PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells

Single-cell RNA-seq quantifies biological heterogeneity across both discrete cell types and continuous cell transitions. Partition-based graph abstraction (PAGA) provides an interpretable graph-like map of the arising data manifold, based on estimating connectivity of manifold partitions ( https://github.com/theislab/paga ). PAGA maps preserve the global topology of data, allow analyzing data at different resolutions, and result in much higher computational efficiency of the typical exploratory data analysis workflow. We demonstrate the method by inferring structure-rich cell maps with consistent topology across four hematopoietic datasets, adult planaria and the zebrafish embryo and benchmark computational…

• DZ
  Deutsches Zentrum für Herz-Kreislaufforschung

  Award: DZHK BER 1.2 VD
• CR
  Cancer Research UK
• DF
  Deutsche Forschungsgemeinschaft

  Awards: RA 838/5-1, Subproject A17
• V
  Vetenskapsrådet
• NI
  National Institutes of Health
• MR
  Medical Research Council

  Award: MC_PC_12009
• CI
  Cambridge Institute for Medical Research, University of Cambridge
• NI
  National Institute of Diabetes and Digestive and Kidney Diseases