ImpulseDE

ImpulseDE models impulse-like temporal patterns in high-throughput gene expression time-series to identify differentially expressed genes and characterize responses to environmental perturbations.

Key Features:

• Impulse model fitting: Fits a representative impulse model to each gene's expression time course to capture single impulse-like temporal patterns.
• Differential expression detection: Identifies and reports differentially expressed genes across multiple time points within a single experiment or between two distinct time courses.
• High-throughput compatibility: Designed for high-throughput time-series datasets derived from microarray or RNA-Seq experiments.
• Computational optimization: Incorporates clustering steps and multi-threading techniques to optimize runtime on large datasets.
• Perturbation response detection: Captures distinctive gene expression changes in response to environmental perturbations.
• R implementation: Implemented as an R package.

Scientific Applications:

• Time-series gene expression analysis: Dissects temporal gene expression dynamics in time-course experiments.
• Environmental perturbation studies: Detects gene expression responses to environmental perturbations.
• Developmental biology: Studies temporal changes in gene expression during development.
• Systems biology: Models dynamic transcriptional responses in systems biology contexts.
• Disease progression studies: Characterizes gene expression dynamics during disease progression.
• Microarray and RNA-Seq time-course analysis: Suitable for analyses of large-scale microarray or RNA-Seq time-series datasets.

Methodology:

Fits an impulse model per gene, uses clustering steps and multi-threading techniques, and identifies and reports differentially expressed genes across time points or between two time courses.