Statistical Methods for Post Genomic Data Conference

Abstract

In this talk, I will discuss our recent advances in the development of isoform-level differential expression tools. In particular, I will focus on how parameter estimates can be made more robust against the noise, sparsity and outliers that are present in scRNA-seq data, without sacrificing scalability. In addition, I will discuss how we can leverage equivalence class counts to unlock droplet scRNA-seq data for sub-gene level differential expression analysis.