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<!DOCTYPE html>
<!--[if lt IE 7]> <html class="lt-ie9 lt-ie8 lt-ie7"> <![endif]-->
<!--[if IE 7]> <html class="lt-ie9 lt-ie8"> <![endif]-->
<!--[if IE 8]> <html class="lt-ie9"> <![endif]-->
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<head>
<title>fathmm - Rank nsSNPs According to Specific Disease Concepts</title>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta name="description" content="Analyze dbSNP/Protein Missense Variants">
<meta name="keywords" content="Disease-Specific Predictions, Disease-Specific Ranking, Disease Concepts, Rank Disease Mutations, Missense Mutation, Amino Acid Substitutions, Hidden Markov Models, HMMs, Single Nucleotide Polymorphisms, SNPs, Non Synonymous Mutation, nsSNPs, fathmm">
<meta name="author" content="Hashem A. Shihab">
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<h2>Rank nsSNPs According to Specific Disease Concepts</h2>
</div>
<ul class="nav nav-tabs" id="myTab">
<li id="new-tab" class="active">
<a href="#new" onclick="javascript: remove();" data-toggle="tab">New Submission</a>
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<div class="span12">
<form class="form-horizontal" id="myForm" name="myForm" action="./cgi-bin/submit.cgi" method="post" enctype="multipart/form-data">
<legend><h3>Enter Your Mutations:</h3></legend>
<div class="row-fluid">
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<label class="control-label" for="weighted">Disease Concept</label>
<div class="controls">
<select id="weighted" name="weighted" class="span11">
<option value="BLOOD" selected>Blood</option>
<option value="BLOOD_COAGULATION">Blood Coagulation</option>
<option value="DEVELOPMENTAL">Developmental</option>
<option value="DIGESTIVE">Digestive</option>
<option value="EAR_NOSE_THROAT">Ear Nose & Throat</option>
<option value="ENDOCRINE">Endocrine</option>
<option value="EYE">Eye</option>
<option value="GENITOURINARY">Genitourinary</option>
<option value="HEART">Heart</option>
<option value="IMMUNE">Immune</option>
<option value="METABOLIC">Metabolic</option>
<option value="MUSCULOSKELETAL">Musculoskeletal</option>
<option value="NERVOUS_SYSTEM">Nervous System</option>
<option value="PSYCHIATRIC">Psychiatric</option>
<option value="REPRODUCTIVE">Reproductive</option>
<option value="RESPIRATORY">Respiratory</option>
<option value="SKIN">Skin</option>
</select>
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<option value="DO">Disease Ontology</option>
<option value="GO">Gene Ontology</option>
<option value="HP" selected>Human Phenotype Ontology</option>
<option value="MP">Mouse Phenotype Ontology</option>
<option value="WP">Worm Phenotype Ontology</option>
<option value="YP">Yeast Phenotype Ontology</option>
<option value="FP">Fly Phenotype Ontology</option>
<option value="FA">Fly Anatomy Ontology</option>
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<li><a href="#overview"><i class="icon-chevron-right"></i> Overview</a></li>
<li><a href="#format"><i class="icon-chevron-right"></i> Input Format</a></li>
<li><a href="#format_batch"><i class="icon-chevron-right"></i> Batch Submission</a></li>
<li><a href="#cutoff"><i class="icon-chevron-right"></i> Prediction Score</a></li>
<li><a href="#vcf"><i class="icon-chevron-right"></i> Annotating VCF's</a></li>
</ul>
</div>
<div class="span9">
<section id="overview">
<h1>Overview:</h1>
<br />
<p>
Our disease-specific algortihm is is capable of <b>ranking protein missense mutations according to seventeen disease concepts</b> by combining sequence
conservation within hidden Markov models (HMMs), representing the alignment of homologous sequences and conserved protein domains, with "pathogenicity weights",
representing the overall tolerance of the corresponding model to disease concepts, e.g. musculoskeletal and/or metabolic disease.
<br /><br />
For more information, please refer to the following publications:
<br /><br />
Shihab HA, Gough J, Mort M, Cooper DN, Day INM, Gaunt, TR.
A Method for Ranking Non-Synonymous Single Nucleotide Polymorphisms based on Disease Concepts
(submitted)
<br /><br />
Shihab HA, Gough J, Cooper DN, Stenson PD, Barker GLA, Edwards KJ, Day INM, Gaunt, TR. (2013). Predicting the Functional, Molecular and Phenotypic
Consequences of Amino Acid Substitutions using Hidden Markov Models. <i>Hum. Mutat.</i>, <b>34</b>:57-65
<a href="http://www.ncbi.nlm.nih.gov/pubmed/23033316"><img src="./img/pubmed.png" alt="fathmm Paper"></a>
</p>
<br />
<a href='./disease.html#top'>Back to Top ...</a>
</section>
<br />
<section id="format">
<h1>Input Format:</h1>
<br />
<p>
Our software accepts one of the following formats (see <a href="./about.html#vcf">here</a> for annotating VCF files):
<br /><br />
<ul>
<li>
<code><protein> <substitution></code>
</li>
<li>
<code>dbSNP rs identifiers</code>
</li>
</ul>
<br />
In the above, <code><protein></code> is the protein identifier and <code><substitution></code> is the amino acid substitution in the conventional one
letter format. At present, <b>our server accepts SwissProt/TrEMBL, RefSeq and Ensembl protein identifiers</b>, e.g.:
<br /><br />
<pre>
P43026 L441P
</pre>
or:
<br /><br />
<pre>
rs137854462
</pre>
</p>
<br />
<a href='./disease.html#top'>Back to Top ...</a>
</section>
<br />
<section id="format_batch">
<h1>Batch Submission:</h1>
<br />
<p>
<b>
It is possible to submit multiple amino acid substitutions as a 'Batch Submission' via our server</b>. Here, all amino acid substitutions for a protein can be
entered on a single line and should be separated by a comma, e.g:
<br /><br />
<pre>
P43026 L441P
ENSP00000325527 N548I,E1073K,C2307S
</pre>
<br />
<b>Note: this option is not available when analysing dbSNP rs identifiers</b>.
</p>
<br />
<a href='./disease.html#top'>Back to Top ...</a>
</section>
<br />
<section id="cutoff">
<h1>Prediction Score:</h1>
<br />
<p>
Our disease-specific predictions are still experimental; therefore, we have not defined clear prediction thresholds for identifying whether a mutation
is associated with your disease of interest or not. However, predictions scoring less than zero indicate there is a chance the mutation is associated
with your disease of interest, with lower scores indicating increased confidence in the association.
</p>
<br />
<a href='./cancer.html#top'>Back to Top ...</a>
</section>
<br />
<section id="vcf">
<h1>VCF Annotation:</h1>
<br />
<p>
Unfortunately, due to disk space constraints, we are unable to annotate Variant Call Format (VCF) files on your behalf. However, the consequences of all VCF variants
can be derived using the <b><a href="http://www.ensembl.org/info/docs/variation/vep/index.html">Ensembl Variant Effect Predictor (VEP)</a></b>.
Once annotated, the following script <b><a href="./parseVCF.py">(available here)</a></b> is capable of parsing these annotations and will provide you with a list of protein
consequences which can then be used as input into our server/software.
<br /><br />
Additional help on using our script is available by typing the following command:
<br /><br />
<pre>python parseVCF.py --help</pre>
</p>
<br />
<a href='./disease.html#top'>Back to Top ...</a>
</section>
</div>
</div>
</div>
</div>
<hr>
<footer>
<p>
If you have found this resource useful, please cite the following work:
<br />
<a href="http://www.ncbi.nlm.nih.gov/pubmed/23033316">Shihab HA, Gough J, Cooper DN, Stenson PD, Barker GLA, Edwards KJ, Day INM, Gaunt, TR. (2013). Predicting the Functional, Molecular and Phenotypic Consequences of Amino Acid Substitutions using Hidden Markov Models. Hum. Mutat., <b>34</b>, 57-65 </a>
</p>
<p>
We welcome any comments and/or suggestions that you may have regarding our software and server - please send an email directly to [email protected]
</p>
</footer>
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