Changelog

Source: NEWS.md

markeR 0.99.2 (23 Jul, 2025)

• Minor fixes in documentation

markeR 0.99.1 (23 Jul, 2025)

• Fix documentation (invalid characters, deep nesting, missing value in data)
• Remove citation, given that a DOI is not yet available
• Removed unwanted files from the repository

markeR 0.99.0 (18 Jul, 2025)

• First submission to Bioconductor

markeR 0.9.5 (18 Jul, 2025)

• Added VisualiseIndividualGenes() wrapper to unify individual gene visualisation functions (ExpressionHeatmap, ROCandAUCplot, etc.) under a single, user-friendly interface.
• Ensured all data arguments are data frames for consistency across functions.
• Minor bug fix: corrected p-value rounding in PlotScores

markeR 0.9.4 (09 Jul, 2025)

• Minor bug fix: corrected p-value rounding in PlotScores

markeR 0.9.3 (03 Jul, 2025)

• Updated documentation and internal code to meet Bioconductor submission guidelines.
• Fixed minor bugs across multiple functions.
• Added unit tests using testthat for all exported functions.
• Reduced size of demo data to improve package loading time and final size.

markeR 0.9.2 (25 Jun, 2025)

• Fixed broken links in README and vignettes
• Added GitHub Actions workflows:
  • R-CMD-check
  • Matrix-based check for minimal supported R versions
• Unified VariableAssociation() function by modularly integrating GSEA_VariableAssociation() and Score_VariableAssociation()
• Added scripts to fully reproduce all analyses from the original markeR manuscript (inst/Paper)

markeR 0.9.1 (20 Jun, 2025)

• Added package logo
  
• Updated and simplified README file with concise installation instructions and main usage workflow
• Creation of dedicated tutorials:
  • Benchmarking mode
  • Discovery mode
  • Gene set similarity
• Improved function documentation
  
• Minor bug fixes and internal cleanup
• Published full codebase for reproducing analyses shown in markeR’s paper

markeR 0.9.0 (21 Apr, 2025)

• Initial release of the package.
• Implementation of score-based and enrichment-based methods to evaluate gene signatures as phenotype markers.
• Visualization of individual genes’ expression, scores, and enrichment results
• Add pkgdown documentation site: https://diseasetranscriptomicslab.github.io/markeR/