comparison glimmer3-build-icm-wrapper.xml @ 0:8624069d7a0e

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author bgruening
date Fri, 07 Jun 2013 07:33:02 -0400
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1 <tool id="glimmer_build-icm" name="ICM builder" version="0.1">
2 <description>(glimmer3)</description>
3 <requirements>
4 <requirement type="package" version="3.02b">glimmer</requirement>
5 </requirements>
6 <command>
7 build-icm
8 --depth $depth
9 #if $no_stops:
10 --no_stops
11 #end if
12 --period $period
13 --width $width
14
15 #if $stop_codon_opts.stop_codon_opts_selector == "gb":
16 --trans_table "${stop_codon_opts.genbank_gencode}"
17 #else:
18 --stop_codons "${stop_codon_opts.stop_codons}"
19 #end if
20
21 $outfile &lt; $infile
22 </command>
23 <inputs>
24 <param name="infile" type="data" format="fasta" label="Trainings Dataset" help="A set of known genes in FASTA format." />
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." />
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, ..." />
27 <param name="width" type="integer" value="12" label="Set the width of the ICM" help="The width includes the predicted position." />
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" />
29
30 <conditional name="stop_codon_opts">
31 <param name="stop_codon_opts_selector" type="select" label="Specify start codons as">
32 <option value="gb" selected="True">Genbank translation table entry</option>
33 <option value="free_form">Comma-separated list</option>
34 </param>
35 <when value="gb">
36 <param name="genbank_gencode" type="select" label="Use Genbank translation table to specify stop codons">
37 <option value="1" select="True">1. Standard</option>
38 <option value="2">2. Vertebrate Mitochondrial</option>
39 <option value="3">3. Yeast Mitochondrial</option>
40 <option value="4">4. Mold, Protozoan, and Coelenterate Mitochondrial Code and the Mycoplasma/Spiroplasma Code</option>
41 <option value="5">5. Invertebrate Mitochondrial</option>
42 <option value="6">6. Ciliate, Dasycladacean and Hexamita Nuclear Code</option>
43 <option value="9">9. Echinoderm Mitochondrial</option>
44 <option value="10">10. Euplotid Nuclear</option>
45 <option value="11">11. Bacteria and Archaea</option>
46 <option value="12">12. Alternative Yeast Nuclear</option>
47 <option value="13">13. Ascidian Mitochondrial</option>
48 <option value="14">14. Flatworm Mitochondrial</option>
49 <option value="15">15. Blepharisma Macronuclear</option>
50 <option value="16">16. Chlorophycean Mitochondrial</option>
51 <option value="21">21. Trematode Mitochondrial</option>
52 <option value="22">22. Scenedesmus obliquus mitochondrial</option>
53 <option value="23">23. Thraustochytrium Mitochondrial</option>
54 <option value="24">24. Pterobranchia mitochondrial</option>
55 </param>
56 </when>
57 <when value="free_form">
58 <param name="stop_codons" type="text" value="tag,tga,taa" label="Specify stop codons as a comma-separated list" />
59 </when>
60 </conditional>
61
62 </inputs>
63 <outputs>
64 <data format="binary" name="outfile" />
65 </outputs>
66 <tests>
67 <test>
68 <param name="infile" value='glimmer3/seqTest.fa'/>
69 <output name="outfile" file='glimmer3/buildICMTestOutput.dat'/>
70 </test>
71 </tests>
72
73 <help>
74
75 **What it does**
76
77 This program constructs an interpolated context model (ICM) from an input set of sequences.
78 This model can be used by Glimmer3 to predict genes.
79
80 -----
81
82
83 **Example**
84
85 * input::
86
87 -Genome Sequence
88
89 >CELF22B7 C.aenorhabditis elegans (Bristol N2) cosmid F22B7
90 GATCCTTGTAGATTTTGAATTTGAAGTTTTTTCTCATTCCAAAACTCTGT
91 GATCTGAAATAAAATGTCTCAAAAAAATAGAAGAAAACATTGCTTTATAT
92 TTATCAGTTATGGTTTTCAAAATTTTCTGACATACCGTTTTGCTTCTTTT
93 TTTCTCATCTTCTTCAAATATCAATTGTGATAATCTGACTCCTAACAATC
94 GAATTTCTTTTCCTTTTTCTTTTTCCAACAACTCCAGTGAGAACTTTTGA
95 ATATCTTCAAGTGACTTCACCACATCAGAAGGTGTCAACGATCTTGTGAG
96 AACATCGAATGAAGATAATTTTAATTTTAGAGTTACAGTTTTTCCTCCGA
97 CAATTCCTGATTTACGAACATCTTCTTCAAGCATTCTACAGATTTCTTGA
98 TGCTCTTCTAGGAGGATGTTGAAATCCGAAGTTGGAGAAAAAGTTCTCTC
99 AACTGAAATGCTTTTTCTTCGTGGATCCGATTCAGATGGACGACCTGGCA
100 GTCCGAGAGCCGTTCGAAGGAAAGATTCTTGTGAGAGAGGCGTGAAACAC
101 AAAGGGTATAGGTTCTTCTTCAGATTCATATCACCAACAGTTTGAATATC
102 CATTGCTTTCAGTTGAGCTTCGCATACACGACCAATTCCTCCAACCTAAA
103 AAATTATCTAGGTAAAACTAGAAGGTTATGCTTTAATAGTCTCACCTTAC
104 GAATCGGTAAATCCTTCAAAAACTCCATAATCGCGTTTTTATCATTTTCT
105 .....
106
107 * output:
108 interpolated context model (ICM)
109
110
111 -------
112
113 **References**
114
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).
116
117
118 </help>
119 </tool>