Robust lineage reconstruction from high-dimensional single-cell data

Nucleic Acids Res. 2016 Aug 19;44(14):e122. doi: 10.1093/nar/gkw452. Epub 2016 May 20.

Abstract

Single-cell gene expression data provide invaluable resources for systematic characterization of cellular hierarchy in multi-cellular organisms. However, cell lineage reconstruction is still often associated with significant uncertainty due to technological constraints. Such uncertainties have not been taken into account in current methods. We present ECLAIR (Ensemble Cell Lineage Analysis with Improved Robustness), a novel computational method for the statistical inference of cell lineage relationships from single-cell gene expression data. ECLAIR uses an ensemble approach to improve the robustness of lineage predictions, and provides a quantitative estimate of the uncertainty of lineage branchings. We show that the application of ECLAIR to published datasets successfully reconstructs known lineage relationships and significantly improves the robustness of predictions. ECLAIR is a powerful bioinformatics tool for single-cell data analysis. It can be used for robust lineage reconstruction with quantitative estimate of prediction accuracy.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Animals
  • Cell Lineage*
  • Databases as Topic
  • Embryo, Mammalian / cytology
  • Hematopoiesis
  • Mice
  • Reproducibility of Results
  • Sequence Analysis, RNA
  • Single-Cell Analysis / methods*