tuneR: Hyperparameter Search for mixOmics
Statistical modeling package extending mixOmics for high-dimensional omics data hyperparameter optimization.
R mixOmics Statistical Modeling Bioconductor
Scientific Context
In computational biology, multivariate omics data often needs dimensionality reduction before it becomes interpretable. mixOmics is one R package used for that workflow.
tuneR focuses on the tuning step for sparse Partial Least Squares (sPLS) models, where exhaustive search can become expensive quickly.
Architecture & Impact
- Benchmark-Backed Search Efficiency: In my benchmark harness, random search cut median wall time by 60.5% while matching the best observed accuracy across a 125-combination block-sPLSDA search space.
- Bioconductor Standards: Uses Bioconductor S4 class structures for interoperability with R bioinformatics workflows.
- Reproducibility: Uses deterministic seeding so tuning runs can be repeated across compute environments.