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Uploaded v0.0.1g, add Phyca11 example to README
author peterjc
date Mon, 19 Aug 2013 12:31:11 -0400
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1 This is package is a Galaxy workflow for comparing three RXLR prediction
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2 methods with a Venn Diagram, and creates a FASTA file of any proteins
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3 passing all three methods.
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5 See http://www.galaxyproject.org for information about the Galaxy Project.
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8 Sample Data
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9 ===========
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11 This workflow was developed and run on several Phytophthora species.
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12 For example, try the "Phyca11" protein set for Phytophthora capsici:
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14 http://genome.jgi-psf.org/Phyca11/download/Phyca11_filtered_proteins.fasta.gz
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16 You can upload this directly into Galaxy via this URL. Galaxy will handle
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17 removing the gzip compression to give you the FASTA protein file which
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18 has 19,805 protein sequences. Of these, only 79 sequences pass all three
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19 of the RXLR prediction tools.
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22 Citation
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23 ========
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25 If you use this workflow directly, or a derivative of it, in work leading
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26 to a scientific publication, please cite:
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28 Cock, P.J.A. and Pritchard, L. 2013. Galaxy as a platform for identifying
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29 candidate pathogen effectors. Chapter 1 in "Plant-Pathogen Interactions:
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30 Methods and Protocols (Second Edition)"; Methods in Molecular Biology.
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31 Humana Press, Springer. In press.
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33 Whisson, S.C., Boevink, C.V., Moleleki, L., et al. (2007)
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34 A translocation signal for delivery of oomycete effector proteins into
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35 host plant cells. Nature 450:115-118.
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36 http://dx.doi.org/10.1038/nature06203
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38 Win, J., Morgan, W., Bos, J., et al. (2007)
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39 Adaptive evolution has targeted the C-terminal domain of the RXLR effectors
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40 of plant pathogenic oomycetes. The Plant Cell 19:2349-2369.
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41 http://dx.doi.org/10.1105/tpc.107.051037
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43 Bhattacharjee, S., Luisa Hiller, N., Liolios, K., et al. (2006)
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44 The malarial host-targeting signal is conserved in the Irish potato famine
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45 pathogen. PLoS Pathogens 2(5):e50.
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46 http://dx.doi.org/10.1371/journal.ppat.0020050
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49 Availability
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50 ============
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52 This workflow is available to download and/or install from the main
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53 Galaxy Tool Shed:
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55 http://toolshed.g2.bx.psu.edu/view/peterjc/rxlr_venn_workflow
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57 Test releases (which should not normally be used) are on the Test Tool Shed:
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59 http://testtoolshed.g2.bx.psu.edu/view/peterjc/rxlr_venn_workflow
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61 Development is being done on github here:
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63 https://github.com/peterjc/picobio/tree/master/galaxy_workflows/rxlr_venn_workflow
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66 Dependencies
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67 ============
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69 These dependencies should be resolved automatically via the Galaxy Tool Shed:
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71 * http://toolshed.g2.bx.psu.edu/view/peterjc/tmhmm_and_signalp
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72 * http://toolshed.g2.bx.psu.edu/view/peterjc/seq_filter_by_id
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73 * http://toolshed.g2.bx.psu.edu/view/peterjc/venn_list
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75 However, at the time of writing those Galaxy tools have their own dependencies
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76 required for this workflow which require manual installation (SignalP v3.0,
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77 HMMER v2.0, and the R/Bioconductor package limma).
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80 Developers
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81 ==========
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82
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83 This workflow is under source code control here:
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85 https://github.com/peterjc/picobio/tree/master/galaxy_workflows/rxlr_venn_workflow
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87 To prepare the tar-ball for uploading to the Tool Shed, I use this:
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89 $ tar -cf rxlr_venn_workflow.tar.gz README.rst repository_dependencies.xml rxlr_venn_workflow.ga
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91 Check this,
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93 $ tar -tzf rxlr_venn_workflow.tar.gz
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94 README.rst
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95 repository_dependencies.xml
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96 rxlr_venn_workflow.ga