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comparison glimmer_wo_icm.xml @ 0:841357e0acbf draft

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author bgruening
date Sat, 06 Jul 2013 10:09:30 -0400
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1 <tool id="glimmer_not-knowlegde-based" name="Glimmer3" version="0.2">
2 <description>Predict ORFs in prokaryotic genomes (not knowlegde-based)</description>
3 <requirements>
4 <requirement type="package" version="3.02b">glimmer</requirement>
5 <requirement type="package" version="1.61">biopython</requirement>
6 </requirements>
7 <command interpreter="python">
8 glimmer_wo_icm.py
9 $input
10 #if $report:
11 $prediction
12 #else:
13 "None"
14 #end if
15 #if $detailed_report:
16 $detailed
17 #else:
18 "None"
19 #end if
20 $overlap
21 $gene_length
22 $threshold
23 $linear
24 $genes_output
25 </command>
26 <inputs>
27 <param name="input" type="data" format="fasta" label="Genome sequence" />
28 <param name="overlap" type="integer" value="0" label="Set maximum overlap length. Overlaps this short or shorter are ignored." />
29 <param name="gene_length" type="integer" value="110" label="Set minimum gene length." />
30 <param name="threshold" type="integer" value="30" label="Set threshold score for calling as gene. If the in-frame score >= N, then the region is given a number and considered a potential gene." />
31 <param name="linear" type="boolean" truevalue="true" falsevalue="false" checked="true" label="Assume linear rather than circular genome, i.e., no wraparound" />
32
33 <param name="detailed_report" type="boolean" truevalue="" falsevalue="" checked="false" label="Output a detailed gene prediction report as separate file" />
34 <param name="report" type="boolean" truevalue="" falsevalue="" checked="false" label="Report the classic glimmer table output" />
35 </inputs>
36 <outputs>
37 <data name="genes_output" format="fasta" label="Glimmer3 on ${on_string} (Gene Prediction FASTA)" />
38 <data name="prediction" format="txt" label="Glimmer3 on ${on_string} (Gene Prediction table)">
39 <filter>report == True</filter>
40 </data>
41 <data name="detailed" format="txt" label="Glimmer3 on ${on_string} (detailed report)">
42 <filter>detailed_report == True</filter>
43 </data>
44 </outputs>
45 <tests>
46 <test>
47 <param name="input" value="streptomyces_Tue6071_plasmid_genomic.fasta" />
48 <param name="overlap" value="0" />
49 <param name="gene_length" value="110" />
50 <param name="threshold" value="30" />
51 <param name="linear" value="true" />
52 <param name="detailed_report" value="" />
53 <param name="report" value="" />
54 <output name="genes_output" file="glimmer_wo_icm_trans-table-11_plasmid_genomic.fasta" ftype="fasta" />
55 </test>
56 </tests>
57 <help>
58
59 **What it does**
60
61 This tool predicts open reading frames (orfs) from a given DNA Sequence. That tool is not knowlegde-based.
62
63 The recommended way is to use a trained Glimmer3 with ICM model. Use the knowlegde-based version for that and insert/generate a training set.
64
65 -----
66
67 **Glimmer Overview**
68
69 ::
70
71 ************** ************** ************** **************
72 * * * * * * * *
73 * long-orfs * ===> * Extract * ===> * build-icm * ===> * glimmer3 *
74 * * * * * * * *
75 ************** ************** ************** **************
76
77 -----
78
79 **Example**
80
81 Suppose you have the following DNA sequences::
82
83 >SQ Sequence 8667507 BP; 1203558 A; 3121252 C; 3129638 G; 1213059 T; 0 other;
84 cccgcggagcgggtaccacatcgctgcgcgatgtgcgagcgaacacccgggctgcgcccg
85 ggtgttgcgctcccgctccgcgggagcgctggcgggacgctgcgcgtcccgctcaccaag
86 cccgcttcgcgggcttggtgacgctccgtccgctgcgcttccggagttgcggggcttcgc
87 cccgctaaccctgggcctcgcttcgctccgccttgggcctgcggcgggtccgctgcgctc
88 ccccgcctcaagggcccttccggctgcgcctccaggacccaaccgcttgcgcgggcctgg
89 .......
90
91 Running this tool will produce a FASTA file with predicted genes and glimmer output files like the following::
92
93 >SQ Sequence 8667507 BP; 1203558 A; 3121252 C; 3129638 G; 1213059 T; 0 other;
94 orf00001 577 699 +1 5.24
95 orf00003 800 1123 +2 5.18
96 orf00004 1144 3813 +1 10.62
97 orf00006 3857 6220 +2 6.07
98 orf00007 6226 7173 +1 1.69
99 orf00008 7187 9307 +2 8.95
100 orf00009 9424 10410 +1 8.29
101 orf00010 10515 11363 +3 7.00
102 orf00011 11812 11964 +1 2.80
103 orf00012 12360 13457 +3 4.80
104 orf00013 14379 14044 -1 7.41
105 orf00015 15029 14739 -3 12.43
106 orf00016 15066 15227 +3 1.91
107 orf00020 16061 15351 -3 2.83
108 orf00021 17513 17391 -3 2.20
109 orf00023 17529 17675 +3 0.11
110
111
112 -------
113
114 **References**
115
116 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).
117
118 </help>
119 </tool>