Literature DB >> 27207878

Robust lineage reconstruction from high-dimensional single-cell data.

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.
© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

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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


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