Rnits

Rnits performs normalization, curve registration, and temporal inference of time-course gene expression data to enable comparative analysis of gene expression dynamics.

Key Features:

• Normalization: Provides normalization techniques tailored for time-series gene expression datasets to make data from different experiments or batches comparable.
• Curve Registration: Includes curve registration methods that align temporal expression profiles across samples to identify consistent temporal patterns.
• Inference: Models temporal changes to infer underlying biological mechanisms, including gene regulatory networks and pathway activity.

Scientific Applications:

• Developmental biology: Analyses temporal gene expression changes during development to identify stage-specific expression dynamics.
• Disease progression: Tracks gene expression dynamics across disease stages to identify temporal biomarkers and mechanistic changes.
• Response to treatment: Evaluates temporal transcriptional responses to treatments to characterize dynamics of therapeutic response.
• Gene regulatory network and pathway analysis: Dissects gene regulatory networks and pathway dynamics active during specific phases of biological processes.

Methodology:

Implements normalization algorithms, curve registration methods, and temporal inference modeling in R as a Bioconductor package.