comparison tools/protein_analysis/signalp3.xml @ 16:7de64c8b258d draft

Uploaded v0.2.5, MIT licence, RST for README, citation information, development moved to GitHub

15:6abd809cefdd

<tool id="signalp3" name="SignalP 3.0" version="0.0.11">
    <description>Find signal peptides in protein sequences</description>
    <!-- If job splitting is enabled, break up the query file into parts -->
    <!-- Using 2000 chunks meaning 4 threads doing 500 each is ideal -->
    <parallelism method="basic" split_inputs="fasta_file" split_mode="to_size" split_size="2000" merge_outputs="tabular_file"></parallelism>
    <command interpreter="python">
      signalp3.py $organism $truncate "\$NSLOTS" $fasta_file $tabular_file
      ##Set the number of threads in the runner entry in universe_wsgi.ini
      ##which (on SGE at least) will set the $NSLOTS environment variable.
      ##If the environment variable isn't set, get "", and defaults to one.
    </command>
    <stdio>
        <!-- Anything other than zero is an error -->
        <exit_code range="1:" />
        <exit_code range=":-1" />

Signal peptides are found at the start of a protein, so there is limited value in providing the full length sequence, and providing the full sequence slows down the analysis. Furthermore, SignalP has an upper bound on the sequence length it will accept (6000bp). Thus for practical reasons it is useful to truncate the proteins before passing them to SignalP. However, the precise point they are truncated does have a small influence on some score values, and thus to the results.

**References**

Bendtsen, Nielsen, von Heijne, and Brunak.
Improved prediction of signal peptides: SignalP 3.0.
J. Mol. Biol., 340:783-795, 2004.
http://dx.doi.org/10.1016/j.jmb.2004.05.028

Nielsen, Engelbrecht, Brunak and von Heijne.
Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites.
Protein Engineering, 10:1-6, 1997.
http://dx.doi.org/10.1093/protein/10.1.1

Nielsen and Krogh.
Prediction of signal peptides and signal anchors by a hidden Markov model.
Proceedings of the Sixth International Conference on Intelligent Systems for Molecular Biology (ISMB 6),
AAAI Press, Menlo Park, California, pp. 122-130, 1998.
http://www.ncbi.nlm.nih.gov/pubmed/9783217

http://www.cbs.dtu.dk/services/SignalP-3.0/output.php

    </help>
</tool>

16:7de64c8b258d

<tool id="signalp3" name="SignalP 3.0" version="0.0.12">
    <description>Find signal peptides in protein sequences</description>
    <!-- If job splitting is enabled, break up the query file into parts -->
    <!-- Using 2000 chunks meaning 4 threads doing 500 each is ideal -->
    <parallelism method="basic" split_inputs="fasta_file" split_mode="to_size" split_size="2000" merge_outputs="tabular_file"></parallelism>
    <command interpreter="python">
      signalp3.py $organism $truncate "\$NSLOTS" $fasta_file $tabular_file
      ##Set the number of threads in the runner entry in universe_wsgi.ini
      ##which (on SGE at least) will set the $NSLOTS environment variable.
      ##If the environment variable isn't set, get "", and the python wrapper
      ##defaults to four threads.
    </command>
    <stdio>
        <!-- Anything other than zero is an error -->
        <exit_code range="1:" />
        <exit_code range=":-1" />

Signal peptides are found at the start of a protein, so there is limited value in providing the full length sequence, and providing the full sequence slows down the analysis. Furthermore, SignalP has an upper bound on the sequence length it will accept (6000bp). Thus for practical reasons it is useful to truncate the proteins before passing them to SignalP. However, the precise point they are truncated does have a small influence on some score values, and thus to the results.

**References**

If you use this Galaxy tool in work leading to a scientific publication please
cite the following papers:

Peter J.A. Cock, Björn A. Grüning, Konrad Paszkiewicz and Leighton Pritchard (2013).
Galaxy tools and workflows for sequence analysis with applications
in molecular plant pathology. PeerJ 1:e167
http://dx.doi.org/10.7717/peerj.167

Bendtsen, Nielsen, von Heijne, and Brunak (2004).
Improved prediction of signal peptides: SignalP 3.0.
J. Mol. Biol., 340:783-795.
http://dx.doi.org/10.1016/j.jmb.2004.05.028

Nielsen, Engelbrecht, Brunak and von Heijne (1997).
Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites.
Protein Engineering, 10:1-6.
http://dx.doi.org/10.1093/protein/10.1.1

Nielsen and Krogh (1998).
Prediction of signal peptides and signal anchors by a hidden Markov model.
Proceedings of the Sixth International Conference on Intelligent Systems for Molecular Biology (ISMB 6),
AAAI Press, Menlo Park, California, pp. 122-130.
http://www.ncbi.nlm.nih.gov/pubmed/9783217

See also http://www.cbs.dtu.dk/services/SignalP-3.0/output.php

This wrapper is available to install into other Galaxy Instances via the Galaxy
Tool Shed at http://toolshed.g2.bx.psu.edu/view/peterjc/tmhmm_and_signalp
    </help>
</tool>