Mercurial > repos > peterjc > tmhmm_and_signalp
annotate tools/protein_analysis/psortb.xml @ 17:e6cc27d182a8 draft
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author | peterjc |
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date | Fri, 21 Nov 2014 08:19:09 -0500 |
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1 <tool id="Psortb" name="psortb" version="0.0.5"> |
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2 <description>Determines sub-cellular localisation of bacterial/archaeal protein sequences</description> |
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3 <!-- If job splitting is enabled, break up the query file into parts --> |
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4 <!-- Using 2000 chunks meaning 4 threads doing 500 each is ideal --> |
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5 <parallelism method="basic" split_inputs="fasta_file" split_mode="to_size" split_size="2000" merge_outputs="tabular_file"></parallelism> |
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6 <version_command interpreter="python">psortb.py --version</version_command> |
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7 <command interpreter="python"> |
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8 psortb.py "\$GALAXY_SLOTS" "$type" "$long" "$cutoff" "$divergent" "$sequence" "$outfile" |
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9 ##If the environment variable isn't set, get "", and python wrapper |
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10 ##defaults to four threads. |
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11 </command> |
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12 <stdio> |
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13 <!-- Anything other than zero is an error --> |
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14 <exit_code range="1:" /> |
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15 <exit_code range=":-1" /> |
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16 </stdio> |
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17 <inputs> |
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18 <param format="fasta" name="sequence" type="data" |
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19 label="Input sequences for which to predict localisation (protein FASTA format)" /> |
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20 <param name="type" type="select" |
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21 label="Organism type (N.B. all sequences in the above file must be of the same type)" > |
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22 <option value="-p">Gram positive bacteria</option> |
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23 <option value="-n">Gram negative bacteria</option> |
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24 <option value="-a">Archaea</option> |
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25 </param> |
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26 <param name="long" type="select" label="Output type"> |
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27 <option value="terse">Short (terse, tabular with 3 columns)</option> |
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28 <!-- The normal output is text, not tabular - worth offering? |
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29 <option value="normal">Normal</option> |
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30 --> |
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31 <option value="long">Long (verbose, tabular with about 30 columns, depending on organism type)</option> |
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32 </param> |
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33 <param name="cutoff" size="10" type="float" optional="true" value="" |
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34 label="Sets a cutoff value for reported results (e.g. 7.5)" |
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35 help="Leave blank or use zero for no cutoff." /> |
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36 <param name="divergent" size="10" type="float" optional="true" value="" |
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37 label="Sets a cutoff value for the multiple localization flag (e.g. 4.5)" |
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38 help="Leave blank or use zero for no cutoff." /> |
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39 </inputs> |
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40 <outputs> |
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41 <data format="tabular" name="outfile" /> |
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42 </outputs> |
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43 <requirements> |
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44 <requirement type="binary">psort</requirement> |
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45 </requirements> |
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46 <tests> |
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47 <test> |
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48 <param name="sequence" value="empty.fasta" ftype="fasta"/> |
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49 <param name="long" value="terse"/> |
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50 <output name="outfile" file="empty_psortb_terse.tabular" ftype="tabular"/> |
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51 </test> |
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52 <test> |
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53 <param name="sequence" value="k12_ten_proteins.fasta" ftype="fasta"/> |
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54 <param name="long" value="terse"/> |
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55 <output name="outfile" file="k12_ten_proteins_psortb_p_terse.tabular" ftype="tabular"/> |
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56 </test> |
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57 </tests> |
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58 <help> |
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59 |
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60 **What it does** |
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61 |
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62 This calls the command line tool PSORTb v3.0 for prediction of prokaryotic |
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63 localization sites. The input dataset needs to be protein FASTA sequences. |
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64 The default output is a simple tabular file with three columns, one row |
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65 per query sequence: |
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66 |
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67 ====== ============================== |
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68 Column Description |
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69 ------ ------------------------------ |
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70 1 Sequence identifier |
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71 2 Localisation, e.g. Cytoplasmic |
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72 3 Score |
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73 ====== ============================== |
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74 |
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75 The long output is also tabular with one row per query sequence, but has |
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76 lots more columns (a different set for each supported organism type). In |
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77 both cases, a simple header line is included (starting with a hash, #, |
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78 so that Galaxy treats it as a comment) giving the column names. |
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79 |
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80 |
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81 **References** |
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82 |
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83 If you use this Galaxy tool in work leading to a scientific publication please |
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84 cite the following papers: |
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85 |
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86 Peter J.A. Cock, Björn A. Grüning, Konrad Paszkiewicz and Leighton Pritchard (2013). |
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87 Galaxy tools and workflows for sequence analysis with applications |
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88 in molecular plant pathology. PeerJ 1:e167 |
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89 http://dx.doi.org/10.7717/peerj.167 |
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90 |
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91 N.Y. Yu, J.R. Wagner, M.R. Laird, G. Melli, S. Rey, R. Lo, P. Dao, |
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92 S.C. Sahinalp, M. Ester, L.J. Foster, F.S.L. Brinkman (2010) |
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93 PSORTb 3.0: Improved protein subcellular localization prediction with |
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94 refined localization subcategories and predictive capabilities for all |
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95 prokaryotes, Bioinformatics 26(13):1608-1615 |
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96 http://dx.doi.org/10.1093/bioinformatics/btq249 |
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97 |
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98 See also http://www.psort.org/documentation/index.html |
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99 |
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100 This wrapper is available to install into other Galaxy Instances via the Galaxy |
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101 Tool Shed at http://toolshed.g2.bx.psu.edu/view/peterjc/tmhmm_and_signalp |
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102 <citations> |
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103 <citation type="doi">10.7717/peerj.167</citation> |
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104 <citation type="doi">10.1093/bioinformatics/btq249</citation> |
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105 </citations> |
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106 </help> |
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107 </tool> |