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annotate tools/protein_analysis/tmhmm2.xml @ 0:bca9bc7fdaef

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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 18:03:34 -0400
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children 3ff1dcbb9440
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bca9bc7fdaef Migrated tool version 0.0.1 from old tool shed archive to new tool shed repository
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1 <tool id="tmhmm2" name="TMHMM 2.0" version="0.0.1">
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2 <description>Find transmembrane domains in protein sequences</description>
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3 <command interpreter="python">
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4 tmhmm2.py 8 $fasta_file $tabular_file
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5 ##I want the number of threads to be a Galaxy config option...
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6 </command>
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7 <inputs>
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8 <param name="fasta_file" type="data" format="fasta" label="FASTA file of protein sequences"/>
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9 <!--
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10 <param name="version" type="select" display="radio" label="Model version">
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11 <option value="">Version 1 (old)</option>
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12 <option value="" selected="True">Version 2 (default)</option>
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13 </param>
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14 -->
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15 </inputs>
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16 <outputs>
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17 <data name="tabular_file" format="tabular" label="TMHMM results" />
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18 </outputs>
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19 <requirements>
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20 <requirement type="binary">tmhmm</requirement>
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21 </requirements>
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22 <tests>
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23 <test>
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24 <param name="fasta_file" value="four_human_proteins.fasta" ftype="fasta"/>
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25 <output name="tabular_file" file="four_human_proteins.tmhmm2.tsv" ftype="tabular"/>
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26 </test>
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27 </tests>
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28 <help>
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29
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30 **What it does**
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31
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32 This calls the TMHMM v2.0 tool for prediction of transmembrane (TM) helices in proteins using a hidden Markov model (HMM).
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33
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34 The input is a FASTA file of protein sequences, and the output is tabular with six columns (one row per protein):
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35
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36 1. Sequence identifier
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37 2. Sequence length
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38 3. Expected number of amino acids in TM helices (ExpAA). If this number is larger than 18 it is very likely to be a transmembrane protein (OR have a signal peptide).
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39 4. Expected number of amino acids in TM helices in the first 60 amino acids of the protein (Exp60). If this number more than a few, be aware that a predicted transmembrane helix in the N-term could be a signal peptide.
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40 5. Number of transmembrane helices predicted by N-best.
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41 6. Topology predicted by N-best (encoded as a strip using o for output and i for inside)
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42
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43 Predicted TM segments in the n-terminal region sometime turn out to be signal peptides.
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44
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45 One of the most common mistakes by the program is to reverse the direction of proteins with one TM segment.
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46
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47 Do not use the program to predict whether a non-membrane protein is cytoplasmic or not.
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48
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49 **Notes**
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50
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51 The raw output from TMHMM v2.0 looks like this (six columns tab separated):
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52
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53 =================================== ======= =========== ============= ========= =============================
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54 gi|2781234|pdb|1JLY|B len=304 ExpAA=0.01 First60=0.00 PredHel=0 Topology=o
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55 gi|4959044|gb|AAD34209.1|AF069992_1 len=600 ExpAA=0.00 First60=0.00 PredHel=0 Topology=o
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56 gi|671626|emb|CAA85685.1| len=473 ExpAA=0.19 First60=0.00 PredHel=0 Topology=o
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57 gi|3298468|dbj|BAA31520.1| len=107 ExpAA=59.37 First60=31.17 PredHel=3 Topology=o23-45i52-74o89-106i
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58 =================================== ======= =========== ============= ========= =============================
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59
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60 In order to make it easier to use in Galaxy, the wrapper script simplifies this to remove the redundant tags, and instead adds a comment line at the top with the column names:
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61
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62 =================================== === ===== ======= ======= ====================
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63 #ID len ExpAA First60 PredHel Topology
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64 gi|2781234|pdb|1JLY|B 304 0.01 0.00 0 o
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65 gi|4959044|gb|AAD34209.1|AF069992_1 600 0.00 0.00 0 o
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66 gi|671626|emb|CAA85685.1| 473 0.19 0.00 0 o
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67 gi|3298468|dbj|BAA31520.1| 107 59.37 31.17 3 o23-45i52-74o89-106i
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68 =================================== === ===== ======= ======= ====================
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69
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70 **References**
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71
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72 Krogh, Larsson, von Heijne, and Sonnhammer.
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73 Predicting Transmembrane Protein Topology with a Hidden Markov Model: Application to Complete Genomes.
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74 J. Mol. Biol. 305:567-580, 2001.
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75
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76 Sonnhammer, von Heijne, and Krogh.
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77 A hidden Markov model for predicting transmembrane helices in protein sequences.
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78 In J. Glasgow et al., eds.: Proc. Sixth Int. Conf. on Intelligent Systems for Molecular Biology, pages 175-182. AAAI Press, 1998.
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79
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80 </help>
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81 </tool>