splineTimeR

splineTimeR applies natural cubic spline regression modeling to detect differentially expressed genes in time-course gene expression data and reconstruct time-dependent gene association networks for studying dynamic transcriptomic responses.

Key Features:

• Natural Cubic Spline Regression Modeling (NCSRM): Uses NCSRM to detect differentially expressed genes across time-course datasets and capture complex temporal expression patterns.
• Increased sensitivity and low false-detection rate: Detects a greater number of genes compared to methods such as BETR while maintaining a reported false-detection rate of 3%.
• Gene Association Network (GAN) reconstruction: Reconstructs GANs using regularized dynamic partial correlation implemented via GeneNet.
• Time-dependent gene regulatory network reconstruction: Supports reconstruction of time-dependent gene regulatory networks from identified differentially expressed genes.
• Functional characterization of key nodes: Identifies and characterizes key nodes within reconstructed networks to infer functional roles.
• Pathway enrichment analysis: Performs pathway enrichment analysis and evaluates overlap with interactome resources such as Reactome.

Scientific Applications:

• Radiation response analysis: Applied to time-resolved transcriptome data from radiation-perturbed cell culture models to distinguish responses between non-tumor cells with normal and increased radiation sensitivity.
• Dose-specific response characterization: In studies at 1 Gy and 10 Gy, identifies senescence-associated responses at lower doses and apoptosis-related responses at higher doses in increased-sensitivity cells, while normal-sensitive cells show a comparatively sparse senescence-related response.
• Network validation against interactomes: Reconstructed GANs demonstrate superior overlap with the Reactome interactome, supporting the biological relevance of inferred interactions.

Methodology:

Applies natural cubic spline regression modeling (NCSRM) for differential expression testing; reconstructs gene association networks using regularized dynamic partial correlation via GeneNet; performs pathway enrichment analysis; reconstructs time-dependent gene regulatory networks; implemented in the Bioconductor R-package splineTimeR.