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Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM

  • Huidong Chen
  • , Luca Albergante
  • , Jonathan Y. Hsu
  • , Caleb A. Lareau
  • , Giosuè Lo Bosco
  • , Jihong Guan
  • , Shuigeng Zhou
  • , Alexander N. Gorban
  • , Daniel E. Bauer
  • , Martin J. Aryee
  • , David M. Langenau
  • , Andrei Zinovyev
  • , Jason D. Buenrostro
  • , Guo Cheng Yuan
  • , Luca Pinello

Research output: Contribution to journalArticlepeer-review

222 Scopus citations

Abstract

Single-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell transcriptomic data, but efforts on analyzing single-cell epigenomic data and on trajectory visualization remain limited. Here we present STREAM, an interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data. We have tested STREAM on several synthetic and real datasets generated with different single-cell technologies. We further demonstrate its utility for understanding myoblast differentiation and disentangling known heterogeneity in hematopoiesis for different organisms. STREAM is an open-source software package.

Original languageEnglish
Article number1903
JournalNature Communications
Volume10
Issue number1
DOIs
StatePublished - 1 Dec 2019
Externally publishedYes

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