annotate tools/protein_analysis/wolf_psort.xml @ 23:e1996f0f4e85 draft default tip

"v0.2.13 - Python 3 fix for raising StopIteration"
author peterjc
date Thu, 17 Jun 2021 17:59:33 +0000
parents 238eae32483c
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e1996f0f4e85 "v0.2.13 - Python 3 fix for raising StopIteration"
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1 <tool id="wolf_psort" name="WoLF PSORT" version="0.0.12">
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2 <description>Eukaryote protein subcellular localization prediction</description>
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3 <requirements>
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4 <requirement type="package">wolfpsort</requirement>
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5 </requirements>
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6 <version_command>
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7 python $__tool_directory__/wolf_psort.py --version
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8 </version_command>
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9 <command detect_errors="aggressive">
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10 python $__tool_directory__/wolf_psort.py $organism "\$GALAXY_SLOTS" '$fasta_file' '$tabular_file'
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11 </command>
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12 <inputs>
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13 <param name="fasta_file" type="data" format="fasta" label="FASTA file of protein sequences"/>
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14 <param name="organism" type="select" display="radio" label="Organism">
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15 <option value="animal">Animal</option>
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16 <option value="plant">Plant</option>
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17 <option value="fungi">Fungi</option>
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18 </param>
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19 </inputs>
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20 <outputs>
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21 <data name="tabular_file" format="tabular" label="WoLF PSORT $organism results" />
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22 </outputs>
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23 <tests>
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24 <test>
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25 <param name="fasta_file" value="four_human_proteins.fasta" ftype="fasta"/>
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26 <param name="organism" value="animal"/>
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27 <output name="tabular_file" file="four_human_proteins.wolf_psort.tabular" ftype="tabular"/>
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28 </test>
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29 <test>
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30 <param name="fasta_file" value="empty.fasta" ftype="fasta"/>
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31 <param name="organism" value="animal"/>
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32 <output name="tabular_file" file="empty_wolf_psort.tabular" ftype="tabular"/>
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33 </test>
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34 <test>
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35 <param name="fasta_file" value="empty.fasta" ftype="fasta"/>
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36 <param name="organism" value="plant"/>
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37 <output name="tabular_file" file="empty_wolf_psort.tabular" ftype="tabular"/>
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38 </test>
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39 <test>
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40 <param name="fasta_file" value="empty.fasta" ftype="fasta"/>
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41 <param name="organism" value="fungi"/>
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42 <output name="tabular_file" file="empty_wolf_psort.tabular" ftype="tabular"/>
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43 </test>
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44 </tests>
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45 <help>
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46
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47 **What it does**
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48
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49 This calls the WoLF PSORT tool for prediction of eukaryote protein subcellular localization.
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50
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51 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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52
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53 ====== ===================
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54 Column Description
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55 ------ -------------------
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56 1 Sequence identifier
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57 2 Compartment
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58 3 Score
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59 4 Prediction rank
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60 ====== ===================
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62
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63 **Localization Compartments**
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64
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65 The table below gives the WoLF PSORT localization site definitions, and the corresponding Gene Ontology (GO) term.
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66
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67 ====== ===================== =====================
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68 Abbrev Localization Site GO Cellular Component
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69 ------ --------------------- ---------------------
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70 chlo chloroplast 0009507, 0009543
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71 cyto cytosol 0005829
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72 cysk cytoskeleton 0005856(2)
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73 E.R. endoplasmic reticulum 0005783
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74 extr extracellular 0005576, 0005618
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75 golg Golgi apparatus 0005794(1)
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76 lyso lysosome 0005764
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77 mito mitochondria 0005739
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78 nucl nuclear 0005634
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79 pero peroxisome 0005777(2)
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80 plas plasma membrane 0005886
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81 vacu vacuolar membrane 0005774(2)
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82 ====== ===================== =====================
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83
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84 Numbers in parentheses, such as "0005856(2)" indicate that descendant "part_of"
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85 cellular components were also included, up to the specified depth (2 in this case).
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86 For example, all of the children and grandchildren of "GO:0005856" were
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87 included as "cysk".
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88
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89 Additionally compound predictions like mito_nucl are also given.
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90
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91
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92 **Notes**
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93
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94 The raw output from WoLF PSORT looks like this (space separated), showing two proteins:
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95
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96 ================================ ============================================
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97 gi|301087619|ref|XP_002894699.1| extr 12, mito 4, E.R. 3, golg 3, mito_nucl 3
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98 gi|301087623|ref|XP_002894700.1| extr 21, mito 2, cyto 2, cyto_mito 2
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99 ================================ ============================================
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100
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101 This is reformatted into a tabular file as follows for use in Galaxy:
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102
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103 ================================ =========== ===== ====
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104 #ID Compartment Score Rank
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105 -------------------------------- ----------- ----- ----
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106 gi|301087619|ref|XP_002894699.1| extr 12 1
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107 gi|301087619|ref|XP_002894699.1| mito 4 2
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108 gi|301087619|ref|XP_002894699.1| E.R. 3 3
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109 gi|301087619|ref|XP_002894699.1| golg 3 4
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110 gi|301087619|ref|XP_002894699.1| mito_nucl 3 5
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111 gi|301087623|ref|XP_002894700.1| extr 21 1
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112 gi|301087623|ref|XP_002894700.1| mito 2 2
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113 gi|301087623|ref|XP_002894700.1| cyto 2 3
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114 gi|301087623|ref|XP_002894700.1| cyto_mito 2 4
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115 ================================ =========== ===== ====
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116
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117 This way you can easily filter for things like having a top prediction for
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118 mitochondria (c2=='mito' and c4==1), or extracellular with a score of at
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119 least 10 (c2=='extr' and 10&lt;=c3), and so on.
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120
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121
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122 **References**
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123
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124 If you use this Galaxy tool in work leading to a scientific publication please
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125 cite the following papers:
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126
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127 Peter J.A. Cock, Björn A. Grüning, Konrad Paszkiewicz and Leighton Pritchard (2013).
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128 Galaxy tools and workflows for sequence analysis with applications
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129 in molecular plant pathology. PeerJ 1:e167
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130 https://doi.org/10.7717/peerj.167
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131
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132 Paul Horton, Keun-Joon Park, Takeshi Obayashi, Naoya Fujita, Hajime Harada, C.J. Adams-Collier, and Kenta Nakai (2007).
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133 WoLF PSORT: Protein Localization Predictor.
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134 Nucleic Acids Research, 35(S2), W585-W587.
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135 https://doi.org/10.1093/nar/gkm259
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136
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137 Paul Horton, Keun-Joon Park, Takeshi Obayashi and Kenta Nakai (2006).
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138 Protein Subcellular Localization Prediction with WoLF PSORT.
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139 Proceedings of the 4th Annual Asia Pacific Bioinformatics Conference APBC06, Taipei, Taiwan. pp. 39-48.
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140
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141 See also http://wolfpsort.org
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142
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143 This wrapper is available to install into other Galaxy Instances via the Galaxy
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144 Tool Shed at http://toolshed.g2.bx.psu.edu/view/peterjc/tmhmm_and_signalp
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145 </help>
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146 <citations>
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147 <citation type="doi">10.7717/peerj.167</citation>
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148 <citation type="doi">10.1093/nar/gkm259</citation>
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149 </citations>
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150 </tool>