annotate interproscan.xml @ 1:eb12db502d3c draft

updated tool help

<tool id="interproscan" name="Interproscan functional predictions of ORFs"  version="1.2">
    <description>Interproscan functional predictions of ORFs</description>
    <command>
## The command is a Cheetah template which allows some Python based syntax.
## Lines starting hash hash are comments. Galaxy will turn newlines into spaces

## create temp directory
#import tempfile, os
#set $tfile = tempfile.mkstemp()[1]

sed 's/ /_/g' $input > $tfile;

## Hack, because interproscan does not seem to produce gff output even if it is configured
#if str($oformat) == "gff":
    #set $tfile2 = tempfile.mkstemp()[1]
    iprscan -cli -nocrc -i $tfile -o $tfile2 -goterms -seqtype p -altjobs -format raw -appl $appl 2>&#38;1;
    converter.pl -format gff3 -input $tfile2 -output $output;
    rm $tfile2;
#else
    iprscan -cli -nocrc -i $tfile -o $output -goterms -seqtype p -altjobs -format $oformat -appl $appl 2>&#38;1;
#end if

rm $tfile

    </command>
        <inputs>
            <param name="input" type="data" format="fasta" label="Protein Fasta File"/>

            <param name="appl" type="select" format="text" label="Applications to run" help="Select your programm.">
                <option value="blastprodom+coils+gene3d+hamap+hmmpanther+hmmpir+hmmpfam+hmmsmart+hmmtigr+fprintscan+patternscan+profilescan+superfamily+seg+signalp+tmhmm" selected="true">all</option>
                <option value="seg">seg</option>
                <option value="signalp">signalp</option>
                <option value="tmhmm">tmhmm</option>
                <option value="fprintscan">fprintscan</option>
                <option value="patternscan">patternscan</option>
                <option value="profilescan">profilescan</option>
                <option value="superfamily">superfamily</option>
                <option value="hmmpir">hmmpir</option>
                <option value="hmmpfam">hmmpfam</option>
                <option value="hmmsmart">hmmsmart</option>
                <option value="hmmtigr">hmmtigr</option>
                <option value="hmmpanther">hmmpanther</option>
                <option value="hamap">hamap</option>
                <option value="gene3d">gene3d</option>
                <option value="coils">coils</option>
                <option value="blastprodom">blastprodom</option>
            </param>

            <param name="oformat" type="select" label="Output format" help="Please select a output format.">
                <option value="gff">gff</option>
                <option value="raw" selected="true">raw</option>
                <option value="txt">txt</option>
                <option value="html">html</option>
                <option value="xml">xml</option>
                <option value="ebixml">EBI header on top of xml</option>
            </param>

        </inputs>
    <outputs>

        <data format="txt" name="output" label="Interproscan calculation on ${on_string}">
            <change_format>
                <when input="oformat" value="html" format="html"/>
                <when input="oformat" value="xml" format="xml"/>
                <when input="oformat" value="ebixml" format="xml"/>
                <when input="oformat" value="gff" format="gff"/>
            </change_format>
        </data>

    </outputs>
    <requirements>
    </requirements>
    <help>
**What it does**

Interproscan is a batch tool to query the Interpro database. It provides annotations based on multiple searches of profile and other functional databases. 
These include SCOP, CATH, PFAM and SUPERFAMILY.

**Input**

Required is a FASTA file containing ORF predictions. This file must NOT contain any spaces in the FASTA headers - any spaces will be convereted to underscores ``_`` by this tool before running with Interproscan.

**Output**

Example for the raw format.
The output will consist of a file in Interproscan raw format, a tabular file in galaxy with 14 columns. 
This can be use to upload the data into a relational database or concatenation of different runs.

====== ================================================================ ======================================================================
column example                                                          description
====== ================================================================ ======================================================================
c1     NF00181542                                                       the id of the input sequence
c2     27A9BBAC0587AB84                                                 the crc64 (checksum) of the protein sequence (supposed to be unique)
c3     272                                                              the length of the sequence (in AA)
c4     HMMPIR                                                           the anaysis method launched. 
c5     PIRSF001424                                                      the database members entry for this match
c6     Prephenate dehydratase                                           the database member description for the entry
c7     1                                                                the start of the domain match 
c8     270                                                              the end of the domain match
c9     6.5e-141                                                         the evalue of the match (reported by member database method) 
c10    T                                                                the status of the match (T: true, ?: unknown) 
c11    06-Aug-2005                                                      the date of the run. 
c12    IPR008237                                                        the corresponding InterPro entry (if iprlookup requested by the user)
c13    Prephenate dehydratase with ACT region                           the description of the InterPro entry
c14    Molecular Function:prephenate dehydratase activity (GO:0004664)  the GO (gene ontology) description for the InterPro entry 
====== ================================================================ ======================================================================

**Database updates**

Typically these take place 2-3 times a year. Please contact your Galaxy administrator to update the databases.

-----
Tools
-----

**PROSITE patterns**
 Some biologically significant amino acid patterns can be summarised in
 the form of regular expressions.
 ScanRegExp (by [e-mail]).

**PROSITE profiles**
 There are a number of protein families as well as functional or
 structural domains that cannot be detected using patterns due to their extreme
 sequence divergence, so the use of techniques based on weight matrices
 (also known as profiles) allows the detection of such proteins or domains.
 A profile is a table of position-specific amino acid weights and gap costs.
 The profile structure used in PROSITE is similar to but slightly more general
 (Bucher P. et al., 1996) than the one introduced by M. Gribskov and
 co-workers.
 pfscan from the Pftools package (by [e-mail]).

**PRINTS**
 The PRINTS database houses a collection of protein family fingerprints.
 These are groups of motifs that together are diagnostically more
 powerful than single motifs by making use of the biological context inherent in a
 multiple-motif method. The fingerprinting method arose from the need for
 a reliable technique for detecting members of large, highly divergent
 protein super-families.
 FingerPRINTScan (Scordis P. et al., 1999).

**PFAM**
 Pfam is a database of protein domain families. Pfam contains curated
 multiple sequence alignments for each family and corresponding hidden
 Markov models (HMMs) (Eddy S.R., 1998). 
 Profile hidden Markov models are statistical models of the primary
 structure consensus of a sequence family. The construction and use
 of Pfam is tightly tied to the HMMER software package.
 hmmpfam from the HMMER2.3.2 package (by Sean Eddy,
 [e-mail], http://hmmer.wustl.edu).

**PRODOM**
 ProDom is a database of protein domain families obtained by automated
 analysis of the SWISS-PROT and TrEMBL protein sequences. It is useful
 for analysing the domain arrangements of complex protein families and the
 homology relationships in modular proteins. ProDom families are built by
 an automated process based on a recursive use of PSI-BLAST homology
 searches.
 ProDomBlast3i.pl (by Emmanuel Courcelle [e-mail]
 and Yoann Beausse [e-mail])
 a wrapper on top of the Blast package (Altschul S.F. et al., 1997).

**SMART**
 SMART (a Simple Modular Architecture Research Tool) allows the
 identification and annotation of genetically mobile domains and the
 analysis of domain architectures. These domains are extensively
 annotated with respect to phyletic distributions, functional class, tertiary
 structures and functionally important residues. SMART alignments are
 optimised manually and following construction of corresponding hidden Markov models (HMMs).
 hmmpfam from the HMMER2.3.2 package (by Sean Eddy,
 [e-mail], http://hmmer.wustl.edu).

**TIGRFAMs**
 TIGRFAMs are a collection of protein families featuring curated multiple
 sequence alignments, Hidden Markov Models (HMMs) and associated
 information designed to support the automated functional identification
 of proteins by sequence homology. Classification by equivalog family
 (see below), where achievable, complements classification by orthologs,
 superfamily, domain or motif. It provides the information best suited
 for automatic assignment of specific functions to proteins from large
 scale genome sequencing projects.
 hmmpfam from the HMMER2.3.2 package (by Sean Eddy,
 [e-mail], http://hmmer.wustl.edu).

**PIR SuperFamily**
 PIR SuperFamily (PIRSF) is a classification system based on evolutionary
 relationship of whole proteins.
 hmmpfam from the HMMER2.3.2 package (by Sean Eddy,
 [e-mail], http://hmmer.wustl.edu).

**SUPERFAMILY**
 SUPERFAMILY is a library of profile hidden Markov models that represent
 all proteins of known structure, based on SCOP.
 hmmpfam/hmmsearch from the HMMER2.3.2 package (by Sean Eddy,
 [e-mail], http://hmmer.wustl.edu).
 Optionally, predictions for coiled-coil, signal peptide cleavage sites
 (SignalP v3) and TM helices (TMHMM v2) are supported (See the FAQs file for details).

**GENE3D**
 Gene3D is supplementary to the CATH database. This protein sequence database
 contains proteins from complete genomes which have been clustered into protein
 families and annotated with CATH domains, Pfam domains and functional
 information from KEGG, GO, COG, Affymetrix and STRINGS.
 hmmpfam from the HMM2.3.2 package (by Sean Eddy,
 [e-mail], http://hmmer.wustl.edu).

**PANTHER**
 The PANTHER (Protein ANalysis THrough Evolutionary Relationships)
 Classification System was designed to classify proteins (and their genes)
 in order to facilitate high-throughput analysis.
 hmmsearch from the HMM2.3.2 package (by Sean Eddy,
 [e-mail], http://hmmer.wustl.edu).
 and blastall from the Blast package (Altschul S.F. et al., 1997).

----------
References
----------

Zdobnov EM, Apweiler R (2001)
InterProScan an integration platform for the signature-recognition methods in InterPro.
Bioinformatics 17, 847-848.
http://dx.doi.org/10.1093/bioinformatics/17.9.847

Quevillon E, Silventoinen V, Pillai S, Harte N, Mulder N, Apweiler R, Lopez R (2005)
InterProScan: protein domains identifier.
Nucleic Acids Research 33 (Web Server issue), W116-W120.
http://dx.doi.org/10.1093/nar/gki442

Hunter S, Apweiler R, Attwood TK, Bairoch A, Bateman A, Binns D, Bork P, Das U, Daugherty L, Duquenne L, Finn RD, Gough J, Haft D, Hulo N, Kahn D, Kelly E, Laugraud A, Letunic I, Lonsdale D, Lopez R, Madera M, Maslen J, McAnulla C, McDowall J, Mistry J, Mitchell A, Mulder N, Natale D, Orengo C, Quinn AF, Selengut JD, Sigrist CJ, Thimma M, Thomas PD, Valentin F, Wilson D, Wu CH, Yeats C. (2009)
InterPro: the integrative protein signature database.
Nucleic Acids Research 37 (Database Issue), D224-228.
http://dx.doi.org/10.1093/nar/gkn785


This wrapper is available to install into other Galaxy Instances via the Galaxy Tool Shed at
http://toolshed.g2.bx.psu.edu/view/bgruening/interproscan


**Galaxy Wrapper Author**::

    *  Bjoern Gruening, Pharmaceutical Bioinformatics, University of Freiburg
    *  Konrad Paszkiewicz, Exeter Sequencing Service, University of Exeter

    </help>
</tool>