Package: detectPanel 0.1.3

detectPanel: Leakage-Aware Discovery of Small Biomarker Panels

Discovers small binary-classification biomarker panels from count or expression matrices while prioritizing detectability, expression stability, and univariate discrimination. Candidate filtering and panel selection can be repeated inside nested cross-validation to reduce information leakage. The package provides shared resampling splits, exhaustive small-panel search, logistic model fitting with an automatic ridge fallback for unstable separation-prone fits, out-of-fold evaluation, selection-frequency summaries, and optional 'DESeq2' differential-expression support. The nested model-selection workflow follows Varma and Simon (2006) <doi:10.1186/1471-2105-7-91>, and the optional differential-expression analysis uses Love, Huber, and Anders (2014) <doi:10.1186/s13059-014-0550-8>.

Authors:Fuhao Jiang [aut, cre]