BioLizard Research Meeting

Abstract

In this talk I discuss recent advances in software for differential expression analysis for single-cell transcriptomics data. I will first compare bulk and single-cell transcriptomics data, discuss several key advances in single-cell protocols, and highlight their impact on the resulting data and downstream analysis methods. Second, I will focus on a promising software tool for differential gene expression analysis, muscat. muscat is designed for the analysis of multi-sample, multi-group data and is rapidly becoming one of the most prominent tools in this context. The final part of my presentation will focus on transcript-level analysis – as opposed to the canonical gene-level inference. I will present satuRn, our novel R package for differential transcript usage (DTU) analysis that has been developed by our research group. Across different benchmark settings, we found that satuRn is the only method that combines all properties that make for a good DTU tool for single-cell data. Finally, the use of satuRn is exemplified through a case study, showcasing how satuRn can discover orthogonal results as compared to traditional gene-level analysis that are furthermore biologically relevant to the system under study.