Section: Partnerships and Cooperations
PIA France Génomique: National funding from “Investissements d'Avenir” (call Infrastructures en Biologie-Santé). France Génomique is a shared infrastructure, whose goal is to support sequencing, genotyping and associated computational analysis, and increase French capacities in genome and bioinformatics data analysis. It gathers 9 sequencing and 8 bioinformatics platforms. Within this consortium, we are responsible for the workpackage devoted to the computational analysis of sRNA-seq data, in coordination with the bioinformatics platform of Génopole Toulouse-Midi-Pyrénées
ADT Vidjil (2015–2017): The purpose of this ADT is to strengthen Vidjil development and to ensure a better diffusion of the software by easing the installation, administration and usability. This will make the software well suited for a daily clinical use. The software is already used in test on our own web server (more than 1,000 samples processed by now). Our goal is that several labs use Vidjil on a daily basis by the end of the ADT, and that they all have their own Vidjil server.
PEPS Gen-CoV: Global bioinformatics analysis of coronavirus strain 229E in hospital outbreak. The goal of this PEPS is to provide with a better characterization of coronavirus infections and to understand underlying mecanisms that lead to the high diversity of coronaviruses. To achieve this goal, we will sequence and analyze a number of coronavirus 229E genomes in order to characterize their diversity, identify features that influence pathogenicity and propose a model of evolution. All those results will be correlated with epidemiologic data thanks to a partnership with Lille hospital.
PEPS JCJC: Frugal algorithms for third-generation DNA sequencing. The goal of this PEPS is to develop lightweight algorithms and data structures for the analysis of third-generation sequencing data. Among third-generation technologies, the MinION sequencer is a new, portable USB device that can perform DNA sequencing using only common lab equipment and a laptop computer. However, analysis of the data produced by the MinION can only be carried by uploading data to a cloud server. Indeed, all algorithms and data structures that are currently known require large computational resources to process such data. This is unfortunate for at least two reasons: analysis of the data now takes more time than its production, and confidential data needs to be processed on potentially insecure cloud servers. We seek to design methods that would enable analysis of sequenced data on the same machine as the one that performed sequencing.