-
Notifications
You must be signed in to change notification settings - Fork 5
/
Superfold.py
1423 lines (1090 loc) · 46.1 KB
/
Superfold.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
#!/usr/bin/env python
# Primary script to run the SuperFold analysis pipeline (in other words RUN THIS SCRIPT)
#
# - Requires a .map file as an argument (see README for details)
# - Requires the following programs be executable from any location (i.e. in the PATH):
# python, Fold, partition, ProbabilityPlot
# - Take a look at the README for other required modules, installation, and execution help.
# - Public release 1.0
# - Copyright Greggory M Rice 2014
# - Update: Sep 30, 2020: Addressed issues with SHAPE reactivity not displaying on Shannon entropy plot.
# Altered the Shannon Entropy plot to display Shannon and SHAPE on separate y axes.
# Fixed np.nan issue with SHAPE plotting.
# -999 values no longer counted as low SHAPE when determining low SHAPE/low Shannon regions
# Fixed issue with beginning of sequence being incorrectly included in low SHAPE/low Shannon region
##################################################################################
# GPL statement:
# This file is part of Shapemapper.
#
# SuperFold is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# SuperFold is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with SuperFold. If not, see <http://www.gnu.org/licenses/>.
# 17 Nov 2014
# all rights reserved
# 1.0 build
##################################################################################
import batchSubmit as batch
import argparse, sys, shlex, os, subprocess, hashlib, time
from RNAtools import dotPlot, CT, padCT, writeSHAPE
# set the plotting environment to be non-interactive
import matplotlib as mtl
mtl.use("Agg")
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
# import arc drawing functions
from drawArcRibbons_simple import writeManyPlot as arcplot
import numpy as np
from PyCircleCompareSF import makeCircle
class shapeMAP:
def __init__(self,fIN):
self.seq = []
self.ntNum = []
self.shape = []
self.stdErr = []
self.zfactor = []
if fIN:
parsed = self.readFile(fIN)
self.ntNum = map(int,parsed[0])
self.shape = map(float,parsed[1])
self.stdErr= map(float,parsed[2])
self.seq = parsed[3]
if len(parsed.keys()) == 5:
try:
self.zfactor = map(float,parsed[4])
except:
print "formatting error: {0}\nNon float in zfactor column".format(fIN)
sys.exit()
# replace T's with U's
for i in range(len(self.seq)):
if self.seq[i] == "T": self.seq[i] = "U"
def readFile(self,fIN):
data = {}
lineNum = 0
for line in open(fIN, "rU").readlines():
x = line.rstrip().split()
# initialize an array obj for the first line
if lineNum == 0:
for i in range(len(x)):
data[i] = [x[i]]
# populate the array obj
else:
for i in range(len(x)):
data[i].append(x[i])
lineNum += 1
return data
def main():
debug = False
# start the stopwatch
startTime = time.time()
# check to see if cmd line programs are available
runCheck()
# parse the input arguments
args = parseArgs()
# set the results directory
resultsDir = "results_"+args.safeName
print resultsDir
try:
os.mkdir(resultsDir)
except:
pass
try:
os.mkdir(resultsDir+"/regions/")
except:
pass
# set location of the logfile
logFile = open("{0}/log_{0}.txt".format(resultsDir),"a")
sys.stdout = logFile
print >> sys.stderr, "log file location: {0}/log_{0}.txt".format(resultsDir)
print "\n"*3,"#"*51
print """# _____ ______ _ _ #
# / ___| | ___| | | | | #
# \ `--. _ _ _ __ ___ _ __| |_ ___ | | __| | #
# `--. \ | | | '_ \ / _ \ '__| _/ _ \| |/ _` | #
# /\__/ / |_| | |_) | __/ | | || (_) | | (_| | #
# \____/ \__,_| .__/ \___|_| \_| \___/|_|\__,_| #
# | | #
# |_| #"""
print "#{0: ^49}#".format( "" )
print "#{0: ^49}#".format( "Superfold ver. Alpha_22-Sept-2014" )
print "#{0: ^49}#".format( "" )
print "#{0: ^49}#".format("starting job: " + args.safeName)
print "#{0: ^49}#".format( time.strftime("%c") )
print "#{0: ^49}#".format( "" )
print "#"*51,"\n\n# Job Submitted with following attributes:"
print args, "\n"
# first step is to run the partition function
print >> sys.stderr, "\nstarting Partition function calculation..."
partitionPairing = dotPlot()
if not debug:
partitionPairing = generateAndRunPartition(args.mapObj, args.allConstraints,args.partitionWindowSize, args.partitionStepSize, args.safeName, args.SHAPEslope, args.SHAPEintercept, args.np, args.maxPairingDist)
# write the partition function file
partitionFileName="{0}/merged_{1}.dp".format(resultsDir, args.safeName)
if not debug:
partitionPairing.writeDP(partitionFileName)
# debug line
if debug:
partitionPairing = dotPlot(partitionFileName)
# get the 99% most probable pairs to use as constraints in folding
probablePairs99 = partitionPairing.requireProb(0.004364805402450088).pairList()
dsConstraint = {0:[],1:[]}
for i,j in probablePairs99:
dsConstraint[0].append(i)
dsConstraint[1].append(j)
# calculate shannon entropy
bpShannonEntropy = partitionPairing.calcShannon()
# write the shannon entropy in .shape format
shannonEntropyName = "{0}/shannon_{1}.txt".format(resultsDir, args.safeName)
writeSHAPE(bpShannonEntropy,shannonEntropyName)
# generate the folded structure model
print >> sys.stderr, "starting Fold..."
initialStructure = CT()
if not debug:
initialStructure = generateAndRunFold(args.mapObj, args.allConstraints,dsConstraint, args.foldWindowSize, args.foldStepSize, args.safeName,args.SHAPEslope,args.SHAPEintercept,args.np, args.maxPairingDist)
# write the folded structure
initialStructureFileName = "{0}/merged_{1}.ct".format(resultsDir, args.safeName)
if not debug:
initialStructure.writeCT(initialStructureFileName)
#debug
if debug:
initialStructure.readCT(initialStructureFileName)
# write final files and figures
print >> sys.stderr, "drawing figures..."
# add in former pk constraints
pkPair = []
for i,j in zip(args.dsConstraints[0],args.dsConstraints[1]):
pkPair.append((i,j))
nonPKpairs = initialStructure.pairList()
finalStructure = CT()
finalStructure.pair2CT(nonPKpairs+pkPair, seq=initialStructure.seq,name='finalStructure wPKs')
finalStructureName = "{0}/merged_wPK_{1}.ct".format(resultsDir, args.safeName)
# if there are pk pairs in the file, then write a second ct file with pk's included
if pkPair != []:
finalStructure.writeCT(finalStructureName)
# calcualte low shannon/shape regions with expansions based on structure
shannonShapeName = "{0}/shannonShape_{1}.pdf".format(resultsDir, args.safeName)
lowSHAPEregions = mainShannonFunc(args.mapObj.origSHAPE, bpShannonEntropy, shannonShapeName, finalStructure)
# plot the arcs along with the shannon/shape reactivities
arcFileName = "{0}/arcPlot_{1}.pdf".format(resultsDir, args.safeName)
ensembleRNA_splitPlot(partitionPairing, initialStructure, pk=pkPair, outFile=arcFileName)
# export the structures of the low shannon/shape regions
maxChar = len(str(lowSHAPEregions[-1][1]))
# file for containing all regions
ps_comb = "{0}/regions_{1}.ps".format(resultsDir,args.safeName)
ps_write = open(ps_comb, "w")
if args.noPVclient:
try:
import pvclient
except:
print "PVclient failed to load"
args.drawPVclient = False
for i,j in lowSHAPEregions:
#define file names
print >> sys.stderr, i,j
ct_name = "{2}/regions/region_{3}_{0:0>{maxChar}}_{1:0>{maxChar}}.ct".format(i,j,resultsDir,args.safeName,maxChar=maxChar)
ps_name = "{2}/regions/region_{3}_{0:0>{maxChar}}_{1:0>{maxChar}}.ps".format(i,j,resultsDir,args.safeName,maxChar=maxChar)
pvclient_name = "{2}/regions/region_{3}_{0:0>{maxChar}}_{1:0>{maxChar}}".format(i,j,resultsDir,args.safeName,maxChar=maxChar)
# write new ct file
x = finalStructure.cutCT(i,j)
x.name = "region {0}-{1}, ".format(i,j) + args.name
x.writeCT(ct_name)
# circle plotting functions
tmpSHAPE = args.mapObj.origSHAPE[i-1:j]
tmpZeros = np.zeros_like(tmpSHAPE)
# file lines
lines = makeCircle(x,x,tmpZeros,tmpSHAPE,{'i':[],'j':[],'correl':[]},[],offset=i)
w = open(ps_name,"w")
w.write(lines)
ps_write.write(lines)
w.close()
if args.noPVclient:
try:
pvclient.python_client(x, tmpSHAPE, i, pvclient_name)
except:
print "Structure drawing failed Region {0}-{1}".format(i,j)
ps_write.close()
runtime = "{0:.2f}".format(time.time() - startTime)
print "\n","#"*51
print "#{0:^49}#".format("job finished: "+args.safeName)
print "#{0:^49}#".format( time.strftime("%c"))
print "#{0:^49}#".format("Total Runtime: " + runtime + " sec.")
print "#"*51
def ensembleRNA_splitPlot(dpObj, ctObj, pk=None, outFile="arcs.pdf"):
def rgb_int2pct(rgbArr):
out = []
for rgb in rgbArr:
out.append((rgb[0]/255.0, rgb[1]/255.0, rgb[2]/255.0))
return out
x = dpObj
y = ctObj
# binning is in log10 scale
#binning = [0.0,0.09691,0.5228,1.0,2.0]
binning = [1.5228, 1.0, 0.5228, 0.09691, 0.0]
# 3% 10% 30% 80% 100%
alphaList = [0.7, 0.7, 0.7, 0.3]
alphaList = [0.3, 0.7, 0.7, 0.7]
#alphaList = [1.0, 1.0, 1.0, 1.0]
#colorList = ["red", "orange", "yellow", "green","blue", "violet"]
# nat methods palett
#colorList = [(215, 25, 28), (253, 174, 97), (171, 221, 164), (43, 131, 186)]
colorList = [ (150,150,150), (255,204,0), (72,143,205) ,(81, 184, 72) ]
# colorbrewer palett
#colorList = [ (43, 131, 186), (171, 221, 164), (253, 174, 97), (215, 25, 28)]
colorList = rgb_int2pct(colorList)
nucArr = []
colors = []
alpha = []
# bin the pairs by cutoff
for i in range(0, len(binning)-1):
probPairs = x.requireProb(binning[i],binning[i+1]).pairList()
for pair in probPairs:
temp = np.zeros_like(y.ct)
temp[pair[0]-1] = pair[1]
#tempCT = RNA.CT()
#tempCT.pair2CT([pair],y.seq)
#nucArr.append(tempCT.stripCT())
nucArr.append(temp)
#add a color from the choice list
colors.append(colorList[i])
alpha.append(alphaList[i])
if pk:
for pair in pk:
temp = np.zeros_like(y.ct)
temp[pair[0]-1] = pair[1]
nucArr.append(temp)
colors.append((0,0,0))
alpha.append(0.8)
#nucArr.append(y.stripCT())
#colors.append("gray")
arcplot(outPath=outFile, pairedNucArr=nucArr, arcColors=colors,seq=y.seq, alpha=alpha, maxDistance=None)
def generateAndRunFold(mapObj, constraints, dsConstraints, windowSize, stepSize, prefix, shapeSlope, shapeIntercept, nprocs, maxDist):
#make list of commands, skip those files that have already been calculated
# run those commands
# run master model, return structure
rnaLength = len(mapObj.seq)
#print rnaLength
# make the directory if it doesn't exist
dirname = "fold_" + prefix
try:
os.mkdir(dirname)
except:
pass
# generate the files for the run and the jobs to submit
jobQueue1 = []
# handle the case where the folding window can cover almost the entire RNA
if rnaLength-windowSize<200:
cut_i = 1
cut_j = rnaLength
fname = "{0}/{1}_{2}_{3}".format(dirname,prefix,cut_i,cut_j)
genFiles(mapObj,constraints,dsConstraints,cut_i,cut_j,fname)
foldCMD = "Fold {0}.seq {0}.ct -sh {0}.shape -sm {1} -si {2} -md {3} -C {0}.const -m 100 -w 0".format(fname, shapeSlope,shapeIntercept, maxDist)
jobQueue1.append(shlex.split(foldCMD))
else:
# middle folds
for i in range(1,rnaLength-windowSize,stepSize):
cut_i = i
cut_j = i+windowSize-1
fname = "{0}/{1}_{2}_{3}".format(dirname,prefix,cut_i,cut_j)
genFiles(mapObj,constraints,dsConstraints,cut_i,cut_j,fname)
foldCMD = "Fold {0}.seq {0}.ct -sh {0}.shape -sm {1} -si {2} -md {3} -C {0}.const -m 100 -w 0".format(fname, shapeSlope,shapeIntercept, maxDist)
jobQueue1.append(shlex.split(foldCMD))
# 5prime folds
# 3prime folds
for i in [-100,-50,50,100]:
cut5prime_j = windowSize+i
fname = "{0}/{1}_{2}_{3}".format(dirname,prefix,1,cut5prime_j)
genFiles(mapObj,constraints,dsConstraints,1,cut5prime_j,fname)
foldCMD = "Fold {0}.seq {0}.ct -sh {0}.shape -sm {1} -si {2} -md {3} -C {0}.const -m 100 -w 0".format(fname, shapeSlope,shapeIntercept, maxDist)
jobQueue1.append(shlex.split(foldCMD))
cut3prime_i = rnaLength-windowSize + i
fname = "{0}/{1}_{2}_{3}".format(dirname,prefix,cut3prime_i,rnaLength)
genFiles(mapObj,constraints,dsConstraints,cut3prime_i,rnaLength,fname)
foldCMD = "Fold {0}.seq {0}.ct -sh {0}.shape -sm {1} -si {2} -md {3} -C {0}.const -m 100 -w 0".format(fname, shapeSlope,shapeIntercept, maxDist)
jobQueue1.append(shlex.split(foldCMD))
# run the generated jobs
batch.batchSubmit(jobQueue1,nprocs)
# run the master modeler
# generate a dummy RNA to align to
targetRNA = CT()
targetRNA.pair2CT([],"".join(mapObj.seq))
targetFolderRNAs, baseCount = MasterModel_readAndRenumberAll(targetRNA,dirname, prefix)
pairs = MasterModel_findOverlapPairs(targetFolderRNAs, baseCount)
masterModelStructure = CT()
masterModelStructure.pair2CT(pairs,targetRNA.seq,'ConsensusModel')
# return the ct structure
return masterModelStructure
def generateAndRunPartition(mapObj, constraints, windowSize, stepSize, prefix, shapeSlope, shapeIntercept, nprocs, maxDist):
#make list of commands, skip those files that have already been calculated
#run partition function
#make list of probability plot commands and run
#run assembleDP program
#return dotplot file from assemble
rnaLength = len(mapObj.seq)
#print rnaLength
# make the directory if it doesn't exist
dirname = "partition_" + prefix
try:
os.mkdir(dirname)
except:
pass
# generate the files for the run and the jobs to submit
jobQueue1 = []
jobQueue2 = []
# store the names of the files to delete pfs after it has been processed to txt
pfsNames = []
# if the length of the RNA is near the window size, just fold the whole thing at once
if rnaLength-windowSize < 200:
cut_i = 1
cut_j = rnaLength
fname = "{0}/{1}_{2}_{3}".format(dirname,prefix,cut_i,cut_j)
genFiles(mapObj,constraints,{0:[],1:[]},cut_i,cut_j,fname)
foldCMD = "partition {0}.seq {0}.pfs -sh {0}.shape -sm {1} -si {2} -md {3} -C {0}.const".format(fname, shapeSlope,shapeIntercept, maxDist)
parseFold = "ProbabilityPlot {0}.pfs {0}.dp -t".format(fname)
jobQueue1.append(shlex.split(foldCMD))
jobQueue2.append(shlex.split(parseFold))
pfsNames.append(fname)
# else statement from ln 331, fold the RNA in windows using the options
else:
# middle folds
for i in range(1,rnaLength-windowSize,stepSize):
cut_i = i
cut_j = i+windowSize-1
fname = "{0}/{1}_{2}_{3}".format(dirname,prefix,cut_i,cut_j)
genFiles(mapObj,constraints,{0:[],1:[]},cut_i,cut_j,fname)
foldCMD = "partition {0}.seq {0}.pfs -sh {0}.shape -sm {1} -si {2} -md {3} -C {0}.const".format(fname, shapeSlope,shapeIntercept, maxDist)
parseFold = "ProbabilityPlot {0}.pfs {0}.dp -t".format(fname)
jobQueue1.append(shlex.split(foldCMD))
jobQueue2.append(shlex.split(parseFold))
pfsNames.append(fname)
# 5prime folds
# 3prime folds
for i in [-100,-50,50,100]:
# 5' end
cut5prime_j = windowSize+i
fname = "{0}/{1}_{2}_{3}".format(dirname,prefix,1,cut5prime_j)
genFiles(mapObj,constraints,{0:[],1:[]},1,cut5prime_j,fname)
foldCMD = "partition {0}.seq {0}.pfs -sh {0}.shape -sm {1} -si {2} -md {3} -C {0}.const".format(fname, shapeSlope,shapeIntercept, maxDist)
parseFold = "ProbabilityPlot {0}.pfs {0}.dp -t".format(fname)
jobQueue1.append(shlex.split(foldCMD))
jobQueue2.append(shlex.split(parseFold))
pfsNames.append(fname)
# 3' end
cut3prime_i = rnaLength-windowSize + i
fname = "{0}/{1}_{2}_{3}".format(dirname,prefix,cut3prime_i,rnaLength)
genFiles(mapObj,constraints,{0:[],1:[]},cut3prime_i,rnaLength,fname)
foldCMD = "partition {0}.seq {0}.pfs -sh {0}.shape -sm {1} -si {2} -md {3} -C {0}.const".format(fname, shapeSlope,shapeIntercept, maxDist)
parseFold = "ProbabilityPlot {0}.pfs {0}.dp -t".format(fname)
jobQueue1.append(shlex.split(foldCMD))
jobQueue2.append(shlex.split(parseFold))
pfsNames.append(fname)
# run the generated jobs
batch.batchSubmit(jobQueue1,nprocs)
batch.batchSubmit(jobQueue2,nprocs)
# clean up the fnames
for fname in pfsNames:
try:
os.remove(fname+".pfs")
except:
pass
# run the assemble DP routine
dpObject = mainAssemble(dirname,trim=300)
return dpObject
def runCheck():
"""
check to see if necessary commands are available to call
"""
neededCmds = ["Fold", "partition", "ProbabilityPlot"]
count = 0
for each in neededCmds:
try:
out, err = "", ""
subprocess.call([each], stdout=subprocess.PIPE, stderr=subprocess.PIPE)
count += 1
except OSError:
print "Program {0} not found in the path".format(each)
if len(neededCmds) != count:
print "...exiting"
sys.exit()
try:
# get the data path and test to see if it is real
datapath = os.environ.get("DATAPATH")
os.listdir(datapath)
except:
print "DATAPATH is not set. RNAstructure will not run"
print "...exiting"
sys.exit()
def parseArgs():
def parseTXT(fIN):
data = {}
lineNum = 0
for line in open(fIN, "rU").readlines():
x = line.rstrip().split()
try:
x = map(int,x)
except:
print "Unexpected character in {0}...exiting".format(fIN)
return 0
# initialize an array obj for the first line
if lineNum == 0:
for i in range(len(x)):
data[i] = [x[i]]
# populate the array obj
else:
for i in range(len(x)):
data[i].append(x[i])
lineNum += 1
return data
def shapeEnergy(x,slope,intercept):
out = []
for i in x:
if i<-500:
out.append(-999)
continue
if -500<i<0:i=0.0
g = slope*np.log(i+1)+intercept
out.append(g)
return np.array(out)
def differentialEnergy(x,a,b,zfactor):
zfactor = np.array(zfactor)
# set -inf and nan to non significant zfactors
zfactor[np.isinf(zfactor)] = -999
zfactor[np.isnan(zfactor)] = -999
out = []
for i in x:
if i<-500:
out.append(-999)
continue
#slow fit; linear so easy
if i >= 0:
g = a*i+b
#slow case
if i < 0:
g = -999#c*i+d
#c = abs(i)
#if c > 0.2:
# g = -0.620*np.log(func(c,f1[0],f1[1],f1[2])/func(c,f2[0],f2[1],f2[2]))
#else:
# g = 2.57275425027 * c + 0.0239
out.append(g)
return np.array(out)*(zfactor>0)
def fakeSHAPE(shape,diff,slope,intercept):
#shape_f,diff_fmap=(float(shape)),map(float(diff))
#print shape
out = []
for i,j in zip(shape,diff):
if i < -500 and j<-500:
out.append(-999)
continue
if i < -500:
g = j
if j < -500:
g = i
if i >-500 and j>-500:
g = i + j
#out.append(g)
out.append(np.exp( (g-intercept) / slope ) -1.0)
return out
arg = argparse.ArgumentParser(description="SuperFold takes a windowing approach to break up the folding of large RNAs. Dividing the folding of a large RNA into smaller segments allows modern multi-core workstations to model RNA structures in a modest amount of clock-time. See README file for further details and file descriptions", epilog="SuperFold v1.0 by Gregg Rice ( gmr@unc.edu )")
arg.add_argument('mapFile', type=str, help='SHAPE-MaP .map file, trimmed to fold desired sequence')
arg.add_argument('--ssRegion', type=str, help='file containing forced single stranded regions')
arg.add_argument('--pkRegion', type=str, help='text file containing pseudoknotted basepairs:\npaired nucleotides on each line seperated by whitespace. e.g.\n\n1 50(newline)2 49(newline)...')
arg.add_argument('--np', type=int, default=2, help='number of processors to use, default:2')
arg.add_argument('--SHAPEslope',type=float,default=1.8, help='SHAPE pseudofreeenergy slope, default:1.8')
arg.add_argument('--SHAPEintercept',type=float,default=-0.6,help='SHAPE pseudofreeenergy intercept, default:-0.6')
arg.add_argument('--differentialFile',type=str, help='.mapd file containing NMIA-1M6 calculated values')
arg.add_argument('--differentialSlope',type=float,default=2.1,help='differential SHAPE slope, default:2.1')
arg.add_argument('--trimInterior',type=int,default=300, help='number of nucleotides to trim to improve negative end effects during windowed folding, default:300')
arg.add_argument('--partitionWindowSize',type=int,default=1200, help='length of the partition window size, default:1200')
arg.add_argument('--partitionStepSize',type=int,default=100, help='spacing between partition windows, default:100')
arg.add_argument('--foldWindowSize',type=int,default=3000, help='length of the Fold window size, default:3000')
arg.add_argument('--foldStepSize',type=int,default=300, help='spacing between Fold windows, default:300')
arg.add_argument('--maxPairingDist', type=int, default=600, help='Maximum pairing distance for partition and Fold, default:600')
arg.add_argument('--noPVclient', action='store_false', help="Don't draw secondary structures using PVclient")
o = arg.parse_args()
o.name = o.mapFile
# read the shapemap file in
mapfile = shapeMAP(o.mapFile)
o.mapObj = mapfile
o.mapObj.origSHAPE = np.array(o.mapObj.shape)
if o.differentialFile:
o.diffMapFile = shapeMAP(o.differentialFile)
calcSHAPEenergy = shapeEnergy(mapfile.shape,o.SHAPEslope,o.SHAPEintercept)
calcDiffEnergy = differentialEnergy(o.diffMapFile.shape,o.differentialSlope,0,o.diffMapFile.zfactor)
calcFakeShape = fakeSHAPE(calcSHAPEenergy,calcDiffEnergy,o.SHAPEslope,o.SHAPEintercept)
o.mapObj.shape = calcFakeShape
#print o.diffMapFile.zfactor
# read the constraint files
# first the ss constraints
try:
ss = parseTXT(o.ssRegion)
# catch the exception
if ss == 0:
sys.exit()
except:
if o.ssRegion == None:
ss = {0:[]}
else:
sys.exit()
o.ssConstraints = ss
# then the ds constraints
try:
ds = parseTXT(o.pkRegion)
# catch the exception
if ds == 0:
sys.exit()
# check to make sure that the pks have partners
if len(ds[0]) != len(ds[1]):
print "pkRegion file incorrectly formatted...exiting"
sys.exit()
except:
# if file not given, fill empty bps
if o.pkRegion == None:
ds = {0:[],1:[]}
else:
sys.exit()
o.dsConstraints = ds
# concatonate all the constraints
allConst = ss[0] + ds[0] + ds[1]
o.allConstraints = allConst
# generate a safe short name for the constraint, shape, and sequence files
# by hashing the names of the input values, changing any input will make a new hash
m = hashlib.md5()
m.update(str(o.mapFile))
m.update(str(o.ssRegion))
m.update(str(o.pkRegion))
m.update(str(o.differentialFile))
m.update(str(o.foldWindowSize))
m.update(str(o.partitionWindowSize))
m.update(str(o.maxPairingDist))
m.update(str(o.partitionStepSize))
o.safeName = o.mapFile[:] +"_"+ m.hexdigest()[:4]
return o
def genFiles(mapObj, ssConstraints, dsConstraints, ntStart, ntEnd, fName):
def shapeFile(SHAPEdata, fOUT):
"""
writes a .SHAPE file compatable with RNAstructure
"""
w = open(fOUT, "w")
for i in range(len(SHAPEdata)):
w.write("{0}\t{1}\n".format(i+1,SHAPEdata[i]))
w.close()
return fOUT
def seqFile(sequence, fOUT, name=None):
"""
write a seq file compatable with RNAstructure format
"""
if not name:
name = str(fOUT)
w = open(fOUT, "w")
w.write(";\n\n{0}\n\n".format(name))
for i in range(len(sequence)):
w.write(sequence[i])
if (i+1) % 50 == 0:
w.write("\n")
elif (i+1) % 10 == 0: w.write(" ")
w.write("1\n")
w.close()
return fOUT
def constraintFile(ssConstraint, dsConstraint, fOUT):
"""
writes a constraint file compatable with RNAstructure
"""
w = open(fOUT, "w")
w.write("DS:\n-1\nSS:\n")
for const in ssConstraint: w.write("{0}\n".format(const))
w.write("-1\nMod:\n-1\nPairs:\n")
for i in range(len(dsConstraint[0])):
line = "{0} {1}\n".format( dsConstraint[0][i], dsConstraint[1][i])
w.write(line)
w.write("-1 -1\nFMN:\n-1\nForbids:\n-1 -1\nMicroarray Constraints:\n0\n")
w.close()
return fOUT
### renumber constraints
renumSS = []
renumDS = {0:[],1:[]}
for i in ssConstraints:
if i >= ntStart and i <=ntEnd:
renumSS.append(i-(ntStart-1))
for i,j in zip(dsConstraints[0],dsConstraints[1]):
if i >= ntStart and j >= ntStart:
if i <= ntEnd and j<=ntEnd:
renumDS[0].append(i-(ntStart-1))
renumDS[1].append(j-(ntStart-1))
# if only one of the pairs is within the desired window hold it out
elif j >= ntStart and j <= ntEnd:
renumSS.append(j-(ntStart-1))
elif i >= ntStart and i <= ntEnd:
renumSS.append(i-(ntStart-1))
renumSS.sort()
# SHAPE file
shapeFile(mapObj.shape[ntStart-1:ntEnd],fName+".shape")
# sequence file
seqFile(mapObj.seq[ntStart-1:ntEnd], fName+".seq",name=fName)
# constraint file
constraintFile(renumSS,renumDS,fName+".const")
def mainAssemble(folderPath, trim=300):
"""
input is the path of a folder of dp files. will return an assembled
dotPlot object with all of the windows. Trim defines how much of each
window to cut out of each of the dp files.
Must have the nt start and ending numbers as the last two parts of the
file name seperated by underscores
"""
targetDP = {}
# load all the dp files into memory
numFiles = len(filter( lambda x:x[-2:]=="dp",os.listdir(folderPath) ) )
num = 1
print "reading files..."
for dpFileName in os.listdir(folderPath):
#ignore all files that are not dp files
if dpFileName[-2:] != "dp": continue
#print "reading {0}...".format(dpFileName)
dp = dotPlot(folderPath + "/" + dpFileName)
start = int(dpFileName.split("_")[-2])
end = dpFileName[:-3].split("_")[-1]
progress(num, numFiles)
num +=1
targetDP[(int(start), int(end))] = dp
# find the first and last dotplot files in sequence
# we only want to trim one side of those
firstDP = min([i[0] for i in targetDP.keys()])
lastDP = max([i[1] for i in targetDP.keys()])
#container for the final dp structure
finalDP = dotPlot()
finalDP.name = "assembled dotPlot"
finalDP.length = lastDP
coverage = []
num = 1
print "trim and resorting..."
# average slipped pairs, renumber, and trim the ends
# the dpKey is the starting number of window
if len(targetDP.keys()) == 1:
return targetDP[targetDP.keys()[0]]
for dpKey in targetDP.keys():
#print "resorting window at {0}...".format(dpKey)
progress(num,numFiles)
num+=1
# remove some of the very lowly probable base pairs to simplify later calculations
# targetDP[dpKey] = targetDP[dpKey].requireProb(4)
# preaverage the slipped base pairs
#targetDP[dpKey].averageSlippedBPs(predictedOnly=False)
# trim 3' end of the first structure in sequence
if dpKey[0] == firstDP:
#print dpKey, "3prime"
targetDP[dpKey] = targetDP[dpKey].trimEnds(trim, which='3prime')
coverage.append((dpKey[0],dpKey[1]-(trim-1)))
# trim 5' end of the first structure in sequence
elif dpKey[1] == lastDP:
#print dpKey, "5prime"
targetDP[dpKey] = targetDP[dpKey].trimEnds(trim, which='5prime')
coverage.append((dpKey[0]+(trim-1),dpKey[1]))
# trim middle dplots at both ends
else:
#print dpKey, "both", trim
targetDP[dpKey] = targetDP[dpKey].trimEnds(trim)
coverage.append((dpKey[0]+(trim-1),dpKey[1]-(trim-1)))
# reset the numbers to the correct global numbers
targetDP[dpKey].dp['i'] += dpKey[0] - 1
targetDP[dpKey].dp['j'] += dpKey[0] - 1
# append to the final dp file
finalDP.dp['i'] = np.append(finalDP.dp['i'], targetDP[dpKey].dp['i'])
finalDP.dp['j'] = np.append(finalDP.dp['j'], targetDP[dpKey].dp['j'])
finalDP.dp['logBP'] = np.append(finalDP.dp['logBP'], targetDP[dpKey].dp['logBP'])
# save a checkpoint file
#pickle.dump(finalDP, open("finaldp1.bin", "wb"))
finalDP = concatonateDP(finalDP, coverage)
return finalDP
def concatonateDP(dpObj, coverage):
"""
merges duplicate entries in a dp file by averaging
"""
def calcCoverage(i, j, coverage):
n = 0
if j-i >= 600: return 500
for a,b in coverage:
if a <= i <= b and a<= j <= b:
n+=1
return n
#print dpObj
#print coverage
dpObj = dpObj.requireProb(2)
# make a shortcut
dp = dpObj.dp
# maxDist is the max search space
maxDist = 600
# construct the return object
outObj = dotPlot()
outObj.length = dpObj.length
outObj.name = dpObj.name
# grab the potential pairs to limit looping space
pairs = set(dpObj.pairList())
fullSize = len(pairs)
outObj.dp['i'] = np.zeros(fullSize)
outObj.dp['j'] = np.zeros(fullSize)
outObj.dp['logBP'] = np.zeros(fullSize)
outObj.dp['coverage'] = np.zeros(fullSize)
n = 0
oldFilter = np.zeros_like(dp['logBP'])
dp['logBP'] = 10**( -dp['logBP'])
print "merging dotplots..."
for i,j in pairs:
i = int(i)
j = int(j)
# remove any long distance base pairs
#if j-i > maxDist: continue
dpFilter = ( dp['i']== i ) * ( dp['j'] == j )
oldFilter += dpFilter
# skip nonexisting pairs
entries = np.sum(dpFilter)
outObj.dp['i'][n] = i
outObj.dp['j'][n] = j
outObj.dp['logBP'][n] = 0.0
outObj.dp['coverage'][n] = calcCoverage(i, j, coverage)
if entries == 0: continue
#elif entries == 1:
#outObj.dp['i'] = np.append(outObj.dp['i'], i )
#outObj.dp['j'] = np.append(outObj.dp['j'], j )