  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, 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. In conclusion, 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.
