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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>.

Last updated

bioinformaticsbiomarkersmachine-learningmirnaomics

5.50 score 21 stars

scDonorAudit - Audit Donor Influence in Single-Cell Pseudobulk Analyses

Audits sample and donor design for two-condition single-cell pseudobulk differential expression analyses. Fits an edgeR quasi-likelihood model to each cell type and repeats the analysis after omitting each donor. Links planned donor omissions to design checks, fit outcomes and observed gene-effect changes. Provides descriptive summaries of donor-deletion sensitivity together with the coverage of valid effects.

Last updated

singlecellrnaseqgeneexpressiondifferentialexpressionqualitycontrolsoftware

3.00 score