Reversed graph embedding resolves complex single-cell trajectories

Abstract

Single-cell trajectories can unveil how gene regulation governs cell fate decisions. However, learning the structure of complex trajectories with two or more branches remains a challenging computational problem. We present Monocle 2, which uses reversed graph embedding to describe multiple fate decisions in a fully unsupervised manner. Applied to two studies of blood development, Monocle 2 revealed that mutations in key lineage transcription factors diverts cells to alternative fates.