Scientific Software
In-development reporting workflows for proteomics quality control, biomarker discovery, and biological interpretation.
Teams need reusable analytical reports that move from metadata checks and QC to statistical workflows, dimensionality reduction, clustering, and biomarker analysis without losing transparency.
ProteomicsReportR is in development as a domain extension that packages proteomics methods into reproducible workflows for inspecting evidence, identifying patterns, and communicating results rigorously.
ProteomicsReportR is part of the SciDataReportR ecosystem. It is designed to translate proteomics analysis patterns into reusable, inspectable reports for biomedical teams working across molecular data, clinical context, and biomarker discovery.
The emphasis is reproducible research: transparent quality control, statistical workflows, data visualization, and report outputs that make scientific reasoning easier to audit and share.
Summaries for missingness, sample-level structure, feature distributions, and data quality checks.
Reusable workflows for group comparisons, candidate biomarker discovery, and interpretable feature prioritization.
Visual workflows that help researchers identify latent molecular structure and disease-relevant subtypes.
ProteomicsReportR extends SciDataReportR for proteomics-focused biomedical data science.
The package supports AI-assisted discovery only when paired with transparent outputs and scientific judgment.