Leakage-Aware Discovery of Small Biomarker Panels R package detectPanel version 0.1.3 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>. Software Depends: R (>= 4.2.0) Imports: ggplot2, graphics, stats, utils Suggests: DESeq2, knitr, rmarkdown, pheatmap, testthat (>= 3.0.0) Fuhao Jiang <emr39515@gmail.com> Comprehensive R Archive Network (CRAN) Fuhao Jiang [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=detectPanel/LICENSE) 2026-09-15 application/tgz https://CRAN.R-project.org/package=detectPanel doi:10.32614/CRAN.package.detectPanel