DDisc
DDisc - Double-dipping in single-cell RNAseq (2021-2024).
[formerly called: PoCI-sc for “Post clustering inference for single cell RNAseq”]
The methods classically used to analyze single-cell RNA-sequencing data suffer from a selection bias. Indeed, the clustering of cells into subgroups and the statistical tests for finding marker genes that differentiate these subgroups are generally performed on the same data. The goal of this project is to develop methods that (i) provide valid statistical guarantees and (ii) can be easily used and interpreted by biologists. These methodological developments will be implemented and made available via an R package, and a graphical user interface.
This interdisciplinary projects brings together statisticians, bioinformaticians and biologists from the Toulouse area to reach this goal. The methods will be developed in the context of three scRNA-seq analysis projects:
- tissue generation (mus musculus)
- embryonic development (sus scrofa)
- root development (medicago truncatula)
Participants
| Institut de Mathématiques de Toulouse | Cathy Maugis-Rabusseau, François Bachoc, Pierre Neuvial, Nicolas Enjalbert-Courrech |
| RESTORE (aka StromaLab) | Marielle Ousset, Jenny Paupert, Emmanuelle Arnaud |
| Laboratoire des Interactions Plantes-Microbes Environnement (LIPME) | Sandra Bensmihen |
| Institut national de recherche pour l’agriculture, l’alimentation et l’environnement (INRAE Toulouse) | Nathalie Vialaneix, Sylvain Foissac, Hervé Acloque |
Workshop
- title: “Statistical challenges in scRNA-seq data analysis”
- date: October 10 and 11, 2022
- program
Funding
