lipidomeR

lipidomeR performs statistical analysis and visualization of large-scale lipidomics datasets to identify lipid-class and lipid-species patterns relevant to molecular profiling and disease studies.

Key Features:

• Statistical analysis and high-dimensional visualization: Performs robust statistical analyses and generates high-dimensional visualizations to explore lipidomic variation.
• Reproducible pipeline: Implements a reproducible analysis pipeline to ensure consistent lipidome-wide results.
• Integration of diverse studies: Handles diverse lipidomics datasets including human plasma reference material, breast tumor tissue, and liver samples across non-alcoholic liver disease (NAFLD) progression.
• Publication-ready figures: Produces integrative, publication-ready figures representing lipid-class and lipid-species data.

Scientific Applications:

• Lipid-class pattern discovery: Identifies within- and between-class lipid patterns across experimental conditions.
• Disease progression analysis: Characterizes lipidomic changes across disease stages such as NAFLD progression.
• Comparative tissue and sample analysis: Compares lipidomes across sample types including human plasma reference material and breast tumor tissue.

Methodology:

Implements statistical analysis and high-dimensional visualization in R and uses lipidomics datasets from repositories such as the Metabolomics Workbench.