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1 <tool id="DGenes" name="Gene prediction" version="1.0.0">
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2 <description/>
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3 <requirements>
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4 <container type="docker">jjkoehorst/sappdocker:GENECALLER</container>
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5 </requirements>
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6 <command interpreter="docker">java -jar /genecaller/target/genecaller-0.0.1-SNAPSHOT-jar-with-dependencies.jar
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7 '-runtype' '$runtype' -input $input -output $output -codon $codon -format TURTLE
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8 </command>
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9 <inputs>
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10 <param format="ttl" label="ttl genome file" name="input" type="data"/>
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11 <param label="codon table selection" name="codon" type="select">
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12 <option value="11">The Bacterial, Archaeal and Plant Plastid Code
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13 (transl_table=11)
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14 </option>
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15 <option value="4">The Mold, Protozoan, Coelenterate Mitochondrial
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16 and Mycoplasma/Spiroplasma Code (transl_table=4)
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17 </option>
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18 </param>
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19 <param label="single or meta genome" name="runtype" type="select">
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20 <option value="single">Single genome analysis</option>
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21 <option value="meta">Metagenome analysis</option>
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22 </param>
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23 </inputs>
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24 <outputs>
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25 <data format="ttl" label="ORF: ${input.name}" name="output"/>
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26 </outputs>
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27 <help>Prodigal gene prediction requires an RDF file from either a
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28 Genome FASTA or
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29 Genbank/EMBL format.
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30 </help>
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31 <citations>
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32 <citation type="bibtex">@article{Hyatt2010,
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33 abstract = {BACKGROUND: The
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34 quality of automated gene prediction in microbial
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35 organisms has
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36 improved steadily over the past decade, but there is
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37 still room for
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38 improvement. Increasing the number of correct
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39 identifications, both of
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40 genes and of the translation initiation
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41 sites for each gene, and
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42 reducing the overall number of false
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43 positives, are all desirable
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44 goals.
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45
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46 RESULTS: With our years of experience in manually curating
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47 genomes for the
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48 Joint Genome Institute, we developed a new gene
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49 prediction algorithm
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50 called Prodigal (PROkaryotic DYnamic programming
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51 Gene-finding
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52 ALgorithm). With Prodigal, we focused specifically on the
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53 three goals
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54 of improved gene structure prediction, improved
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55 translation
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56 initiation site recognition, and reduced false positives.
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57 We compared
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58 the results of Prodigal to existing gene-finding methods
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59 to
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60 demonstrate that it met each of these objectives.
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61
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62 CONCLUSION: We
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63 built a fast, lightweight, open source gene prediction program
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64 called
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65 Prodigal http://compbio.ornl.gov/prodigal/. Prodigal achieved
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66 good
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67 results compared to existing methods, and we believe it will be
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68 a
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69 valuable asset to automated microbial annotation pipelines.},
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70 author =
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71 {Hyatt, Doug and Chen, Gwo-Liang and Locascio, Philip F and
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72 Land,
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73 Miriam L and Larimer, Frank W and Hauser, Loren J},
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74 doi =
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75 {10.1186/1471-2105-11-119},
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76 file =
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77 {:Users/koeho006/Library/Application Support/Mendeley
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78 Desktop/Downloaded/Hyatt et al. - 2010 - Prodigal prokaryotic gene
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79 recognition and translation initiation site identification.pdf:pdf},
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80 issn = {1471-2105},
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81 journal = {BMC bioinformatics},
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82 keywords =
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83 {Algorithms,Databases, Genetic,Genome, Bacterial,Peptide Chain
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84 Initiation, Translational,Peptide Chain Initiation, Translational:
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85 genetics,Prokaryotic Cells,Software},
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86 mendeley-groups = {Dump/VAPP
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87 Paper},
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88 month = jan,
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89 number = {1},
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90 pages = {119},
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91 pmid = {20211023},
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92 title = {{Prodigal: prokaryotic gene recognition and translation
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93 initiation site identification.}},
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94 url =
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95 {http://www.biomedcentral.com/1471-2105/11/119},
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96 volume = {11},
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97 year =
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98 {2010}
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99 }
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100
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101 </citation>
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102 </citations>
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103 </tool> |
