Mercurial > repos > peterjc > tmhmm_and_signalp

annotate tools/protein_analysis/wolf_psort.py @ 34:7a2e20baacee draft default tip

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"v0.2.13 - Python 3 fix for raising StopIteration"
author peterjc
date Thu, 17 Jun 2021 17:58:23 +0000
parents 20da7f48b56f
children
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1 #!/usr/bin/env python
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2 """Wrapper for WoLF PSORT v0.2 for use in Galaxy.
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3
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4 This script takes exactly four command line arguments:
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5 * the organism type (animal, plant or fungi)
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6 * number of threads to use (integer)
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7 * an input protein FASTA filename
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8 * output tabular filename.
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9
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10 It then calls the standalone WoLF PSORT v0.2 program runWolfPsortSummary
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11 (not the webservice), and coverts the output from something like this:
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13 # k used for kNN is: 27
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14 gi|301087619|ref|XP_002894699.1| extr 12, mito 4, E.R. 3, golg 3, mito_nucl 3
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15 gi|301087623|ref|XP_002894700.1| extr 21, mito 2, cyto 2, cyto_mito 2
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17 In order to make it easier to use in Galaxy, this wrapper script reformats
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18 this to use tab separators, with one line per compartment prediction:
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20 #ID Compartment Score Rank
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21 gi|301087619|ref|XP_002894699.1| extr 12 1
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22 gi|301087619|ref|XP_002894699.1| mito 4 2
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23 gi|301087619|ref|XP_002894699.1| E.R. 3 3
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24 gi|301087619|ref|XP_002894699.1| golg 3 4
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25 gi|301087619|ref|XP_002894699.1| mito_nucl 3 5
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26 gi|301087623|ref|XP_002894700.1| extr 21 1
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27 gi|301087623|ref|XP_002894700.1| mito 2 2
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28 gi|301087623|ref|XP_002894700.1| cyto 2 3
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29 gi|301087623|ref|XP_002894700.1| cyto_mito 2 4
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31 Additionally in order to take full advantage of multiple cores, by subdividing
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32 the input FASTA file multiple copies of WoLF PSORT are run in parallel. I would
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33 normally use Python's multiprocessing library in this situation but it requires
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34 at least Python 2.6 and at the time of writing Galaxy still supports Python 2.4.
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35 """
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37 from __future__ import print_function
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38
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39 import os
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40 import sys
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42 from seq_analysis_utils import run_jobs, split_fasta, thread_count
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44 FASTA_CHUNK = 500
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45 exe = "runWolfPsortSummary"
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47 """
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48 Note: I had trouble getting runWolfPsortSummary on the path (via a link), other
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49 than by including all of /opt/WoLFPSORT_package_v0.2/bin , so used a wrapper
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50 python script called runWolfPsortSummary as follows:
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51
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52 #!/usr/bin/env python
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53 #Wrapper script to call WoLF PSORT from its own directory.
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54 import os
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55 import sys
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56 import subprocess
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57 saved_dir = os.path.abspath(os.curdir)
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58 os.chdir("/opt/WoLFPSORT_package_v0.2/bin")
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59 args = ["./runWolfPsortSummary"] + sys.argv[1:]
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60 return_code = subprocess.call(args)
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61 os.chdir(saved_dir)
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62 sys.exit(return_code)
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63
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64 For more details on this workaround, see:
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65 https://lists.galaxyproject.org/pipermail/galaxy-dev/2015-December/023386.html
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66 """
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67
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68 if "-v" in sys.argv or "--version" in sys.argv:
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69 sys.exit("WoLF-PSORT wrapper version 0.0.12")
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70
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71 if len(sys.argv) != 5:
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72 sys.exit(
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73 "Require four arguments, organism, threads, input protein FASTA file, "
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74 "and output tabular file"
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75 )
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76
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77 organism = sys.argv[1]
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78 if organism not in ["animal", "plant", "fungi"]:
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79 sys.exit("Organism argument %s is not one of animal, plant, fungi" % organism)
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80
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81 num_threads = thread_count(sys.argv[2], default=4)
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82 fasta_file = sys.argv[3]
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83 tabular_file = sys.argv[4]
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84
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85
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86 def clean_tabular(raw_handle, out_handle):
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87 """Clean up WoLF PSORT output to make it tabular."""
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88 for line in raw_handle:
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89 if not line or line.startswith("#"):
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90 continue
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91 name, data = line.rstrip("\r\n").split(None, 1)
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92 for rank, comp_data in enumerate(data.split(",")):
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93 comp, score = comp_data.split()
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94 out_handle.write("%s\t%s\t%s\t%i\n" % (name, comp, score, rank + 1))
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95
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96
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97 fasta_files = split_fasta(fasta_file, tabular_file, n=FASTA_CHUNK)
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98 temp_files = [f + ".out" for f in fasta_files]
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99 assert len(fasta_files) == len(temp_files)
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100 jobs = [
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101 "%s %s < %s > %s" % (exe, organism, fasta, temp)
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102 for (fasta, temp) in zip(fasta_files, temp_files)
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103 ]
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104 assert len(fasta_files) == len(temp_files) == len(jobs)
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105
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106
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107 def clean_up(file_list):
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108 for f in file_list:
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109 if os.path.isfile(f):
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110 os.remove(f)
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111
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112
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113 if len(jobs) > 1 and num_threads > 1:
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114 # A small "info" message for Galaxy to show the user.
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115 print("Using %i threads for %i tasks" % (min(num_threads, len(jobs)), len(jobs)))
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116 results = run_jobs(jobs, num_threads)
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117 assert len(fasta_files) == len(temp_files) == len(jobs)
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118 for fasta, temp, cmd in zip(fasta_files, temp_files, jobs):
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119 error_level = results[cmd]
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120 try:
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121 output = open(temp).readline()
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122 except IOError:
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123 output = ""
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124 if error_level or output.lower().startswith("error running"):
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125 clean_up(fasta_files)
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126 clean_up(temp_files)
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127 sys.exit(
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128 "One or more tasks failed, e.g. %i from %r gave:\n%s"
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129 % (error_level, cmd, output),
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130 error_level,
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131 )
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132 del results
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133
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134 out_handle = open(tabular_file, "w")
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135 out_handle.write("#ID\tCompartment\tScore\tRank\n")
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136 for temp in temp_files:
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137 data_handle = open(temp)
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138 clean_tabular(data_handle, out_handle)
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139 data_handle.close()
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peterjc
parents:
diff changeset
140 out_handle.close()
ef7ceca37e3f Migrated tool version 0.0.8 from old tool shed archive to new tool shed repository
peterjc
parents:
diff changeset
141
ef7ceca37e3f Migrated tool version 0.0.8 from old tool shed archive to new tool shed repository
peterjc
parents:
diff changeset
142 clean_up(fasta_files)
ef7ceca37e3f Migrated tool version 0.0.8 from old tool shed archive to new tool shed repository
peterjc
parents:
diff changeset
143 clean_up(temp_files)