| Literature DB >> 27207878 |
Gregory Giecold1, Eugenio Marco1, Sara P Garcia1, Lorenzo Trippa1, Guo-Cheng Yuan2.
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.Entities:
Mesh:
Year: 2016 PMID: 27207878 PMCID: PMC5001598 DOI: 10.1093/nar/gkw452
Source DB: PubMed Journal: Nucleic Acids Res ISSN: 0305-1048 Impact factor: 16.971