Bioconductor Europe Conference 2019

Abstract

I discuss my current research project, in which I am developing a novel software tool to perform differential expression analyses for single-cell transcripts data at the isoform level as opposed to the canonical gene level. This allows us to assess the change in relative usage of transcripts within a gene between conditions. Such changes are often a direct consequence of alternative splicing regulation, crucially contributing to transcriptome complexity. However, deregulation of the splicing process may have detrimental consequences for the organism, often leading to disease, and is a well-known hallmark of cancer. We show that the current state-of-the-art methods for assessing differential transcript usage, originally developed for bulk RNA-seq, do not scale to scRNA-seq applications. To fill this gap, we propose a general framework that unlocks previously developed differential expression tools for differential transcript usage analysis, leveraging their speed and power to scRNA-seq applications.