annotate find_CAPS.py @ 2:ea2117a7b363 draft

Uploaded CAPS marker design workflow for 454 Data
author john-mccallum
date Sun, 09 Sep 2012 23:16:56 -0400
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children
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1 #!/usr/bin/python2.6
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2 ##find snps that condition CAPS
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3 ##usage find_CAPS.py <reference file> <gff file>
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4
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5
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6 #Copyright 2012 John McCallum & Leshi Chen
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7 #New Zealand Institute for Plant and Food Research
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8 #This program is free software: you can redistribute it and/or modify
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9 # it under the terms of the GNU General Public License as published by
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10 # the Free Software Foundation, either version 3 of the License, or
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11 # (at your option) any later version.
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12 #
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13 # This program is distributed in the hope that it will be useful,
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14 # but WITHOUT ANY WARRANTY; without even the implied warranty of
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15 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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16 # GNU General Public License for more details.
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17 #
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18 # You should have received a copy of the GNU General Public License
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19 # along with this program. If not, see <http://www.gnu.org/licenses/>.
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21
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22
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23 import sys
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24
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25 from Bio import SeqIO
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26 from BCBio import GFF
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27 from Bio.Restriction import *
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28
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29 ###This list is limited to economical enzymes performing well in PCR buffer
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30 rest_batch = RestrictionBatch(
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31 [AluI, ApaI, BamHI, BbrPI, BfrI, ClaI, DdeI, DpnII, DraI, EcoRI,
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32 HaeIII, HindII, HinfI, HpaI, PvuII, RsaI, SacI, Sau3AI, SmaI, TaqI])
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33
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34 in_file=sys.argv[1]
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35 gff_file=sys.argv[2]
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36
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37 in_seq_handle = open(in_file)
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38 in_gff_handle=open(gff_file)
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39
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40 ##use iterator
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41 for myrec in SeqIO.parse(in_seq_handle, "fasta"):
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42 ##create single-entry dictionary to accept gff annotations from parser
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43 seq_dict = {myrec.id:myrec}
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44
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45 ##note that this filters out only SNP features
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46 limit_info = dict(gff_id = [myrec.id] ,gff_type = ['SNP'])
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47 in_gff_handle.seek(0)
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48
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49 ##parse annotations into
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50 annotations = [r for r
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51 in GFF.parse(in_gff_handle,
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52 base_dict=seq_dict,
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53 limit_info=limit_info)]
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54
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55 ##if there are any for this sequence, proceed
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56 if annotations:
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57 rec=annotations[0]
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58 for feat in rec.features:
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59 fstart=feat.location.start.position
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60 fend=feat.location.end.position
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61
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62 if 20 < fstart < len(rec) - 20:
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63 #just work with +/- 20 bp, ignoring SNPS within this
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64 #distance from ends
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65 fseq=rec.seq[fstart-20:fstart+20]
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66 ref_seq = rec.seq[fstart-20:fstart+20]
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67 variant_seq = ref_seq.tomutable()
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68
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69 #mutate the variant
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70 variant_seq[20]= feat.qualifiers['Variant_seq'][0]
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71 variant_seq = variant_seq.toseq()
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72
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73 #digest the sequences
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74 ref_cuts = rest_batch.search(ref_seq)
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75 var_cuts = rest_batch.search(variant_seq)
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76
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77 #print
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78 for enz in ref_cuts:
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79 kr = set(ref_cuts[enz])
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80 km = set(var_cuts[enz])
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81 outputstr=[rec.id, fstart +1,fend+1,feat.id,enz]
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82 if len(kr) > len(km):
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83 outputstr.append("reference")
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84 print('\t'.join(map(str,outputstr)))
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85 elif len(kr) < len(km):
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86 outputstr.append("variant")
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87 print('\t'.join(map(str,outputstr)))
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88
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89 in_gff_handle.close()
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90 in_seq_handle.close()
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