Dear all

This week, Mark Robinson (Institute of Molecular Life Sciences, University of Zurich), one of the developers of edgeR, is going to give a talk about his new approach on performing differential expression analysis on single-cell data with multiple samples and multiple conditions:

Single-cell RNA-sequencing (scRNA-seq) has become an empowering technology to characterize the transcriptomes of individual cells. Although many early analyses of differential expression (DE) have focused on finding markers for cell sub-populations (experimental units are cells), there is now an emergence of datasets across replicates and multiple conditions where the goal is to make patient-level inferences (experimental units are patients), with 100s to 1000s of cells measured for each patient. This provides an opportunity to go back and make use of the existing robust bulk RNA-seq frameworks, by first aggregating the data into "pseudobulk" counts at the subpopulation level. However, this opens up new questions, which we will address in this talk: how does one track subpopulations across patients? do we lose information by aggregating? normalization? We will present a comprehensive framework for flexible multi-sample multi-condition DE of scRNA-seq experiments.

This will take place on October 24 at 3pm in the FSVM seminar room of the VIB-UGent building in Zwijnaarde (Technologiepark-Zwijnaarde 71, 9052 Ghent, Belgium).

Kind regards