comparison genecaller.xml @ 35:fa736576c7ed draft

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35:fa736576c7ed

<tool id="DGenes" name="Gene prediction" version="1.0.0">
	<description/>
	<requirements>
		<container type="docker">jjkoehorst/sappdocker:GENECALLER</container>
	</requirements>
	<command interpreter="docker">java -jar /genecaller/genecaller-0.0.1-SNAPSHOT-jar-with-dependencies.jar
		'-runtype' '$runtype' -input $input -output $output -codon $codon -format TURTLE
	</command>
	<inputs>
		<param format="ttl" label="ttl genome file" name="input" type="data"/>
		<param label="codon table selection" name="codon" type="select">
			<option value="11">The Bacterial, Archaeal and Plant Plastid Code
				(transl_table=11)
			</option>
			<option value="4">The Mold, Protozoan, Coelenterate Mitochondrial
				and Mycoplasma/Spiroplasma Code (transl_table=4)
			</option>
		</param>
		<param label="single or meta genome" name="runtype" type="select">
			<option value="single">Single genome analysis</option>
			<option value="meta">Metagenome analysis</option>
		</param>
	</inputs>
	<outputs>
		<data format="ttl" label="ORF: ${input.name}" name="output"/>
	</outputs>
	<help>Prodigal gene prediction requires an RDF file from either a
		Genome FASTA or
		Genbank/EMBL format.
	</help>
	<citations>
		<citation type="bibtex">@article{Hyatt2010,
			abstract = {BACKGROUND: The
			quality of automated gene prediction in microbial
			organisms has
			improved steadily over the past decade, but there is
			still room for
			improvement. Increasing the number of correct
			identifications, both of
			genes and of the translation initiation
			sites for each gene, and
			reducing the overall number of false
			positives, are all desirable
			goals.

			RESULTS: With our years of experience in manually curating
			genomes for the
			Joint Genome Institute, we developed a new gene
			prediction algorithm
			called Prodigal (PROkaryotic DYnamic programming
			Gene-finding
			ALgorithm). With Prodigal, we focused specifically on the
			three goals
			of improved gene structure prediction, improved
			translation
			initiation site recognition, and reduced false positives.
			We compared
			the results of Prodigal to existing gene-finding methods
			to
			demonstrate that it met each of these objectives.

			CONCLUSION: We
			built a fast, lightweight, open source gene prediction program
			called
			Prodigal http://compbio.ornl.gov/prodigal/. Prodigal achieved
			good
			results compared to existing methods, and we believe it will be
			a
			valuable asset to automated microbial annotation pipelines.},
			author =
			{Hyatt, Doug and Chen, Gwo-Liang and Locascio, Philip F and
			Land,
			Miriam L and Larimer, Frank W and Hauser, Loren J},
			doi =
			{10.1186/1471-2105-11-119},
			file =
			{:Users/koeho006/Library/Application Support/Mendeley
			Desktop/Downloaded/Hyatt et al. - 2010 - Prodigal prokaryotic gene
			recognition and translation initiation site identification.pdf:pdf},
			issn = {1471-2105},
			journal = {BMC bioinformatics},
			keywords =
			{Algorithms,Databases, Genetic,Genome, Bacterial,Peptide Chain
			Initiation, Translational,Peptide Chain Initiation, Translational:
			genetics,Prokaryotic Cells,Software},
			mendeley-groups = {Dump/VAPP
			Paper},
			month = jan,
			number = {1},
			pages = {119},
			pmid = {20211023},
			title = {{Prodigal: prokaryotic gene recognition and translation
			initiation site identification.}},
			url =
			{http://www.biomedcentral.com/1471-2105/11/119},
			volume = {11},
			year =
			{2010}
			}

		</citation>
	</citations>
</tool>