitem1: | |
171 repeats1.append(int(belems[6])) | |
172 repeats2.append(int(belems[13])) | |
173 if belems[4] == 'mononucleotide': | |
174 thresholds.append(mono_threshold) | |
175 else: | |
176 thresholds.append(non_mono_threshold) | |
177 mut1["%s\t%s" % ( pitem1, sitem1 )] = mutabilityEstimator( repeats1, repeats2, thresholds ) | |
178 if region == 'align': | |
179 count1[str(pitem1)+'\t'+str(sitem1)] = min( sum(repeats1), sum(repeats2) ) | |
180 else: | |
181 if winspecies == 1: | |
182 count1[str(pitem1)+'\t'+str(sitem1)] = sum(repeats1) | |
183 elif winspecies == 2: | |
184 count1[str(pitem1)+'\t'+str(sitem1)] = sum(repeats2) | |
185 else: | |
186 if belems[p_group_cols[0]] == pitem1 and belems[s_group_cols[0]] == sitem1: | |
187 repeats1.append(int(belems[6])) | |
188 repeats2.append(int(belems[13])) | |
189 if belems[4] == 'mononucleotide': | |
190 thresholds.append(mono_threshold) | |
191 else: | |
192 thresholds.append(non_mono_threshold) | |
193 mut1["%s\t%s" % ( pitem1, sitem1 )] = mutabilityEstimator( repeats1, repeats2, thresholds ) | |
194 if region == 'align': | |
195 count1[str(pitem1)+'\t'+str(sitem1)] = min( sum(repeats1), sum(repeats2) ) | |
196 else: | |
197 if winspecies == 1: | |
198 count1["%s\t%s" % ( pitem1, sitem1 )] = sum(repeats1) | |
199 elif winspecies == 2: | |
200 count1["%s\t%s" % ( pitem1, sitem1 )] = sum(repeats2) | |
201 else: #Sub-group by feature is None | |
202 for bline in blk_lines: | |
203 belems = bline.split('\t') | |
204 if type(pitem1) == list: | |
205 #print >> sys.stderr, "item: " + str(item1) | |
206 if p_group_cols[0] == 6: | |
207 belems[p_group_cols[0]] = int(belems[p_group_cols[0]]) | |
208 if belems[p_group_cols[0]] in pitem1: | |
209 repeats1.append(int(belems[6])) | |
210 repeats2.append(int(belems[13])) | |
211 if belems[4] == 'mononucleotide': | |
212 thresholds.append(mono_threshold) | |
213 else: | |
214 thresholds.append(non_mono_threshold) | |
215 else: | |
216 if belems[p_group_cols[0]] == pitem1: | |
217 repeats1.append(int(belems[6])) | |
218 repeats2.append(int(belems[13])) | |
219 if belems[4] == 'mononucleotide': | |
220 thresholds.append(mono_threshold) | |
221 else: | |
222 thresholds.append(non_mono_threshold) | |
223 mut1["%s" % (pitem1)] = mutabilityEstimator( repeats1, repeats2, thresholds ) | |
224 if region == 'align': | |
225 count1["%s" % (pitem1)] = min( sum(repeats1), sum(repeats2) ) | |
226 else: | |
227 if winspecies == 1: | |
228 count1[str(pitem1)] = sum(repeats1) | |
229 elif winspecies == 2: | |
230 count1[str(pitem1)] = sum(repeats2) | |
231 | |
232 for pitem2 in uniq_elems_2: | |
233 #repeats1 = [] | |
234 #repeats2 = [] | |
235 thresholds = [] | |
236 if s_group_cols[0] != -1: #Sub-group by feature is not None | |
237 for sitem2 in uniq_s_elems_2: | |
238 repeats1 = [] | |
239 repeats2 = [] | |
240 if type(sitem2)==type(''): | |
241 sitem2 = sitem2.strip() | |
242 for bline in blk_lines: | |
243 belems = bline.split('\t') | |
244 if type(pitem2) == list: | |
245 if p_group_cols[0] == 6: | |
246 belems[p_group_cols[1]] = int(belems[p_group_cols[1]]) | |
247 if belems[p_group_cols[1]] in pitem2 and belems[s_group_cols[1]] == sitem2: | |
248 repeats2.append(int(belems[13])) | |
249 repeats1.append(int(belems[6])) | |
250 if belems[4] == 'mononucleotide': | |
251 thresholds.append(mono_threshold) | |
252 else: | |
253 thresholds.append(non_mono_threshold) | |
254 mut2["%s\t%s" % ( pitem2, sitem2 )] = mutabilityEstimator( repeats2, repeats1, thresholds ) | |
255 #count2[str(pitem2)+'\t'+str(sitem2)]=len(repeats2) | |
256 if region == 'align': | |
257 count2["%s\t%s" % ( pitem2, sitem2 )] = min( sum(repeats1), sum(repeats2) ) | |
258 else: | |
259 if winspecies == 1: | |
260 count2["%s\t%s" % ( pitem2, sitem2 )] = len(repeats2) | |
261 elif winspecies == 2: | |
262 count2["%s\t%s" % ( pitem2, sitem2 )] = len(repeats1) | |
263 else: | |
264 if type(sitem2) == list: | |
265 if s_group_cols[0] == 6: | |
266 belems[s_group_cols[1]] = int(belems[s_group_cols[1]]) | |
267 if belems[p_group_cols[1]] == pitem2 and belems[s_group_cols[1]] in sitem2: | |
268 repeats2.append(int(belems[13])) | |
269 repeats1.append(int(belems[6])) | |
270 if belems[4] == 'mononucleotide': | |
271 thresholds.append(mono_threshold) | |
272 else: | |
273 thresholds.append(non_mono_threshold) | |
274 mut2["%s\t%s" % ( pitem2, sitem2 )] = mutabilityEstimator( repeats2, repeats1, thresholds ) | |
275 if region == 'align': | |
276 count2["%s\t%s" % ( pitem2, sitem2 )] = min( sum(repeats1), sum(repeats2) ) | |
277 else: | |
278 if winspecies == 1: | |
279 count2["%s\t%s" % ( pitem2, sitem2 )] = len(repeats2) | |
280 elif winspecies == 2: | |
281 count2["%s\t%s" % ( pitem2, sitem2 )] = len(repeats1) | |
282 else: | |
283 if belems[p_group_cols[1]] == pitem2 and belems[s_group_cols[1]] == sitem2: | |
284 repeats1.append(int(belems[13])) | |
285 repeats2.append(int(belems[6])) | |
286 if belems[4] == 'mononucleotide': | |
287 thresholds.append(mono_threshold) | |
288 else: | |
289 thresholds.append(non_mono_threshold) | |
290 mut2["%s\t%s" % ( pitem2, sitem2 )] = mutabilityEstimator( repeats2, repeats1, thresholds ) | |
291 if region == 'align': | |
292 count2["%s\t%s" % ( pitem2, sitem2 )] = min( sum(repeats1), sum(repeats2) ) | |
293 else: | |
294 if winspecies == 1: | |
295 count2["%s\t%s" % ( pitem2, sitem2 )] = len(repeats2) | |
296 elif winspecies == 2: | |
297 count2["%s\t%s" % ( pitem2, sitem2 )] = len(repeats1) | |
298 else: #Sub-group by feature is None | |
299 for bline in blk_lines: | |
300 belems = bline.split('\t') | |
301 if type(pitem2) == list: | |
302 if p_group_cols[0] == 6: | |
303 belems[p_group_cols[1]] = int(belems[p_group_cols[1]]) | |
304 if belems[p_group_cols[1]] in pitem2: | |
305 repeats2.append(int(belems[13])) | |
306 repeats1.append(int(belems[6])) | |
307 if belems[4] == 'mononucleotide': | |
308 thresholds.append(mono_threshold) | |
309 else: | |
310 thresholds.append(non_mono_threshold) | |
311 else: | |
312 if belems[p_group_cols[1]] == pitem2: | |
313 repeats2.append(int(belems[13])) | |
314 repeats1.append(int(belems[6])) | |
315 if belems[4] == 'mononucleotide': | |
316 thresholds.append(mono_threshold) | |
317 else: | |
318 thresholds.append(non_mono_threshold) | |
319 mut2["%s" % (pitem2)] = mutabilityEstimator( repeats2, repeats1, thresholds ) | |
320 if region == 'align': | |
321 count2["%s" % (pitem2)] = min( sum(repeats1), sum(repeats2) ) | |
322 else: | |
323 if winspecies == 1: | |
324 count2["%s" % (pitem2)] = sum(repeats2) | |
325 elif winspecies == 2: | |
326 count2["%s" % (pitem2)] = sum(repeats1) | |
327 for key in mut1.keys(): | |
328 if key in mut2.keys(): | |
329 mut = (mut1[key][0]+mut2[key][0])/(mut1[key][1]+mut2[key][1]) | |
330 count = count1[key] | |
331 del mut2[key] | |
332 else: | |
333 unit_found = False | |
334 if p_group_cols[0] == 7 or s_group_cols[0] == 7: #if it is Repeat Unit (AG, GCT etc.) check for reverse-complements too | |
335 if p_group_cols[0] == 7: | |
336 this, other = 0, 1 | |
337 else: | |
338 this, other = 1, 0 | |
339 groups1 = key.split('\t') | |
340 mutn = mut1[key][0] | |
341 mutd = mut1[key][1] | |
342 count = 0 | |
343 for key2 in mut2.keys(): | |
344 groups2 = key2.split('\t') | |
345 if groups1[other] == groups2[other]: | |
346 if groups1[this] in groups2[this]*2 or reverse_complement(groups1[this]) in groups2[this]*2: | |
347 #mut = (mut1[key][0]+mut2[key2][0])/(mut1[key][1]+mut2[key2][1]) | |
348 mutn += mut2[key2][0] | |
349 mutd += mut2[key2][1] | |
350 count += int(count2[key2]) | |
351 unit_found = True | |
352 del mut2[key2] | |
353 #break | |
354 if unit_found: | |
355 mut = mutn/mutd | |
356 else: | |
357 mut = mut1[key][0]/mut1[key][1] | |
358 count = count1[key] | |
359 mut = "%.2e" % (mut/num_generations) | |
360 if region == 'align': | |
361 print >> fout, str(blk) + '\t'+seq1 + '\t' + seq2 + '\t' +key.strip()+ '\t'+str(mut) + '\t'+ str(count) | |
362 elif region == 'win': | |
363 fout.write("%s\t%s\t%s\t%s\n" % ( blk, key.strip(), mut, count )) | |
364 fout.flush() | |
365 | |
366 #catch any remaining repeats, for instance if the orthologous position contained different repeat units | |
367 for remaining_key in mut2.keys(): | |
368 mut = mut2[remaining_key][0]/mut2[remaining_key][1] | |
369 mut = "%.2e" % (mut/num_generations) | |
370 count = count2[remaining_key] | |
371 if region == 'align': | |
372 print >> fout, str(blk) + '\t'+seq1 + '\t'+seq2 + '\t'+remaining_key.strip()+ '\t'+str(mut)+ '\t'+ str(count) | |
373 elif region == 'win': | |
374 fout.write("%s\t%s\t%s\t%s\n" % ( blk, remaining_key.strip(), mut, count )) | |
375 fout.flush() | |
376 #print >> fout, blk + '\t'+remaining_key.strip()+ '\t'+str(mut)+ '\t'+ str(count) | |
377 | |
378 | |
379 def counter(node, start, end, report_func): | |
380 if start <= node.start < end and start < node.end <= end: | |
381 report_func(node) | |
382 if node.right: | |
383 counter(node.right, start, end, report_func) | |
384 if node.left: | |
385 counter(node.left, start, end, report_func) | |
386 elif node.start < start and node.right: | |
387 counter(node.right, start, end, report_func) | |
388 elif node.start >= end and node.left and node.left.maxend > start: | |
389 counter(node.left, start, end, report_func) | |
390 | |
391 | |
392 def main(): | |
393 infile = sys.argv[1] | |
394 | |
395 for i, line in enumerate( file ( infile )): | |
396 line = line.rstrip('\r\n') | |
397 if len( line )>0 and not line.startswith( '#' ): | |
398 elems = line.split( '\t' ) | |
399 break | |
400 if i == 30: | |
401 break # Hopefully we'll never get here... | |
402 | |
403 if len( elems ) != 15: | |
404 stop_err( "This tool only works on tabular data output by 'Extract Orthologous Microsatellites from pair-wise alignments' tool. The data in your input dataset is either missing or not formatted properly." ) | |
405 global winspecies, speciesind | |
406 if region == 'win': | |
407 if dbkey_i in elems[1]: | |
408 winspecies = 1 | |
409 speciesind = 1 | |
410 elif dbkey_i in elems[8]: | |
411 winspecies = 2 | |
412 speciesind = 8 | |
413 else: | |
414 stop_err("The species build corresponding to your interval file is not present in the Microsatellite file.") | |
415 | |
416 fin = open(infile, 'r') | |
417 skipped = 0 | |
418 linestr = "" | |
419 | |
420 if region == 'win': | |
421 msats = NiceReaderWrapper( fileinput.FileInput( infile ), | |
422 chrom_col = speciesind, | |
423 start_col = speciesind+1, | |
424 end_col = speciesind+2, | |
425 strand_col = -1, | |
426 fix_strand = True) | |
427 msatTree = quicksect.IntervalTree() | |
428 for item in msats: | |
429 if type( item ) is GenomicInterval: | |
430 msatTree.insert( item, msats.linenum, item.fields ) | |
431 | |
432 for iline in fint: | |
433 try: | |
434 iline = iline.rstrip('\r\n') | |
435 if not(iline) or iline == "": | |
436 continue | |
437 ielems = iline.strip("\r\n").split('\t') | |
438 ichr = ielems[chr_col_i] | |
439 istart = int(ielems[start_col_i]) | |
440 iend = int(ielems[end_col_i]) | |
441 isrc = "%s.%s" % ( dbkey_i, ichr ) | |
442 if isrc not in msatTree.chroms: | |
443 continue | |
444 result = [] | |
445 root = msatTree.chroms[isrc] #root node for the chrom | |
446 counter(root, istart, iend, lambda node: result.append( node )) | |
447 if not(result): | |
448 continue | |
449 tmpfile1 = tempfile.NamedTemporaryFile('wb+') | |
450 for node in result: | |
451 tmpfile1.write("%s\n" % "\t".join( node.other )) | |
452 | |
453 tmpfile1.seek(0) | |
454 output_writer(iline, tmpfile1.readlines()) | |
455 except: | |
456 skipped += 1 | |
457 if skipped: | |
458 print "Skipped %d intervals as invalid." % (skipped) | |
459 elif region == 'align': | |
460 if s_group_cols[0] != -1: | |
461 print >> fout, "#Window\tSpecies_1\tSpecies_2\tGroupby_Feature\tSubGroupby_Feature\tMutability\tCount" | |
462 else: | |
463 print >> fout, "#Window\tSpecies_1\tWindow_Start\tWindow_End\tSpecies_2\tGroupby_Feature\tMutability\tCount" | |
464 prev_bnum = -1 | |
465 try: | |
466 for line in fin: | |
467 line = line.strip("\r\n") | |
468 if not(line) or line == "": | |
469 continue | |
470 elems = line.split('\t') | |
471 try: | |
472 assert int(elems[0]) | |
473 assert len(elems) == 15 | |
474 except: | |
475 continue | |
476 new_bnum = int(elems[0]) | |
477 if new_bnum != prev_bnum: | |
478 if prev_bnum != -1: | |
479 output_writer(prev_bnum, linestr.strip().replace('\r','\n').split('\n')) | |
480 linestr = line + "\n" | |
481 else: | |
482 linestr += line | |
483 linestr += "\n" | |
484 prev_bnum = new_bnum | |
485 output_writer(prev_bnum, linestr.strip().replace('\r','\n').split('\n')) | |
486 except Exception, ea: | |
487 print >> sys.stderr, ea | |
488 skipped += 1 | |
489 if skipped: | |
490 print "Skipped %d lines as invalid." % (skipped) | |
491 | |
492 | |
493 if __name__ == "__main__": | |
494 main() |