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1 <tool id="predictnls" name="PredictNLS" version="0.0.8">
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1
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2 <description>Find nuclear localization signals (NLSs) in protein sequences</description>
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3
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3 <requirements>
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4 <requirement type="binary">predictnls</requirement>
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5 </requirements>
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1
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6 <stdio>
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7 <!-- Assume anything other than zero is an error -->
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8 <exit_code range="1:" />
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9 <exit_code range=":-1" />
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10 </stdio>
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3
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11 <command interpreter="python">
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12 predictnls.py $fasta_file $tabular_file
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13 </command>
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14 <inputs>
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15 <param name="fasta_file" type="data" format="fasta" label="FASTA file of protein sequences"/>
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16 </inputs>
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17 <outputs>
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18 <data name="tabular_file" format="tabular" label="predictNLS results" />
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19 </outputs>
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20 <tests>
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21 <test>
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22 <param name="fasta_file" value="four_human_proteins.fasta"/>
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23 <output name="tabular_file" file="four_human_proteins.predictnls.tabular"/>
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24 </test>
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25 </tests>
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26 <help>
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27
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28 **What it does**
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29
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30 This calls a Python re-implementation of the PredictNLS tool for prediction of
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31 nuclear localization signals (NLSs), which works by looking for matches to
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32 a known set of patterns (described using regular expressions).
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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
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35 these columns (multiple rows per protein):
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36
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37 ====== ==========================================================================
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38 Column Description
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39 ------ --------------------------------------------------------------------------
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40 1 Sequence identifier
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41 2 Start of NLS
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42 3 NLS sequence
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43 4 NLS pattern (regular expression)
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44 5 Number of reference proteins with this NLS
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45 6 Percentage of reference proteins with this NLS which are nuclear localized
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46 7 Comma separated list of reference proteins
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47 8 Comma separated list of reference proteins' localizations
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48 ====== ==========================================================================
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49
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50 If a sequence has no predicted NLS, then there is no line in the output file
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51 for it. This is a simplification of the text rich output from the command line
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52 tool, to give a tabular file suitable for use within Galaxy.
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53
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54 Information about potential DNA binding (shown in the original predictnls
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55 tool) is not given.
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56
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57 **Localizations**
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58
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59 The following abbreviations are used (derived from SWISS-PROT):
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60
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61 ==== =======================
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62 Abbr Localization
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63 ---- -----------------------
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64 cyt Cytoplasm
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65 pla Chloroplast
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66 ret Eendoplasmic reticululm
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67 ext Extracellular
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68 gol Golgi
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69 lys Lysosomal
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70 mit Mitochondria
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71 nuc Nuclear
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72 oxi Peroxisom
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73 vac Vacuolar
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74 rip Periplasmic
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75 ==== =======================
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76
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77 **References**
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78
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79 If you use this Galaxy tool in work leading to a scientific publication please
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80 cite the following papers:
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81
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82 Peter J.A. Cock, Björn A. Grüning, Konrad Paszkiewicz and Leighton Pritchard (2013).
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83 Galaxy tools and workflows for sequence analysis with applications
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84 in molecular plant pathology. PeerJ 1:e167
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85 http://dx.doi.org/10.7717/peerj.167
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86
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87 Murat Cokol, Rajesh Nair, and Burkhard Rost (2000).
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88 Finding nuclear localization signals.
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89 EMBO reports 1(5), 411–415
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90 http://dx.doi.org/10.1093/embo-reports/kvd092
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91
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92 See also http://rostlab.org
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93
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94 This wrapper is available to install into other Galaxy Instances via the Galaxy
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95 Tool Shed at http://toolshed.g2.bx.psu.edu/view/peterjc/predictnls
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96 </help>
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97 <citations>
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98 <citation type="doi">10.7717/peerj.167</citation>
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99 <citation type="doi">10.1093/embo-reports/kvd092</citation>
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100 </citations>
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101 </tool>
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