Mercurial > repos > peterjc > tmhmm_and_signalp

annotate tools/protein_analysis/signalp3.py @ 0:a2eeeaa6f75e

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Migrated tool version 0.0.1 from old tool shed archive to new tool shed repository
author peterjc
date Tue, 07 Jun 2011 17:37:26 -0400
parents
children ef7ceca37e3f
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a2eeeaa6f75e 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 SignalP v3.0 for use in Galaxy.
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3
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4 This script takes exactly fives command line arguments:
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5 * the organism type (euk, gram+ or gram-)
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6 * length to truncate sequences to (integer)
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7 * number of threads to use (integer)
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8 * an input protein FASTA filename
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9 * output tabular filename.
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10
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11 It then calls the standalone SignalP v3.0 program (not the webservice)
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12 requesting the short output (one line per protein) using both NN and HMM
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13 for predictions.
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14
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15 First major feature is cleaning up the output. The raw output from SignalP
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16 v3.0 looks like this (21 columns space separated):
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17
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18 # SignalP-NN euk predictions # SignalP-HMM euk predictions
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19 # name Cmax pos ? Ymax pos ? Smax pos ? Smean ? D ? # name ! Cmax pos ? Sprob ?
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20 gi|2781234|pdb|1JLY| 0.061 17 N 0.043 17 N 0.199 1 N 0.067 N 0.055 N gi|2781234|pdb|1JLY|B Q 0.000 17 N 0.000 N
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21 gi|4959044|gb|AAD342 0.099 191 N 0.012 38 N 0.023 12 N 0.014 N 0.013 N gi|4959044|gb|AAD34209.1|AF069992_1 Q 0.000 0 N 0.000 N
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22 gi|671626|emb|CAA856 0.139 381 N 0.020 8 N 0.121 4 N 0.067 N 0.044 N gi|671626|emb|CAA85685.1| Q 0.000 0 N 0.000 N
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23 gi|3298468|dbj|BAA31 0.208 24 N 0.184 38 N 0.980 32 Y 0.613 Y 0.398 N gi|3298468|dbj|BAA31520.1| Q 0.066 24 N 0.139 N
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24
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25 In order to make it easier to use in Galaxy, this wrapper script reformats
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26 this to use tab separators. Also it removes the redundant truncated name
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27 column, and assigns unique column names in the header:
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28
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29 #ID NN_Cmax_score NN_Cmax_pos NN_Cmax_pred NN_Ymax_score NN_Ymax_pos NN_Ymax_pred NN_Smax_score NN_Smax_pos NN_Smax_pred NN_Smean_score NN_Smean_pred NN_D_score NN_D_pred HMM_bang HMM_Cmax_score HMM_Cmax_pos HMM_Cmax_pred HMM_Sprob_score HMM_Sprob_pred
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30 gi|2781234|pdb|1JLY|B 0.061 17 N 0.043 17 N 0.199 1 N 0.067 N 0.055 N Q 0.000 17 N 0.000 N
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31 gi|4959044|gb|AAD34209.1|AF069992_1 0.099 191 N 0.012 38 N 0.023 12 N 0.014 N 0.013 N Q 0.000 0 N 0.000 N
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32 gi|671626|emb|CAA85685.1| 0.139 381 N 0.020 8 N 0.121 4 N 0.067 N 0.044 N Q 0.000 0 N 0.000 N
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33 gi|3298468|dbj|BAA31520.1| 0.208 24 N 0.184 38 N 0.980 32 Y 0.613 Y 0.398 N Q 0.066 24 N 0.139 N
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34
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35 The second major feature is overcoming SignalP's built in limit of 4000
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36 sequences by breaking up the input FASTA file into chunks. This also allows
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37 us to pre-trim the sequences since SignalP only needs their starts.
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38
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39 The third major feature is taking advantage of multiple cores (since SignalP
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40 v3.0 itself is single threaded) by using the individual FASTA input files to
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41 run multiple copies of TMHMM in parallel. I would normally use Python's
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42 multiprocessing library in this situation but it requires at least Python 2.6
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43 and at the time of writing Galaxy still supports Python 2.4.
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44 """
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45 import sys
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46 import os
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47 from seq_analysis_utils import stop_err, split_fasta, run_jobs
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48
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49 FASTA_CHUNK = 500
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50 MAX_LEN = 6000 #Found by trial and error
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51
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52 if len(sys.argv) != 6:
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53 stop_err("Require five arguments, organism, truncate, threads, input protein FASTA file & output tabular file")
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54
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55 organism = sys.argv[1]
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56 if organism not in ["euk", "gram+", "gram-"]:
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57 stop_err("Organism argument %s is not one of euk, gram+ or gram-" % organism)
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58
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59 try:
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60 truncate = int(sys.argv[2])
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61 except:
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62 truncate = 0
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63 if truncate < 0:
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64 stop_err("Truncate argument %s is not a positive integer (or zero)" % sys.argv[2])
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65
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66 try:
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67 num_threads = int(sys.argv[3])
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68 except:
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69 num_threads = 0
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70 if num_threads < 1:
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71 stop_err("Threads argument %s is not a positive integer" % sys.argv[3])
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72
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73 fasta_file = sys.argv[4]
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74
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75 tabular_file = sys.argv[5]
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76
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77 def clean_tabular(raw_handle, out_handle):
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78 """Clean up SignalP output to make it tabular."""
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79 for line in raw_handle:
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80 if not line or line.startswith("#"):
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81 continue
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82 parts = line.rstrip("\r\n").split()
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83 assert len(parts)==21, repr(line)
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84 assert parts[14].startswith(parts[0])
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85 #Remove redundant truncated name column (col 0)
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86 #and put full name at start (col 14)
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87 parts = parts[14:15] + parts[1:14] + parts[15:]
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88 out_handle.write("\t".join(parts) + "\n")
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89
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90 fasta_files = split_fasta(fasta_file, tabular_file, n=FASTA_CHUNK, truncate=truncate, max_len=MAX_LEN)
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91 temp_files = [f+".out" for f in fasta_files]
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92 assert len(fasta_files) == len(temp_files)
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93 jobs = ["signalp -short -t %s %s > %s" % (organism, fasta, temp)
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94 for (fasta, temp) in zip(fasta_files, temp_files)]
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95 assert len(fasta_files) == len(temp_files) == len(jobs)
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96
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97 def clean_up(file_list):
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98 for f in file_list:
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99 if os.path.isfile(f):
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100 os.remove(f)
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101
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102 if len(jobs) > 1 and num_threads > 1:
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103 #A small "info" message for Galaxy to show the user.
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104 print "Using %i threads for %i tasks" % (min(num_threads, len(jobs)), len(jobs))
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105 results = run_jobs(jobs, num_threads)
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106 assert len(fasta_files) == len(temp_files) == len(jobs)
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107 for fasta, temp, cmd in zip(fasta_files, temp_files, jobs):
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108 error_level = results[cmd]
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109 try:
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110 output = open(temp).readline()
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111 except IOError:
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112 output = ""
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113 if error_level or output.lower().startswith("error running"):
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114 clean_up(fasta_files)
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115 clean_up(temp_files)
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116 stop_err("One or more tasks failed, e.g. %i from %r gave:\n%s" % (error_level, cmd, output),
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117 error_level)
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118 del results
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119
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120 out_handle = open(tabular_file, "w")
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121 fields = ["ID"]
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122 #NN results:
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123 for name in ["Cmax", "Ymax", "Smax"]:
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124 fields.extend(["NN_%s_score"%name, "NN_%s_pos"%name, "NN_%s_pred"%name])
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125 fields.extend(["NN_Smean_score", "NN_Smean_pred", "NN_D_score", "NN_D_pred"])
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126 #HMM results:
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127 fields.extend(["HMM_type", "HMM_Cmax_score", "HMM_Cmax_pos", "HMM_Cmax_pred",
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128 "HMM_Sprob_score", "HMM_Sprob_pred"])
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129 out_handle.write("#" + "\t".join(fields) + "\n")
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130 for temp in temp_files:
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diff changeset
131 data_handle = open(temp)
a2eeeaa6f75e Migrated tool version 0.0.1 from old tool shed archive to new tool shed repository
peterjc
parents:
diff changeset
132 clean_tabular(data_handle, out_handle)
a2eeeaa6f75e Migrated tool version 0.0.1 from old tool shed archive to new tool shed repository
peterjc
parents:
diff changeset
133 data_handle.close()
a2eeeaa6f75e Migrated tool version 0.0.1 from old tool shed archive to new tool shed repository
peterjc
parents:
diff changeset
134 out_handle.close()
a2eeeaa6f75e Migrated tool version 0.0.1 from old tool shed archive to new tool shed repository
peterjc
parents:
diff changeset
135
a2eeeaa6f75e Migrated tool version 0.0.1 from old tool shed archive to new tool shed repository
peterjc
parents:
diff changeset
136 clean_up(fasta_files)
a2eeeaa6f75e Migrated tool version 0.0.1 from old tool shed archive to new tool shed repository
peterjc
parents:
diff changeset
137 clean_up(temp_files)