Reversed graph embedding resolves complex single-cell trajectories

Nat Methods. 2017 Oct;14(10):979-982. doi: 10.1038/nmeth.4402. Epub 2017 Aug 21.

Abstract

Single-cell trajectories can unveil how gene regulation governs cell fate decisions. However, learning the structure of complex trajectories with multiple branches remains a challenging computational problem. We present Monocle 2, an algorithm that uses reversed graph embedding to describe multiple fate decisions in a fully unsupervised manner. We applied Monocle 2 to two studies of blood development and found that mutations in the genes encoding key lineage transcription factors divert cells to alternative fates.

MeSH terms

  • Algorithms*
  • Animals
  • Cell Differentiation / physiology*
  • Computer Simulation*
  • Gene Expression Regulation, Developmental / physiology*
  • Models, Biological*
  • Mutation
  • Transcription Factors / genetics
  • Transcription Factors / metabolism
  • Transcriptome / physiology

Substances

  • Transcription Factors