The ReproGenomics Viewer: a multi-omics and cross-species resource compatible with single-cell studies for the reproductive science community

Thomas Darde 1 Estelle Lecluze 1 Aurélie Lardenois 1 Isabelle Stévant 2 Nathan Alary 1 Frank Tüttelmann 3 Olivier Collin 4, 5 Serge Nef 2 Bernard Jégou 1 Antoine Rolland 1 Fréderic Chalmel 1, *
* Corresponding author
4 Plateforme bioinformatique GenOuest [Rennes]
UR1 - Université de Rennes 1, Plateforme Génomique Santé Biogenouest®, Inria Rennes – Bretagne Atlantique , IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires
Abstract : Motivation: Recent advances in transcriptomics have enabled unprecedented insight into gene expression analysis at a single-cell resolution. While it is anticipated that the number of publications based on such technologies will increase in the next decade, there is currently no public resource to centralize and enable scientists to explore single-cell datasets published in the field of reproductive biology.Results: Here, we present a major update of the ReproGenomics Viewer (RGV), a cross-species and cross-technology web-based resource of manually-curated sequencing datasets related to reproduction. The redesign of RGV's architecture is accompanied by significant growth of the database content including several landmark single-cell RNA sequencing datasets. The implementation of additional tools enables users to visualize and browse the complex, high-dimensional data now being generated in the reproductive field.Availability and implementation: The ReproGenomics Viewer resource is freely accessible at http://rgv.genouest.org. The website is implemented in Python, JavaScript, and MongoDB, and is compatible with all major browsers. Source codes can be downloaded from https://github.com/fchalmel/RGV.
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Thomas Darde, Estelle Lecluze, Aurélie Lardenois, Isabelle Stévant, Nathan Alary, et al.. The ReproGenomics Viewer: a multi-omics and cross-species resource compatible with single-cell studies for the reproductive science community. Bioinformatics, Oxford University Press (OUP), 2019, 35 (17), pp.3133-3139. ⟨10.1093/bioinformatics/btz047⟩. ⟨hal-02015545⟩

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