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1 <tool id="glimmer_build-icm" name="ICM builder" version="0.1">
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2 <description>(glimmer3)</description>
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3 <requirements>
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4 <requirement type="package" version="3.02b">glimmer</requirement>
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5 </requirements>
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6 <command>
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7 build-icm
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8 --depth $depth
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9 #if $no_stops:
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10 --no_stops
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11 #end if
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12 --period $period
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13 --width $width
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14
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15 #if $stop_codon_opts.stop_codon_opts_selector == "gb":
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16 --trans_table "${stop_codon_opts.genbank_gencode}"
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17 #else:
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18 --stop_codons "${stop_codon_opts.stop_codons}"
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19 #end if
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20
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21 $outfile < $infile
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22 </command>
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23 <inputs>
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24 <param name="infile" type="data" format="fasta" label="Trainings Dataset" help="A set of known genes in FASTA format." />
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25 <param name="depth" type="integer" value="7" label="Set the depth of the ICM" help="The depth is the maximum number of positions in the context window that will be used to determine the probability of the predicted position." />
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26 <param name="period" type="integer" value="3" label="Set the period of the ICM" help="The period is the number of different submodels for different positions in the text in a cyclic pattern. E.g., if the period is 3, the first submodel will determine positions 1, 4, 7, ..." />
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27 <param name="width" type="integer" value="12" label="Set the width of the ICM" help="The width includes the predicted position." />
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28 <param name="no_stops" type="boolean" truevalue="--no_stops" falsevalue="" checked="true" label="Do not use any input strings with in-frame stop codons" />
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29
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30 <conditional name="stop_codon_opts">
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31 <param name="stop_codon_opts_selector" type="select" label="Specify start codons as">
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32 <option value="gb" selected="True">Genbank translation table entry</option>
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33 <option value="free_form">Comma-separated list</option>
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34 </param>
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35 <when value="gb">
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36 <param name="genbank_gencode" type="select" label="Use Genbank translation table to specify stop codons">
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37 <option value="1" select="True">1. Standard</option>
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38 <option value="2">2. Vertebrate Mitochondrial</option>
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39 <option value="3">3. Yeast Mitochondrial</option>
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40 <option value="4">4. Mold, Protozoan, and Coelenterate Mitochondrial Code and the Mycoplasma/Spiroplasma Code</option>
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41 <option value="5">5. Invertebrate Mitochondrial</option>
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42 <option value="6">6. Ciliate, Dasycladacean and Hexamita Nuclear Code</option>
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43 <option value="9">9. Echinoderm Mitochondrial</option>
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44 <option value="10">10. Euplotid Nuclear</option>
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45 <option value="11">11. Bacteria and Archaea</option>
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46 <option value="12">12. Alternative Yeast Nuclear</option>
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47 <option value="13">13. Ascidian Mitochondrial</option>
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48 <option value="14">14. Flatworm Mitochondrial</option>
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49 <option value="15">15. Blepharisma Macronuclear</option>
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50 <option value="16">16. Chlorophycean Mitochondrial</option>
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51 <option value="21">21. Trematode Mitochondrial</option>
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52 <option value="22">22. Scenedesmus obliquus mitochondrial</option>
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53 <option value="23">23. Thraustochytrium Mitochondrial</option>
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54 <option value="24">24. Pterobranchia mitochondrial</option>
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55 </param>
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56 </when>
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57 <when value="free_form">
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58 <param name="stop_codons" type="text" value="tag,tga,taa" label="Specify stop codons as a comma-separated list" />
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59 </when>
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60 </conditional>
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61
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62 </inputs>
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63 <outputs>
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64 <data format="binary" name="outfile" />
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65 </outputs>
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66 <tests>
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67 <test>
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68 <param name="infile" value='glimmer3/seqTest.fa'/>
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69 <output name="outfile" file='glimmer3/buildICMTestOutput.dat'/>
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70 </test>
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71 </tests>
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72
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73 <help>
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74
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75 **What it does**
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76
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77 This program constructs an interpolated context model (ICM) from an input set of sequences.
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78 This model can be used by Glimmer3 to predict genes.
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79
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80 -----
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81
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82
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83 **Example**
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84
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85 * input::
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86
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87 -Genome Sequence
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88
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89 >CELF22B7 C.aenorhabditis elegans (Bristol N2) cosmid F22B7
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90 GATCCTTGTAGATTTTGAATTTGAAGTTTTTTCTCATTCCAAAACTCTGT
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91 GATCTGAAATAAAATGTCTCAAAAAAATAGAAGAAAACATTGCTTTATAT
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92 TTATCAGTTATGGTTTTCAAAATTTTCTGACATACCGTTTTGCTTCTTTT
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93 TTTCTCATCTTCTTCAAATATCAATTGTGATAATCTGACTCCTAACAATC
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94 GAATTTCTTTTCCTTTTTCTTTTTCCAACAACTCCAGTGAGAACTTTTGA
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95 ATATCTTCAAGTGACTTCACCACATCAGAAGGTGTCAACGATCTTGTGAG
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96 AACATCGAATGAAGATAATTTTAATTTTAGAGTTACAGTTTTTCCTCCGA
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97 CAATTCCTGATTTACGAACATCTTCTTCAAGCATTCTACAGATTTCTTGA
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98 TGCTCTTCTAGGAGGATGTTGAAATCCGAAGTTGGAGAAAAAGTTCTCTC
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99 AACTGAAATGCTTTTTCTTCGTGGATCCGATTCAGATGGACGACCTGGCA
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100 GTCCGAGAGCCGTTCGAAGGAAAGATTCTTGTGAGAGAGGCGTGAAACAC
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101 AAAGGGTATAGGTTCTTCTTCAGATTCATATCACCAACAGTTTGAATATC
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102 CATTGCTTTCAGTTGAGCTTCGCATACACGACCAATTCCTCCAACCTAAA
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103 AAATTATCTAGGTAAAACTAGAAGGTTATGCTTTAATAGTCTCACCTTAC
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104 GAATCGGTAAATCCTTCAAAAACTCCATAATCGCGTTTTTATCATTTTCT
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105 .....
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106
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107 * output:
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108 interpolated context model (ICM)
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109
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110
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111 -------
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112
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113 **References**
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114
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115 A.L. Delcher, K.A. Bratke, E.C. Powers, and S.L. Salzberg. Identifying bacterial genes and endosymbiont DNA with Glimmer. Bioinformatics (Advance online version) (2007).
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116
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117
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118 </help>
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119 </tool>
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