GeneSwitches

GeneSwitches orders gene-expression and functional events along single-cell RNA sequencing (RNA-seq) pseudo-time trajectories to identify the timing of gene activation and functional changes during cell state transitions.

Key Features:

• Pseudo-time trajectory analysis: Operates on any given single-cell pseudo-time trajectory to determine the order of gene-expression changes over time.
• Identification of on/off switch genes: Uses a statistical framework based on logistic regression to identify genes that switch on or off at specific pseudo-time points.
• Functional event ordering: Orders functional events including the appearance of surface markers and the gain or loss of functional ontologies along pseudo-time.
• Comparative switching analysis: Compares switching genes between two related pseudo-temporal processes to reveal similarities and differences in gene regulatory mechanisms.
• Single-cell RNA-seq compatibility: Leverages single-cell RNA sequencing (RNA-seq) gene expression profiles as input data for analysis.

Scientific Applications:

• Cell differentiation studies: Maps the order of gene switches to reconstruct pathways involved in cell differentiation and developmental processes.
• Disease progression analysis: Elucidates sequences of gene-expression and functional events relevant to disease mechanisms, including cancer.
• Biomarker discovery: Tracks the temporal appearance of surface markers to support identification of potential biomarkers.

Methodology:

Applies logistic regression to single-cell RNA-seq data mapped onto pseudo-time trajectories to determine when specific genes are activated or deactivated.