title: Robust lineage reconstruction from high-dimensional single-cell data.
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.
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
authors.forename: Gregory
authors.initials: G
authors.lastname: Giecold
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
authors.forename: Eugenio
authors.initials: E
authors.lastname: Marco
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
authors.forename: Sara P
authors.initials: SP
authors.lastname: Garcia
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
authors.forename: Lorenzo
authors.initials: L
authors.lastname: Trippa
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA Harvard Stem Cell Institute, Cambridge, MA 02138, USA gcyuan@jimmy.harvard.edu.
authors.forename: Guo-Cheng
authors.initials: GC
authors.lastname: Yuan
mesh_terms: D000465:Algorithms; D000818:Animals; D019070:Cell Lineage; D019992:Databases as Topic; D004622:Embryo, Mammalian / Q000166:cytology; D006410:Hematopoiesis; D051379:Mice; D015203:Reproducibility of Results; D017423:Sequence Analysis, RNA; D059010:Single-Cell Analysis / Q000379:methods*