Master thesis of Vincent Marty
In Schiebinger et al. (2019), the authors introduce the Waddington-OT algorithm (WOTA). Based upon Optimal Transport theory, this approach studies developmental time courses to infer ancestor-descendant fates and model the regulatory programs that underlie them. This was initially applied to explain cellular reprogramming of murine fibroblasts into IPSCs based on the expression of a group of transcription factors.
We will assess the relevance of the WOTA in a different setting, the CD8 T cell differentiation after antigen presentation. Within the frame of the MEMOIRE (MultiscalE MOdeling of CD8 T cell Immune Responses) ANR project, we plan to identify, at the single cell level, signatures associated with functionally relevant memory CD8 T cell subsets in mice, to characterize dynamical molecular networks that are predictive of their generation, and to build a multiscale model of this process. One important part of the internship, co-mentored by Fabien Crauste and Olivier Gandrillon, will consist in assessing the impact of low-level single cell RNAseq treatment (filtering, doublet detection, normalization, feature selection, denoising, dimensionality reduction) on the final output. Furthermore, the resulting trajectories will be compared with mainstream algorithms like Monocle.