Efficient Tools for Quantifying and Simulating Transcript-Level Abundance in Single-Cell RNA-seq

To create and evaluate efficient tools for quantifying gene and transcript group expression from single-cell RNA-seq data, as well as a realistic data simulation tool to aid in assessment.

First, the Patro lab built a method for uncertainty quantification for droplet-based single-cell RNA-seq quantification—implemented as the alevin tool within their salmon software. Alevin proposes a framework for dealing with gene multi-mapping tools and delivers a computational approach to assess gene-level quantification uncertainty, as described in their preprint. Second, they built a sequence-level simulation tool for droplet-based single-cell RNA-seq data, minnow.