MetabolomicsReportR is an open-source component of the SciDataReportR ecosystem designed to standardize metabolomics analysis workflows. The package emphasizes reproducible quality control, statistical discovery, pathway enrichment, and biological interpretation, helping researchers move from metabolite measurements to mechanistic insight.
Scientific Software
MetabolomicsReportR
In-development metabolomics reporting for multi-omics biomedical discovery.
Scientific problem
Modern metabolomics studies generate hundreds to thousands of molecular measurements that require rigorous quality control, normalization, statistical modeling, pathway interpretation, and biological contextualization.
Why It Was Needed
Researchers need transparent workflows that transform metabolite-level findings into interpretable biological mechanisms while preserving reproducibility and analytical rigor.
What It Enables
MetabolomicsReportR provides reproducible metabolomics workflows for quality assessment, statistical discovery, pathway enrichment, network-based interpretation, and biologically informed reporting.
Capabilities
Quality control and preprocessing
Assess missingness, outliers, batch effects, normalization performance, and overall data quality through reproducible workflows.
Statistical discovery
Support differential metabolite analysis, association testing, longitudinal modeling, biomarker discovery, and exploratory machine learning.
Pathway enrichment and interpretation
Connect metabolite-level findings to biological pathways, molecular processes, and disease mechanisms using modern enrichment approaches.
RaMP-DB integration
Leverage the RaMP knowledgebase to harmonize metabolite identifiers and connect findings across pathways, reactions, metabolites, genes, and biological annotations.
Publication-ready reporting
Generate transparent reports, visualizations, and analytical summaries that document the full metabolomics workflow.