➔ Poster
AuthorsLien Nguyen 1* , Maud Lacombe 1 , Sandra Dérozier 2 , Lisa Perus 1 , Olivier Rué 2 , Florence Combes 1 , Christophe Caron 2 , Virginie Brun 1 , Valentin Loux 2 , Yves Vandenbrouck 1
1 : Institut de Biosciences et Biotechnologies de Grenoble (BIG), Université de Grenoble, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA) - Grenoble, Centre National de la Recherche Scientifique : FR3425
17, rue des Martyrs 38054 Grenoble cedex 9 - France
2 : Unité Mathématiques et Informatique Appliquées du Génome à l'Environnement (MAIAGE), Institut National de la Recherche Agronomique, Université Paris-Saclay
Domaine de Vilvert 78350 Jouy en Josas Cedex - France
* : Corresponding author
Abstract
Introduction
Galaxy is a well-maintained software platform providing simple interfaces to tools and online access to computational resources in a transparent way. Build upon Galaxy, the ProteoRE (Proteomics Research Environment) project is a joint effort between the French proteomics infrastructure (ProFI) and the French bioinformatics Institute (IFB). Its primary aim is to centrally provide the proteomics community with an online research service enabling biologists/clinicians without programming expertise to explore their proteomics data through the Web in a reproducible manner.
Methods
Starting from proteome software output files (MaxQuant, Proline), various components have been designed driven by expertise and needs from our collaborators. These modules embedded into Galaxy components have been implemented either by reusing tools (from the Galaxy Tool Shed) or by wrapping Bioconductor packages and external code, and further beta-tested.
Results
We have set up two use cases scenarios derived from our own research projects to interpret a large proteins identification list and to entail selection of biomarkers candidates based on biochemical criteria. A first ProteoRE instance is now deployed and currently in beta-testing before public release in early 2018.
Conclusions
While Galaxy-based tools offers services for primary proteomics data analyses (e.g. MS data conversion, protein database tools, search algorithms), tools focusing on downstream analysis are still lacking. The ProteoRE platform proposes to fill this gap with the hope of promoting proteomics data in the Life Science community.
