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date Wed, 29 Jun 2016 01:36:58 -0400
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1 <tool id="DGenes" name="Gene prediction" version="1.0.0">
2 <description/>
3 <requirements>
4 <container type="docker">jjkoehorst/sappdocker:GENECALLER</container>
5 </requirements>
6 <command interpreter="docker">java -jar /genecaller/target/genecaller-0.0.1-SNAPSHOT-jar-with-dependencies.jar
7 '-runtype' '$runtype' -input $input -output $output -codon $codon -format TURTLE
8 </command>
9 <inputs>
10 <param format="ttl" label="ttl genome file" name="input" type="data"/>
11 <param label="codon table selection" name="codon" type="select">
12 <option value="11">The Bacterial, Archaeal and Plant Plastid Code
13 (transl_table=11)
14 </option>
15 <option value="4">The Mold, Protozoan, Coelenterate Mitochondrial
16 and Mycoplasma/Spiroplasma Code (transl_table=4)
17 </option>
18 </param>
19 <param label="single or meta genome" name="runtype" type="select">
20 <option value="single">Single genome analysis</option>
21 <option value="meta">Metagenome analysis</option>
22 </param>
23 </inputs>
24 <outputs>
25 <data format="ttl" label="ORF: ${input.name}" name="output"/>
26 </outputs>
27 <help>Prodigal gene prediction requires an RDF file from either a
28 Genome FASTA or
29 Genbank/EMBL format.
30 </help>
31 <citations>
32 <citation type="bibtex">@article{Hyatt2010,
33 abstract = {BACKGROUND: The
34 quality of automated gene prediction in microbial
35 organisms has
36 improved steadily over the past decade, but there is
37 still room for
38 improvement. Increasing the number of correct
39 identifications, both of
40 genes and of the translation initiation
41 sites for each gene, and
42 reducing the overall number of false
43 positives, are all desirable
44 goals.
45
46 RESULTS: With our years of experience in manually curating
47 genomes for the
48 Joint Genome Institute, we developed a new gene
49 prediction algorithm
50 called Prodigal (PROkaryotic DYnamic programming
51 Gene-finding
52 ALgorithm). With Prodigal, we focused specifically on the
53 three goals
54 of improved gene structure prediction, improved
55 translation
56 initiation site recognition, and reduced false positives.
57 We compared
58 the results of Prodigal to existing gene-finding methods
59 to
60 demonstrate that it met each of these objectives.
61
62 CONCLUSION: We
63 built a fast, lightweight, open source gene prediction program
64 called
65 Prodigal http://compbio.ornl.gov/prodigal/. Prodigal achieved
66 good
67 results compared to existing methods, and we believe it will be
68 a
69 valuable asset to automated microbial annotation pipelines.},
70 author =
71 {Hyatt, Doug and Chen, Gwo-Liang and Locascio, Philip F and
72 Land,
73 Miriam L and Larimer, Frank W and Hauser, Loren J},
74 doi =
75 {10.1186/1471-2105-11-119},
76 file =
77 {:Users/koeho006/Library/Application Support/Mendeley
78 Desktop/Downloaded/Hyatt et al. - 2010 - Prodigal prokaryotic gene
79 recognition and translation initiation site identification.pdf:pdf},
80 issn = {1471-2105},
81 journal = {BMC bioinformatics},
82 keywords =
83 {Algorithms,Databases, Genetic,Genome, Bacterial,Peptide Chain
84 Initiation, Translational,Peptide Chain Initiation, Translational:
85 genetics,Prokaryotic Cells,Software},
86 mendeley-groups = {Dump/VAPP
87 Paper},
88 month = jan,
89 number = {1},
90 pages = {119},
91 pmid = {20211023},
92 title = {{Prodigal: prokaryotic gene recognition and translation
93 initiation site identification.}},
94 url =
95 {http://www.biomedcentral.com/1471-2105/11/119},
96 volume = {11},
97 year =
98 {2010}
99 }
100
101 </citation>
102 </citations>
103 </tool>