PseudotimeDE

PseudotimeDE performs differential expression analysis along pseudotime trajectories from single-cell RNA sequencing (scRNA-seq) data by explicitly accounting for uncertainty in pseudotime inference.

Key Features:

• Adaptability: Integrates with various pseudotime inference methods to perform DE analysis across different pseudotime frameworks.
• Uncertainty Accounting: Explicitly models the uncertainty associated with pseudotime estimation when testing for differential expression.
• Well-Calibrated p-values: Produces well-calibrated p-values for hypothesis testing along pseudotime trajectories.
• False Discovery Rate Control and Power: Demonstrates control of the false discovery rate while maintaining high statistical power based on simulation and real-data evaluation.

Scientific Applications:

• Cell state transition analysis: Identification of differentially expressed genes to elucidate molecular mechanisms underlying cell state transitions.
• Developmental and dynamic process analysis: Detection of dynamic gene expression changes along developmental pathways and other temporal trajectories in scRNA-seq data.

Methodology:

Implements a statistical framework that performs differential expression testing along pseudotime while explicitly modeling pseudotime inference uncertainty and remaining compatible with multiple pseudotime inference methods.