The bioinformatics / biostatistics platform support the lab research teams as well as the scientific community of the Medicine and Sciences faculties within the framework of cross-functional collaborations. Its areas of expertise mainly focus on:
- omics data analysis (transcriptomes, proteomes, methylomes, epigenomes, metabolomes, exomes, genomes),
- multi-omics, systems biology and integrative genomics,
- automatic & state-of-the-art pipelines,
- population genetics,
- analysis of flow and mass cytometry data,
- single-cell RNA-sequencing transcriptomics.
Pipelines, tools and workflows are specific to each omics, the acquisition technologies (chip, NGS, mass spectrometry) and their limits, and data origin (experimental, public datasets, meta-analyses). We provide a wide range of statistical/supervised and unsupervised approaches.
Contact
Team
Sébastien Hergalant
Engineer (INSERM), manager
Ghislain Fiévet
Engineer, development on projects (MIGB)
Romain Piucco
PhD student / Engineer (MIGB)
Ramia Safar
Engineer (UL), functional genomics platform
Pierre Rouyer
Technician (UL), quality controls, pipelines
The team provides support to researchers in developing their projects:
- by participating in grant applications, writing methods and suitable bioinformatics / statistical analyses,
- by advising on experimental designs,
- by supplying the necessary material resources and skills,
- by producing tools, protocols, reports and reproducible results.
TEACHING
We supervise and train students of all grades starting from L3, whether biologists, computer scientists, or medical / pharm students. We also welcome PhD and post-doc fellows.
We organize courses on omics analyses, NGS data analysis, quality controls on big data, R language (from beginner to advanced levels), biostatistics, bash interpreter (command lines, complex handlings), system administration and linux (scripting, automation).
CORE FACILITIES
The high-performance computing cluster revolves around an infrastructure of servers and systems supplying the bioinformatics platform and team with high-availibility, shared workspaces.
The HPC cluster includes 5 linux servers and 6 SAN modular & block storage bays, with more than 200 computing cores, 5 TB of memory and 300 TB of data. The storage facilities are shared and part of the lab BioDataCenter.
