Robust lineage reconstruction from high-dimensional single-cell data

被引:19
作者
Giecold, Gregory [1 ,2 ]
Marco, Eugenio [1 ,2 ,4 ]
Garcia, Sara P. [1 ,2 ]
Trippa, Lorenzo [1 ,2 ]
Yuan, Guo-Cheng [1 ,2 ,3 ]
机构
[1] Dana Farber Canc Inst, Dept Biostat & Computat Biol, Boston, MA 02215 USA
[2] Harvard TH Chan Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA
[3] Harvard Stem Cell Inst, Cambridge, MA 02138 USA
[4] Editas Med, Cambridge, MA 02142 USA
关键词
FATE DECISIONS; RNA-SEQ; CYTOMETRY;
D O I
10.1093/nar/gkw452
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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 fromsinglecell 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.
引用
收藏
页数:7
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