comparison tools/filters/get_orfs_or_cdss.xml @ 0:9cff9a1176ea

Uploaded v0.0.1

0:9cff9a1176ea

<tool id="get_orfs_or_cdss" name="Get open reading frames (ORFs) or coding sequences (CDSs)" version="0.0.1">
	<description>e.g. to get peptides from ESTs</description>
	<command interpreter="python">
get_orfs_or_cdss.py $input_file $input_file.ext $table $ftype $ends $mode $min_len $strand $out_nuc_file $out_prot_file
	</command>
	<inputs>
		<param name="input_file" type="data" format="fasta,fastq,sff" label="Sequence file (nucleotides)" help="FASTA, FASTQ, or SFF format." />
		<param name="table" type="select" label="Genetic code" help="Tables from the NCBI, these determine the start and stop codons">
			<option value="1">1. Standard</option>
			<option value="2">2. Vertebrate Mitochondrial</option>
			<option value="3">3. Yeast Mitochondrial</option>
			<option value="4">4. Mold, Protozoan, Coelenterate Mitochondrial and Mycoplasma/Spiroplasma</option>
			<option value="5">5. Invertebrate Mitochondrial</option>
			<option value="6">6. Ciliate Macronuclear and Dasycladacean</option>
			<option value="9">9. Echinoderm Mitochondrial</option>
			<option value="10">10. Euplotid Nuclear</option>
			<option value="11">11. Bacterial</option>
			<option value="12">12. Alternative Yeast Nuclear</option>
			<option value="13">13. Ascidian Mitochondrial</option>
			<option value="14">14. Flatworm Mitochondrial</option>
			<option value="15">15. Blepharisma Macronuclear</option>
			<option value="16">16. Chlorophycean Mitochondrial</option>
			<option value="21">21. Trematode Mitochondrial</option>
			<option value="22">22. Scenedesmus obliquus</option>
			<option value="23">23. Thraustochytrium Mitochondrial</option>
		</param>
		<param name="ftype" type="select" value="True" label="Look for ORFs or CDSs">
                        <option value="ORF">Look for ORFs (check for stop codons only, ignore start codons)</option>
                        <option value="CDS">Look for CDSs (with start and stop codons)</option>
		</param>
                <param name="ends" type="select" value="open" label="Sequence end treatment">
			<option value="open">Open ended (will allow missing start/stop codons at the ends)</option>
                        <option value="closed">Complete (will check for start/stop codons at the ends)</option>
                        <!-- TODO? Circular, for using this on finished bacteria etc -->
                </param>

		<param name="mode" type="select" label="Selection criteria" help="Suppose a sequence has ORFs/CDSs of lengths 100, 102 and 102 -- which should be taken? These options would return 3, 2 or 1 ORF.">
                    <option value="all">All ORFs/CDSs from each sequence</option>
                    <option value="top">All ORFs/CDSs from each sequence with the maximum length</option>
                    <option value="one">First ORF/CDS from each sequence with the maximum length</option>
		</param>
                <param name="min_len" type="integer" size="5" value="30" label="Minimum length ORF/CDS (in amino acids, e.g. 30 aa = 90 bp plus any stop codon)">
                </param>
                <param name="strand" type="select" label="Strand to search" help="Use the forward only option if your sequence directionality is known (e.g. from poly-A tails, or strand specific RNA sequencing.">
                    <option value="both">Search both the forward and reverse strand</option>
                    <option value="forward">Only search the forward strand</option>
                    <option value="reverse">Only search the reverse strand</option>
                </param>
	</inputs>
	<outputs>
		<data name="out_nuc_file" format="fasta" label="${ftype.value}s (nucleotides)" />
		<data name="out_prot_file" format="fasta" label="${ftype.value}s (amino acids)" />
	</outputs>
	<tests>
                <test>
                        <param name="input_file" value="get_orf_input.fasta" />
                        <param name="table" value="1" />
                        <param name="ftype" value="CDS" />
                        <param name="ends" value="open" />
                        <param name="mode" value="all" />
                        <param name="min_len" value="10" />
                        <param name="strand" value="forward" />
                        <output name="out_nuc_file" file="get_orf_input.t1_nuc_out.fasta" />
                        <output name="out_prot_file" file="get_orf_input.t1_prot_out.fasta" />
                </test>
		<test>
			<param name="input_file" value="get_orf_input.fasta" />
			<param name="table" value="11" />
			<param name="ftype" value="CDS" />
			<param name="ends" value="closed" />
			<param name="mode" value="all" />
			<param name="min_len" value="10" />
			<param name="strand" value="forward" />
			<output name="out_nuc_file" file="get_orf_input.t11_nuc_out.fasta" />
			<output	name="out_prot_file" file="get_orf_input.t11_prot_out.fasta" />
		</test>
		<test>
                        <param name="input_file" value="get_orf_input.fasta" />
                        <param name="table" value="11" />
                        <param name="ftype" value="CDS" />
                        <param name="ends" value="open" />
                        <param name="mode" value="all" />
                        <param name="min_len" value="10" />
                        <param name="strand" value="forward" />
                        <output name="out_nuc_file" file="get_orf_input.t11_open_nuc_out.fasta" />
                        <output name="out_prot_file" file="get_orf_input.t11_open_prot_out.fasta" />
		</test>
	</tests>
	<requirements>
		<requirement type="python-module">Bio</requirement>
	</requirements>
	<help>

**What it does**

Takes an input file of nucleotide sequences (typically FASTA, but also FASTQ
and Standard Flowgram Format (SFF) are supported), and searches each sequence
for open reading frames (ORFs) or potential coding sequences (CDSs) of the
given minimum length. These are returned as FASTA files of nucleotides and
protein sequences.

You can choose to have all the ORFs/CDSs above the minimum length for each
sequence (similar to the EMBOSS getorf tool), those with the longest length
equal, or the first ORF/CDS with the longest length (in the special case
where a sequence encodes two or more long ORFs/CDSs of the same length). The
last option is a reasonable choice when the input sequences represent EST or
mRNA sequences, where only one ORF/CDS is expected.

Note that if no ORFs/CDSs in a sequence match the criteria, there will be no
output for that sequence.

Also note that the ORFs/CDSs are assigned modified identifiers to distinguish
them from the original full length sequences, by appending a suffix.

The start and stop codons are taken from the `NCBI Genetic Codes
&lt;http://www.ncbi.nlm.nih.gov/Taxonomy/Utils/wprintgc.cgi&gt;`_.
When searching for ORFs, the sequences will run from stop codon to stop
codon, and any start codons are ignored. When searching for CDSs, the first
potential start codon will be used, giving the longest possible CDS within
each ORF, and thus the longest possible protein sequence. This is useful
for things like BLAST or domain searching, but since this may not be the
correct start codon may not be appropriate for signal peptide detection
etc.

**Example Usage**

Given some EST sequences (Sanger capillary reads) assembled into unigenes,
or a transcriptome assembly from some RNA-Seq, each of your nucleotide
sequences should (barring sequencing, assembly errors, frame-shifts etc)
encode one protein as a single ORF/CDS, which you wish to extract (and
perhaps translate into amino acids).

If your RNS-Seq data was strand specific, and assembled taking this into
account, you should only search for ORFs/CDSs on the forward strand.

**Citation**

This tool uses Biopython. If you use this tool in scientific work leading
to a publication, please cite the Biopython application note (and Galaxy
too of course):

Cock et al 2009. Biopython: freely available Python tools for computational
molecular biology and bioinformatics. Bioinformatics 25(11) 1422-3.
http://dx.doi.org/10.1093/bioinformatics/btp163 pmid:19304878.

	</help>
</tool>