|
0
|
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>
|
