annotate tools/protein_analysis/wolf_psort.xml @ 16:7de64c8b258d draft

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

<tool id="wolf_psort" name="WoLF PSORT" version="0.0.6">
    <description>Eukaryote protein subcellular localization prediction</description>
    <command interpreter="python">
      wolf_psort.py $organism "\$NSLOTS" "$fasta_file" "$tabular_file"
      ##I want the number of threads to be a Galaxy config option...
      ##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 python wrapper
      ##defaults to four threads.
    </command>
    <stdio>
        <!-- Anything other than zero is an error -->
        <exit_code range="1:" />
        <exit_code range=":-1" />
    </stdio>
    <inputs>
        <param name="fasta_file" type="data" format="fasta" label="FASTA file of protein sequences"/> 
        <param name="organism" type="select" display="radio" label="Organism">
            <option value="animal">Animal</option>
            <option value="plant">Plant</option>
            <option value="fungi">Fungi</option>
        </param>
    </inputs>
    <outputs>
        <data name="tabular_file" format="tabular" label="WoLF PSORT $organism results" />
    </outputs>
    <requirements>
        <requirement type="binary">runWolfPsortSummary</requirement>
    </requirements>
    <tests>
        <test>
            <param name="fasta_file" value="four_human_proteins.fasta" ftype="fasta"/>
            <param name="organism" value="animal"/>
            <output name="tabular_file" file="four_human_proteins.wolf_psort.tabular" ftype="tabular"/>
        </test>
        <test>
            <param name="fasta_file" value="empty.fasta" ftype="fasta"/>
            <param name="organism" value="animal"/>
            <output name="tabular_file" file="empty_wolf_psort.tabular" ftype="tabular"/>
        </test>
        <test>
            <param name="fasta_file" value="empty.fasta" ftype="fasta"/>
            <param name="organism" value="plant"/>
            <output name="tabular_file" file="empty_wolf_psort.tabular" ftype="tabular"/>
        </test>
        <test>
            <param name="fasta_file" value="empty.fasta" ftype="fasta"/>
            <param name="organism" value="fungi"/>
            <output name="tabular_file" file="empty_wolf_psort.tabular" ftype="tabular"/>
        </test>
    </tests>
    <help>
    
**What it does**

This calls the WoLF PSORT tool for prediction of eukaryote protein subcellular localization.

The input is a FASTA file of protein sequences, and the output is tabular with four columns (multiple rows per protein):

====== ===================
Column Description
------ -------------------
     1 Sequence identifier
     2 Compartment
     3 Score
     4 Prediction rank
====== ===================


**Localization Compartments**

The table below gives the WoLF PSORT localization site definitions, and the corresponding Gene Ontology (GO) term.

====== ===================== =====================
Abbrev Localization Site     GO Cellular Component
------ --------------------- ---------------------
chlo   chloroplast           0009507, 0009543
cyto   cytosol               0005829
cysk   cytoskeleton          0005856(2)
E.R.   endoplasmic reticulum 0005783
extr   extracellular         0005576, 0005618
golg   Golgi apparatus       0005794(1)
lyso   lysosome		     0005764
mito   mitochondria	     0005739
nucl   nuclear		     0005634
pero   peroxisome	     0005777(2)
plas   plasma membrane	     0005886
vacu   vacuolar membrane     0005774(2)
====== ===================== =====================

Numbers in parentheses, such as "0005856(2)" indicate that descendant "part_of"
cellular components were also included, up to the specified depth (2 in this case).
For example, all of the children and grandchildren of "GO:0005856" were
included as "cysk". 

Additionally compound predictions like mito_nucl are also given.


**Notes**

The raw output from WoLF PSORT looks like this (space separated), showing two proteins:

================================ ============================================
gi|301087619|ref|XP_002894699.1| extr 12, mito 4, E.R. 3, golg 3, mito_nucl 3
gi|301087623|ref|XP_002894700.1| extr 21, mito 2, cyto 2, cyto_mito 2
================================ ============================================

This is reformatted into a tabular file as follows for use in Galaxy:

================================ =========== ===== ====
#ID                              Compartment Score Rank
-------------------------------- ----------- ----- ----
gi|301087619|ref|XP_002894699.1| extr           12    1
gi|301087619|ref|XP_002894699.1| mito            4    2
gi|301087619|ref|XP_002894699.1| E.R.            3    3
gi|301087619|ref|XP_002894699.1| golg            3    4
gi|301087619|ref|XP_002894699.1| mito_nucl       3    5
gi|301087623|ref|XP_002894700.1| extr           21    1
gi|301087623|ref|XP_002894700.1| mito            2    2
gi|301087623|ref|XP_002894700.1| cyto            2    3
gi|301087623|ref|XP_002894700.1| cyto_mito       2    4
================================ =========== ===== ====

This way you can easily filter for things like having a top prediction for
mitochondria (c2=='mito' and c4==1), or extracellular with a score of at
least 10 (c2=='extr' and 10&lt;=c3), and so on.


**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

Paul Horton, Keun-Joon Park, Takeshi Obayashi, Naoya Fujita, Hajime Harada, C.J. Adams-Collier, and Kenta Nakai (2007).
WoLF PSORT: Protein Localization Predictor.
Nucleic Acids Research, 35(S2), W585-W587.
http://dx.doi.org/10.1093/nar/gkm259

Paul Horton, Keun-Joon Park, Takeshi Obayashi and Kenta Nakai (2006).
Protein Subcellular Localization Prediction with WoLF PSORT.
Proceedings of the 4th Annual Asia Pacific Bioinformatics Conference APBC06, Taipei, Taiwan. pp. 39-48.

See also http://wolfpsort.org

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>