ECLAIR

ECLAIR infers cell lineage relationships from single-cell gene expression data using an ensemble statistical approach that quantifies uncertainty in lineage branching.

Key Features:

• Ensemble approach: Aggregates multiple analytical models to enhance robustness and reliability of lineage predictions.
• Statistical inference: Performs statistical inference of cell lineage relationships from single-cell gene expression data.
• Uncertainty quantification: Provides a quantitative estimate of uncertainty for each predicted lineage branching.
• Cellular hierarchy reconstruction: Reconstructs cellular hierarchies in multicellular organisms from expression data.
• Validation on published datasets: Has been applied to published datasets to demonstrate recovery of known lineage relationships.

Scientific Applications:

• Lineage reconstruction: Recovering known and inferred cell lineage relationships from single-cell gene expression datasets.
• Single-cell data analysis: Characterizing cellular hierarchies and population structure in single-cell transcriptional studies.
• Developmental biology: Supporting systematic characterization of developmental lineages and related biological hierarchies with quantified confidence.

Methodology:

ECLAIR uses an ensemble approach that aggregates multiple analytical models to perform statistical inference of cell lineage relationships from single-cell gene expression data and produces quantitative uncertainty estimates for predicted lineage branchings; it has been applied to published datasets for validation.