annotate tools/protein_analysis/wolf_psort.xml @ 17:e6cc27d182a8 draft

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date Fri, 21 Nov 2014 08:19:09 -0500
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1 <tool id="wolf_psort" name="WoLF PSORT" version="0.0.8">
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2 <description>Eukaryote protein subcellular localization prediction</description>
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3 <command interpreter="python">
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4 wolf_psort.py $organism "\$GALAXY_SLOTS" "$fasta_file" "$tabular_file"
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5 ##If the environment variable isn't set, get "", and python wrapper
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6 ##defaults to four threads.
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7 </command>
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8 <stdio>
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9 <!-- Anything other than zero is an error -->
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10 <exit_code range="1:" />
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11 <exit_code range=":-1" />
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12 </stdio>
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13 <inputs>
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14 <param name="fasta_file" type="data" format="fasta" label="FASTA file of protein sequences"/>
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15 <param name="organism" type="select" display="radio" label="Organism">
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16 <option value="animal">Animal</option>
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17 <option value="plant">Plant</option>
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18 <option value="fungi">Fungi</option>
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19 </param>
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20 </inputs>
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21 <outputs>
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22 <data name="tabular_file" format="tabular" label="WoLF PSORT $organism results" />
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23 </outputs>
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24 <requirements>
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25 <requirement type="binary">runWolfPsortSummary</requirement>
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26 </requirements>
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27 <tests>
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28 <test>
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29 <param name="fasta_file" value="four_human_proteins.fasta" ftype="fasta"/>
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30 <param name="organism" value="animal"/>
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31 <output name="tabular_file" file="four_human_proteins.wolf_psort.tabular" ftype="tabular"/>
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32 </test>
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33 <test>
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34 <param name="fasta_file" value="empty.fasta" ftype="fasta"/>
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35 <param name="organism" value="animal"/>
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36 <output name="tabular_file" file="empty_wolf_psort.tabular" ftype="tabular"/>
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37 </test>
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38 <test>
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39 <param name="fasta_file" value="empty.fasta" ftype="fasta"/>
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40 <param name="organism" value="plant"/>
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41 <output name="tabular_file" file="empty_wolf_psort.tabular" ftype="tabular"/>
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42 </test>
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43 <test>
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44 <param name="fasta_file" value="empty.fasta" ftype="fasta"/>
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45 <param name="organism" value="fungi"/>
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46 <output name="tabular_file" file="empty_wolf_psort.tabular" ftype="tabular"/>
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47 </test>
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48 </tests>
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49 <help>
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50
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51 **What it does**
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52
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53 This calls the WoLF PSORT tool for prediction of eukaryote protein subcellular localization.
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54
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55 The input is a FASTA file of protein sequences, and the output is tabular with four columns (multiple rows per protein):
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56
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57 ====== ===================
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58 Column Description
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59 ------ -------------------
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60 1 Sequence identifier
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61 2 Compartment
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62 3 Score
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63 4 Prediction rank
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64 ====== ===================
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65
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66
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67 **Localization Compartments**
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68
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69 The table below gives the WoLF PSORT localization site definitions, and the corresponding Gene Ontology (GO) term.
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70
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71 ====== ===================== =====================
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72 Abbrev Localization Site GO Cellular Component
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73 ------ --------------------- ---------------------
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74 chlo chloroplast 0009507, 0009543
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75 cyto cytosol 0005829
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76 cysk cytoskeleton 0005856(2)
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77 E.R. endoplasmic reticulum 0005783
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78 extr extracellular 0005576, 0005618
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79 golg Golgi apparatus 0005794(1)
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80 lyso lysosome 0005764
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81 mito mitochondria 0005739
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82 nucl nuclear 0005634
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83 pero peroxisome 0005777(2)
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84 plas plasma membrane 0005886
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85 vacu vacuolar membrane 0005774(2)
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86 ====== ===================== =====================
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87
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88 Numbers in parentheses, such as "0005856(2)" indicate that descendant "part_of"
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89 cellular components were also included, up to the specified depth (2 in this case).
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90 For example, all of the children and grandchildren of "GO:0005856" were
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91 included as "cysk".
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92
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93 Additionally compound predictions like mito_nucl are also given.
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94
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95
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96 **Notes**
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97
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98 The raw output from WoLF PSORT looks like this (space separated), showing two proteins:
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99
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100 ================================ ============================================
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101 gi|301087619|ref|XP_002894699.1| extr 12, mito 4, E.R. 3, golg 3, mito_nucl 3
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102 gi|301087623|ref|XP_002894700.1| extr 21, mito 2, cyto 2, cyto_mito 2
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103 ================================ ============================================
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104
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105 This is reformatted into a tabular file as follows for use in Galaxy:
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106
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107 ================================ =========== ===== ====
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108 #ID Compartment Score Rank
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109 -------------------------------- ----------- ----- ----
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110 gi|301087619|ref|XP_002894699.1| extr 12 1
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111 gi|301087619|ref|XP_002894699.1| mito 4 2
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112 gi|301087619|ref|XP_002894699.1| E.R. 3 3
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113 gi|301087619|ref|XP_002894699.1| golg 3 4
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114 gi|301087619|ref|XP_002894699.1| mito_nucl 3 5
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115 gi|301087623|ref|XP_002894700.1| extr 21 1
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116 gi|301087623|ref|XP_002894700.1| mito 2 2
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117 gi|301087623|ref|XP_002894700.1| cyto 2 3
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118 gi|301087623|ref|XP_002894700.1| cyto_mito 2 4
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119 ================================ =========== ===== ====
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120
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121 This way you can easily filter for things like having a top prediction for
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122 mitochondria (c2=='mito' and c4==1), or extracellular with a score of at
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123 least 10 (c2=='extr' and 10&lt;=c3), and so on.
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124
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125
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126 **References**
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127
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128 If you use this Galaxy tool in work leading to a scientific publication please
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129 cite the following papers:
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130
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131 Peter J.A. Cock, Björn A. Grüning, Konrad Paszkiewicz and Leighton Pritchard (2013).
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132 Galaxy tools and workflows for sequence analysis with applications
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133 in molecular plant pathology. PeerJ 1:e167
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134 http://dx.doi.org/10.7717/peerj.167
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135
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136 Paul Horton, Keun-Joon Park, Takeshi Obayashi, Naoya Fujita, Hajime Harada, C.J. Adams-Collier, and Kenta Nakai (2007).
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137 WoLF PSORT: Protein Localization Predictor.
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138 Nucleic Acids Research, 35(S2), W585-W587.
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139 http://dx.doi.org/10.1093/nar/gkm259
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140
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141 Paul Horton, Keun-Joon Park, Takeshi Obayashi and Kenta Nakai (2006).
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142 Protein Subcellular Localization Prediction with WoLF PSORT.
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143 Proceedings of the 4th Annual Asia Pacific Bioinformatics Conference APBC06, Taipei, Taiwan. pp. 39-48.
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144
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145 See also http://wolfpsort.org
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146
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147 This wrapper is available to install into other Galaxy Instances via the Galaxy
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148 Tool Shed at http://toolshed.g2.bx.psu.edu/view/peterjc/tmhmm_and_signalp
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149 </help>
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150 <citations>
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151 <citation type="doi">10.7717/peerj.167</citation>
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152 <citation type="doi">10.1093/nar/gkm259</citation>
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153 </citations>
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154 </tool>