Mercurial > repos > peterjc > tmhmm_and_signalp
annotate tools/protein_analysis/tmhmm2.py @ 0:bca9bc7fdaef
Migrated tool version 0.0.1 from old tool shed archive to new tool shed repository
author | peterjc |
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date | Tue, 07 Jun 2011 18:03:34 -0400 |
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children | 3ff1dcbb9440 |
rev | line source |
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Migrated tool version 0.0.1 from old tool shed archive to new tool shed repository
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1 #!/usr/bin/env python |
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2 """Wrapper for TMHMM v2.0 for use in Galaxy. |
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3 |
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4 This script takes exactly two command line arguments - an input protein FASTA |
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5 filename and an output tabular filename. It then calls the standalone TMHMM |
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6 v2.0 program (not the webservice) requesting the short output (one line per |
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7 protein). |
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8 |
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9 First major feature is cleaning up the tabular output. The raw output from |
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10 TMHMM v2.0 looks like this (six columns tab separated): |
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11 |
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12 gi|2781234|pdb|1JLY|B len=304 ExpAA=0.01 First60=0.00 PredHel=0 Topology=o |
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13 gi|4959044|gb|AAD34209.1|AF069992_1 len=600 ExpAA=0.00 First60=0.00 PredHel=0 Topology=o |
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14 gi|671626|emb|CAA85685.1| len=473 ExpAA=0.19 First60=0.00 PredHel=0 Topology=o |
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15 gi|3298468|dbj|BAA31520.1| len=107 ExpAA=59.37 First60=31.17 PredHel=3 Topology=o23-45i52-74o89-106i |
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16 |
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17 In order to make it easier to use in Galaxy, this wrapper script simplifies |
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18 this to remove the redundant tags, and instead adds a comment line at the |
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19 top with the column names: |
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20 |
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21 #ID len ExpAA First60 PredHel Topology |
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22 gi|2781234|pdb|1JLY|B 304 0.01 60 0.00 0 o |
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23 gi|4959044|gb|AAD34209.1|AF069992_1 600 0.00 0 0.00 0 o |
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24 gi|671626|emb|CAA85685.1| 473 0.19 0.00 0 o |
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25 gi|3298468|dbj|BAA31520.1| 107 59.37 31.17 3 o23-45i52-74o89-106i |
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26 |
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27 The second major potential feature is taking advantage of multiple cores |
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28 (since TMHMM v2.0 itself is single threaded) by dividing the input FASTA file |
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29 into chunks and running multiple copies of TMHMM in parallel. I would normally |
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30 use Python's multiprocessing library in this situation but it requires at |
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31 least Python 2.6 and at the time of writing Galaxy still supports Python 2.4. |
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32 """ |
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33 import sys |
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34 import os |
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35 from seq_analysis_utils import stop_err, split_fasta, run_jobs |
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36 |
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37 FASTA_CHUNK = 500 |
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38 |
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39 if len(sys.argv) != 4: |
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40 stop_err("Require three arguments, number of threads (int), input protein FASTA file & output tabular file") |
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41 try: |
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42 num_threads = int(sys.argv[1]) |
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43 except: |
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44 num_threads = 0 |
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45 if num_threads < 1: |
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46 stop_err("Threads argument %s is not a positive integer" % sys.argv[1]) |
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47 fasta_file = sys.argv[2] |
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48 tabular_file = sys.argv[3] |
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49 |
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50 def clean_tabular(raw_handle, out_handle): |
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51 """Clean up tabular TMHMM output.""" |
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52 for line in raw_handle: |
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53 if not line: |
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54 continue |
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55 parts = line.rstrip("\r\n").split("\t") |
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56 try: |
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57 identifier, length, expAA, first60, predhel, topology = parts |
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58 except: |
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59 assert len(parts)!=6 |
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60 stop_err("Bad line: %r" % line) |
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61 assert length.startswith("len="), line |
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62 length = length[4:] |
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63 assert expAA.startswith("ExpAA="), line |
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64 expAA = expAA[6:] |
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65 assert first60.startswith("First60="), line |
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66 first60 = first60[8:] |
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67 assert predhel.startswith("PredHel="), line |
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68 predhel = predhel[8:] |
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69 assert topology.startswith("Topology="), line |
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70 topology = topology[9:] |
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71 out_handle.write("%s\t%s\t%s\t%s\t%s\t%s\n" \ |
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72 % (identifier, length, expAA, first60, predhel, topology)) |
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73 |
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74 fasta_files = split_fasta(fasta_file, tabular_file, FASTA_CHUNK) |
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75 temp_files = [f+".out" for f in fasta_files] |
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76 jobs = ["tmhmm %s > %s" % (fasta, temp) |
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77 for fasta, temp in zip(fasta_files, temp_files)] |
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78 |
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79 def clean_up(file_list): |
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80 for f in file_list: |
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81 if os.path.isfile(f): |
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82 os.remove(f) |
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83 |
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84 if len(jobs) > 1 and num_threads > 1: |
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85 #A small "info" message for Galaxy to show the user. |
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86 print "Using %i threads for %i tasks" % (min(num_threads, len(jobs)), len(jobs)) |
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87 results = run_jobs(jobs, num_threads) |
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88 for fasta, temp, cmd in zip(fasta_files, temp_files, jobs): |
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89 error_level = results[cmd] |
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90 if error_level: |
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91 try: |
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92 output = open(temp).readline() |
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93 except IOError: |
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94 output = "" |
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95 clean_up(fasta_files) |
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96 clean_up(temp_files) |
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97 stop_err("One or more tasks failed, e.g. %i from %r gave:\n%s" % (error_level, cmd, output), |
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98 error_level) |
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99 del results |
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100 del jobs |
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101 |
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102 out_handle = open(tabular_file, "w") |
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103 out_handle.write("#ID\tlen\tExpAA\tFirst60\tPredHel\tTopology\n") |
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104 for temp in temp_files: |
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105 data_handle = open(temp) |
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106 clean_tabular(data_handle, out_handle) |
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107 data_handle.close() |
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108 out_handle.close() |
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109 |
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110 clean_up(fasta_files) |
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111 clean_up(temp_files) |