/var/lib/mobyle/programs/netOglyc.xml

<?xml version='1.0' encoding='UTF-8'?>
<!-- XML Authors: Corinne Maufrais, Nicolas Joly and Bertrand Neron,             -->
<!-- 'Biological Software and Databases' Group, Institut Pasteur, Paris.         -->
<!-- Distributed under LGPLv2 License. Please refer to the COPYING.LIB document. -->
<program>
  <head>
    <name>netOglyc</name>
    <version>3.1</version>
    <xi:include xmlns:xi="http://www.w3.org/2001/XInclude" href="Entities/cbs_package.xml"/>
    <doc>
      <title>netOglyc</title>
      <description>
        <text lang="en">predict O-glycosylation sites in proteins.</text>
      </description>
      <sourcelink>http://www.cbs.dtu.dk/cgi-bin/nph-sw_request?netNglyc</sourcelink>
      <authors> Karin Julenius, kj@cbs.dtu.dk</authors>
      <reference>Prediction,  conservation  analysis and structural characterization of 
      mammalian mucin-type O-glycosylation sites.
       K. Julenius, A. Moelgaard, R. Gupta and S. Brunak.
       Glycobiology, 15:153-164, 2005.
      </reference>
      <doclink>http://www.cbs.dtu.dk/services/NetOGlyc/</doclink>
      <doclink>http://www.cbs.dtu.dk/databases/OGLYCBASE/</doclink> 
      <comment>
        <text lang="en">The NetOglyc server produces neural network predictions of mucin type GalNAc O-glycosylation sites in mammalian proteins.</text>
      </comment>
    </doc>
    <category>sequence:protein:motifs</category>
    <category>sequence:protein:pattern</category>
    <category>sequence:protein:profiles</category>
  </head>
  <parameters>
     
    <parameter ishidden="1" iscommand="1">
      <name>netoglyc</name>
      <type>
        <datatype>
          <class>String</class>
        </datatype>
      </type>
      <format>
        <code proglang="perl">" netOglyc "</code>
        <code proglang="python">" netOglyc "</code>
      </format>
    </parameter>
   
    <parameter ismandatory="1" issimple="1" ismaininput="1">
      <name>sequence</name>
      <prompt lang="en">Input Sequence</prompt>
      <type>
        <datatype>
          <class>Sequence</class>
        </datatype>
        <dataFormat>FASTA</dataFormat>
      </type>
      <format>
        <code proglang="python">" " + str( value )</code>
      </format>
      <argpos>50</argpos>
      <example>
&gt;LEUK_RAT P13838 LEUKOSIALIN PRECURSOR (LEUCOCYTE SIALOGLYCOPROTEIN) (SIALOPHORIN) (CD43) (W3/13 ANTIGEN).
WAQVVSQENLPNTMTMLPFTPNSESPSTSEALSTYSSIATVPVTEDPKESISPWGQTTAP
ASSIPLGTPELSSFFFTSAGASGNTPVPELTTSQEVSTEASLVLFPKSSGVASDPPVTIT
NPATSSAVASTSLETFKGTSAPPVTVTSSTMTSGPFVATTVSSETSGPPVTMATGSLGPS
KETHGLSATIATSSGESSSVAGGTPVFSTKISTTSTPNPITTVPPRPGSSGMLLVSMLIA
LTVVLVLVALLLLWRQRQKRRTGALTLSRGGKRNGTVDAWAGPARVPDEEATTASGSGGN
KSSGAPETDGSGQRPTLTTFFSRRKSRQGSVALEELKPGTGPNLKGEEEPLVGSEDEAVE
TPTSDGPQAKDGAAPQSL
      </example>
    </parameter>
    
    <parameter>
      <name>signal_peptide</name>
      <prompt lang="en">Run signalp on the input sequences (-sp).</prompt>
      <type>
        <datatype>
          <class>Boolean</class>
        </datatype>
      </type>
      <vdef>
        <value>0</value>
      </vdef>
      <format>
        <code proglang="perl">( $value ) ? "-sp ": ""</code>
        <code proglang="python">( "","-sp ")[ bool( value ) ]</code>
      </format>
      <argpos>10</argpos>
      <comment>
         <text lang="en"> Non-secretory  proteins  are unlikely to be glycosylated in vivo even though they contain potential motifs.
       Therefore, it is possible to run the signal peptide predictor signalp on the input sequences</text>
      </comment>
    </parameter>
    
    <parameter >
      <name>graphics</name>
      <prompt lang="en">generate graphics (-g).</prompt>
      <type>
        <datatype>
          <class>Boolean</class>
        </datatype>
      </type>
      <vdef>
        <value>0</value>
      </vdef>
      <format>
        <code proglang="perl">( $value )? "-g " : ""</code>
        <code proglang="python">( "" , "-g " )[ bool( value ) ]</code>
      </format>
      <comment>
        <text lang="en"> Generate graphics, plotting the G-score against the position in the sequence
              of each serine and threonine residue. The I-score is plotted instead for the
              residues  where  it  decides  the  final answer. For each input sequence two
              files will be produced  ``&lt;seqname&gt;.ps''
              (in PostScript) and ``&lt;seqname&gt;.gif'' (in GIF).</text>
      </comment>
      <argpos>20</argpos>
    </parameter>  
    
    <parameter isstdout="1">
      <name>results</name>
      <prompt lang="en">netOglyc report</prompt>
      <type>
        <datatype>
          <superclass>Report</superclass>
          <class>NetOGlyc</class>
        </datatype>
      </type>
      <filenames>
        <code proglang="perl">"netOglyc.out"</code>
        <code proglang="python">"netOglyc.out"</code>
      </filenames>
      <comment>
      <div xmlns="http://www.w3.org/1999/xhtml">
        <p> Each input sequence is displayed with the predicted sites
       indicated,  labelled  with  ``S''  and ``T'' for serine and threonine, respectively. The signal peptide (if
       predicted) is labelled with ``_''. The details of the prediction for each serine and threonine residue  are
       then shown in a table. The columns are:</p>
       <ul>
           <li>sequence name</li>
           <li>residue (S or T)</li>
           <li>position in the sequence</li>
           <li>G-score (general predictor)</li>
           <li>I-score (isolated site predictor)</li>
           <li>final answer (S/T for predicted sites, otherwise `.')</li>
           <li>comment</li>
        </ul>   
        <p>The  final  answer  is  calculated as follows.  If the G-score is &gt;0.5 the residue is predicted as glycosy‐
       lated; the higher the score the more confident the prediction. If the G-score is &lt; 0.5 but the I-score  &gt;0.5
       and there are no predicted neighbouring sites (distance &lt;10 residues) the residue is also predicted as gly‐
       cosylated.</p>
       <p>If a residue in a predicted signal peptide is predicted as glycosylated there is a warning in  the  comment
       field.
        </p>
        </div>
      </comment>
    </parameter> 
    
    <parameter isout="1">
      <name>postscript</name>
      <prompt lang="en">graphic in Postsricpt</prompt>
      <type>
        <datatype>
          <superclass>Binary</superclass>
          <class>NetOGlyc_graphic</class>
        </datatype>
        <dataFormat>PostScript</dataFormat>
      </type>
      <precond>
        <code proglang="perl">graphics</code>
        <code proglang="python">graphics</code>
      </precond>
      <filenames>
        <code proglang="perl">"*.ps"</code>
        <code proglang="python">"*.ps"</code>
      </filenames>
      <comment>
        <text lang="en"> plotting the G-score against the position in the  sequence  of  each  serine  and
              threonine  residue.  The  I-score  is  plotted  instead  for the residues where it decides the final
              answer.
        </text>
      </comment>
    </parameter> 
    
    <parameter isout="1">
      <name>gif</name>
      <prompt lang="en">graphic in GIF</prompt>
      <type>
        <datatype>
          <superclass>Binary</superclass>
          <class>NetOGlyc_graphic</class>
        </datatype>
        <dataFormat>GIF</dataFormat>
      </type>
      <precond>
        <code proglang="perl">graphics</code>
        <code proglang="python">graphics</code>
      </precond>
      <filenames>
        <code proglang="perl">"*.gif"</code>
        <code proglang="python">"*.gif"</code>
      </filenames>
      <comment>
        <text lang="en"> plotting the G-score against the position in the  sequence  of  each  serine  and
              threonine  residue.  The  I-score  is  plotted  instead  for the residues where it decides the final
              answer.
        </text>
      </comment>
    </parameter> 
    
    
  </parameters>
</program>
mobyle-programs 5.1.2-1 / var / lib / mobyle / programs / netOglyc.xml
