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<?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>
>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 ``<seqname>.ps''
(in PostScript) and ``<seqname>.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 >0.5 the residue is predicted as glycosy‐
lated; the higher the score the more confident the prediction. If the G-score is < 0.5 but the I-score >0.5
and there are no predicted neighbouring sites (distance <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>
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