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<!DOCTYPE html>
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<head>
<title>PRIDE ProteoGenomics Pipeline</title>
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</head>
<body>
<div class="wrapper">
<div class="sidebar-wrapper">
<div class="profile-container">
<img class="img-circle" src="assets/images/profile.jpg" alt="" />
<h1 class="name">PRIDE</h1>
<h3 class="tagline">Protein Identification Database</h3>
</div><!--//profile-container-->
<div class="contact-container container-block">
<ul class="list-unstyled contact-list">
<li class="email"><i class="fa fa-envelope"></i><a href="mailto: [email protected]">[email protected]</a></li>
<li class="website"><i class="fa fa-globe"></i><a href="http://www.ebi.ac.uk/pride/archive" target="_blank">PRIDE Archive</a></li>
</ul>
</div>
<div class="contact-container container-block">
<h4 class="section-title">Content</h4>
<ul class="list-unstyled contact-list">
<li class="active"><i class="fa fa-angle-double-right"></i><a href="#proteogenomics">ProteoGenomics Pipeline</a></li>
<li><i class="fa fa-angle-double-right"></i><a href="#pia-section">Peptide Quality Assessment</a></li>
<li><i class="fa fa-angle-double-right"></i><a href="#pogo-section">Genome Coordinates Mapping</a></li>
</ul>
</div>
</div><!--//sidebar-wrapper-->
<div class="main-wrapper">
<section class="section summary-section">
<h2 class="section-title"><i class="fa fa-book"></i>Dataset</h2>
<div class="upper-row">
<h3 class="job-title" id="title">Title: {{dataset-title}}</h3>
<h3 class="job-title" id="accession">ProteomeXChange Accession: <a href="{{pride-link}}">{{dataset-accession}}</a></h3>
</div><!--//upper-row-->
<div class="summary">
<p>{{dataset-description}}</p>
</div><!--//summary-->
</section><!--//section-->
<section class="section summary-section">
<h2 class="section-title"><i class="fa fa-book"></i>Methods</h2>
<div class="summary">
<p>Mass spectrometry (MS) based proteomics and next-generation sequencing technologies have improved our understanding of the crosstalk between genome, transcriptome, and proteome
and contribute to a better understanding of the variations between healthy and disease states. Substantial advances in MS technologies enable more complete identification
and quantification of proteomes, making these data more comparable with transcriptomics. However, most of the omics studies are performed in independent groups and most
of the repositories and resources only stores data for a specific omics type: genomics or proteomics. Recently, integrative analysis of quantitative measurements from
genomic and proteomic studies have identified novel insights into gene expression regulation, cell signaling, and disease.
</p>
<p>The <strong>PRIDE Proteogenomics Pipeline</strong> has the goal of mapping each Complete Submission in <a href="http://www.ebi.ac.uk/pride/">PRIDE Archive database</a> to ENSEMBL genomes
coordinates (<strong>Figure 1</strong>). In the flowing sections, we will explain in details all the steps involve in the Proteogenomics Mapping Pipeline.
</p>
<img src="assets/images/proteogenomics.png" alt="" /></br></br>
<p>
<strong>Figure 1</strong>: The PRIDE Proteogenomics Pipeline enables the representation of each Complete Submission into the ENSEMBL/UCSC Browsers. When the user made a
<a href="http://www.proteomexchange.org/submission/index.html">Complete Submission</a> containing the Result and Peaks list files in a standard file format;
the (2) Proteogenomics Mapping Pipeline map each high-quality peptide to their corresponding genome coordinates.
Finally, a <a href="https://genome.ucsc.edu/goldenpath/help/hgTrackHubHelp.html">Track Hub</a> is generated and published in the <a href="https://www.trackhubregistry.org/">ENSEMBL TrackHub Registry</a>
</p>
</div><!--//summary-->
</section><!--//section-->
<section class="section summary-section">
<h2 class="section-title" id="proteogenomics"><i class="fa fa-sitemap"></i>PRIDE Proteogenomics Pipeline</h2>
<p>
The process to map the different MS-based proteomics evidences to the corresponding genome coordinates can be classified in multiple steps:
(i) quality assessment of the PSMS/Peptide Evidences (ii) Mapping of the corresponding high-quality evidences to genome coordinates; (iii) Generation and publication of the resulted
Track Hubs in a public Repository (<strong>Figure 2</strong>).
</p>
<img src="assets/images/proteogeonomics_mapping.png"/></br></br>
<div class="item">
<div class="meta">
<div class="upper-row">
<h3 class="job-title" id="pia-section">Quality assessment of peptide evidences</h3>
</div><!--//upper-row-->
<div class="company">Protein Inference Toolkit</div>
</div><!--//meta-->
<div class="details" style="margin-bottom: 2em;">
<p>Each Complete Submission in PRIDE is a combination of <strong>Result Files</strong> (containing the PSMs/Peptides) and <strong>Peaks lists</strong> files.
This combination is organized into <strong>Assays</strong> with the corresponding metadata associated (e.g tissue, taxonomy, cell type). In order to assess the
quality of the corresponding PSMs/Peptides, the <a href="https://github.com/mpc-bioinformatics/pia">Protein Inference Toolkit (PIA)</a> has been used <a href="#pia">[1]</a>. In summary,
PIA supports the majority of established search engines and scoring models. It enables to translate those scoring models into a Global FDR score and filter <strong>1% FDR</strong> at PSM and
<strong>1% FDR</strong> Peptide levels.
</p>
</div><!--//details-->
</div><!--//item-->
<div class="item">
<div class="meta">
<div class="upper-row">
<h3 class="job-title" id="pogo-section">Mapping the peptide Evidences to Genome Coordinates</h3>
</div><!--//upper-row-->
<div class="company">PoGo Mapping Tool</div>
</div><!--//meta-->
<div class="details" style="margin-bottom: 2em;">
<p>The <a href="https://github.com/PRIDE-Toolsuite/PoGo/">PoGo tool</a> is used to map the resulted list of Peptides to the corresponding Genome Coordinates <a href="#pogo">[2]</a>. In summary, PoGo leverages the annotated protein coding sequences (CDS)
together with a reference protein sequence database (protein-DB) to map peptides to their genomic loci (<strong>Figure 3</strong>).
</p>
<img src="assets/images/pogo.png">
<br>
<br>
<p>
<strong>Figure 4</strong>: (A) Transcript annotation (GTF) and translated protein sequences (FASTA) form the reference input for PoGo.
In addition, the pogo input file containing the peptide sequences, experiment and the quantitative information should be provided.
(B) Annotated protein coding transcripts in GTF format and respective translated protein sequences in FASTA format are integrated by
PoGo through intermediate coordinates (turquoise), representing the exonic structure of the transcript within the protein. (C) Peptides,
identified through searching mass spectrometry data against the protein sequence database, are mapped against the proteins. (D) Example mappings
of PoGo for the overlapping repeat peptide VPEPGCTKVPEPGCTK in a genome browser (0 mismatches). Application of PoGo allowing for up to two mismatches
results in identification of two additional repeats (1 and 2 mismatches, red boxes). The additional mappings of the initial peptide sequence
were validated through peptides of the exact sequence identified in the same mass spectrometry experiment (validation). Leucine (L) and isoleucine
(I) are substituted through their common single-letter code ‘‘J.’’ (E) Comparison of different peptide-to-genome mapping tools with regard to
reference sequence type, integration into frameworks, support of online and offline genome browsers (blue). Additional features (orange)
indicate the superior performance of PoGo over other tools.
</p>
</div><!--//details-->
</div><!--//item-->
<div class="item">
<div class="meta">
<div class="upper-row">
<h3 class="job-title">Track Hub Creation</h3>
</div><!--//upper-row-->
<div class="company">Track Hub creator</div>
</div><!--//meta-->
<div class="details">
<p><a href="https://github.com/Proteogenomics/trackhub-creator">The Proteogenomics Track Hub creator</a> provides a set of functionalities to convert the list of peptides evidences
into public <strong>Track Hub</strong> into the ENSEMBL Track Hub registry. Amount other functionalities it enables to download the latest releases of ENSEMBL protein
and coordinates data files for specific taxonomies. </p>
</div><!--//details-->
</div><!--//item-->
</section><!--//section-->
<section class="section projects-section">
<h2 class="section-title"><i class="fa fa-quote-left"></i>Cite Us: </h2>
<div class="intro">
<p>If you use this pipeline, please cite us: </p>
</div><!--//intro-->
<div class="item">
<span class="project-title">
Vizcaíno JA, Csordas A, del-Toro N, Dianes JA, Griss J, Lavidas I, Mayer G, Perez-Riverol Y, Reisinger F, Ternent T, Xu QW, Wang R, Hermjakob H (2016).
2016 update of the PRIDE database and related tools. Nucleic Acids Res 44(D1): D447-D456 (PubMed ID: <a href="http://europepmc.org/abstract/MED/26527722">26527722</a>).
</span>
</div><!--//item-->
</section><!--//section-->
<section class="section projects-section">
<h2 class="section-title"><i class="fa fa-quote-left"></i>{{publication-title}}: </h2>
<div class="item">
<span class="project-title">
{{publication}}
</span>
</div><!--//item-->
</section><!--//section-->
<section class="section projects-section">
<h2 class="section-title"><i class="fa fa-angle-double-right"></i>References</h2>
<div class="item">
<span class="project-title" id="pia">
[1] - Uszkoreit J, Maerkens A, Perez-Riverol Y, Meyer HE, Marcus K, Stephan C, Kohlbacher O, Eisenacher M. PIA: An intuitive protein inference engine with a
web-based user interface. Journal of proteome research. 2015 Jun 10;14(7):2988-97. (PubMed ID: <a href="http://europepmc.org/abstract/MED/25938255">25938255</a>)
</span>
</div><!--//item-->
<div class="item">
<span class="project-title" id="pogo">
[2] - Schlaffner CN, Pirklbauer GJ, Bender A, Choudhary JS. Fast, Quantitative and Variant Enabled Mapping of Peptides to Genomes. Cell systems. 2017 Aug 23;5(2):152-6.
(PubMed ID: <a href="http://europepmc.org/abstract/MED/28837811">28837811</a>)
</span>
</div><!--//item-->
</section>
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