Genomic and transcriptomic platform
The genomic and transcriptomic platform was set up in 2017 to coordinate NGS CPTP analyses coming from RNAseq, ChIPseq and ATACseq experiments. Through its expertise and advanced technological facilities the platform respond to the growing bioinformatic and biostatistic needs of the CPTP research teams.
DRY : Manuel LEBEURRIER (IE Inserm)
WET : Adeline Chaubet (IE Inserm)
Genomic and transcriptomic platform services are designed for biologists and bioinformaticians. The analyses concern mostly RNAseq, ChIPseq and ATACseq experiments. Specific pipelines were developed and deployed on the Genotoul. The platform also carries out analyses regarding variant calling (SNP / INDEL / CNV), gene fusion detections, linkage and association analyses.
The platform aims to diffuse its expertise through regular trainings on bioinformatics, biostatistics and computing fields. These are the trainings that have already been performed :
- NGS: Yesterday to tomorow sequencing generation story
- RNAseq analysis: theory and concepts behind differentially expressed genes
- Galaxy initiation: differentially expressed gene analysis
- Introduction to command lines and Linux OS
- Discovery of public databases
- Gene Set Enrichment Analysis
- Single-Cell RNAseq
- 10X genomics and their tools
- R initiation
- Test theory with R
- DESEQ2 package: differentially expressed gene analysis
- Mixomics package: focus on PCA and PLSDA
- ggPubR package: publication ready figures
- FlowAI package : automatic or interactive quality control on FCS data
- FlowClean package : automated identification and removal of fluorescence anomalies in flow cytometry
- Clustering and classification: from k-means to t-SNE
In order to respond to the teams needs two operating methods have been adopted:
- The client fills a project sheet to describe briefly the context, the scientific issue and the planned study design.
- The platform suggests the experimental design and methodologies according to the biological question. Technical details are filled into a technical sheet after agreement between the client and the bioinformatician.
- The platform team provides an analysis sheet describing all the steps needed to transform raw data into deliverables. Starting date, time needed and deliverables are specified to the client. The quote is send to the client for signature.
- A quote is provided by the platform team. Once the signed quote is received the project will be added to the analysis schedule.
- The “wet” part of the project is done by the platform staff in coordination with members of the client researcher team. A library sheet for quality control is filled in and sent to the client and the bioinformatician.
- After sequencing, the bioinformatic analysis is performed and the deliverables are transferred to the client. A result delivery confirmation is signed by the client and sent back to the platform.
With training performed by the genomic plateform, a member of the demanding team will be trained to the common bioinformatic analyses. This person will then be in charge of the future analyses. This responsibility includes the necessity to sending the sheets (project, technical and library) and the quality control to the platform. In this way, the platform will follow the project evolution in order to validate the results obtained in the different key steps of the analysis.
Platform developments are stored in the GitHub repository : CPTPGenomicTranscriptomic.
- Gene-Attributes : A shiny app that obtains Ensembl gene ID, gene names, the coordinates and description of an input file using biomaRt package.
- Gene-Attributes-Multiple : A shiny app that obtains Ensembl gene ID, gene names, the coordinates and description of multiple input files using biomaRt package.
- FlowAIAll : Clean cytometry data using FlowAI R package through a new Rshiny interface
- ShinyFlowClean : Clean cytometry data using FlowClean R package through a Rshiny interface.
- shinyheatmap : Web application for enormous biological heatmaps.
- cytofkit2 : A shiny app to analyzed flow cytometry data using tSNE and Rphenograph.
- OpenCyto : Automated gating data using OpenCyto R package through a new Rshiny interface.
- iSEE : The interactive Summarized Experiment Explorer
- 3DtSNE : A Shiny app to explore t-SNE representation.
- shinyCircos : an R/shiny application for creation of Circos plot interactively.
- Anne Dejean (CR INSERM)
- Véronique Adoue (CR CNRS)
- José Enrique Méjia (CR INSERM)
- Nicolas Blanchard (CR1 Inserm)
- Olivier Joffre (MCU UPS)
Molecular Therapy, Forthcoming.