DDisc
Double-dipping in single-cell RNAseq
Coordinator: Pierre Neuvial
Funding: 80 PRIME 2021
Date: 2021-2024
Web site: DDisc
Summary
The methods classically used to analyze single-cell RNA-seq 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)
