- Moved Python bridge scripts from
inst/python/to a top-levelpython/directory, as these are supplementary scripts not part of the R package itself. - Added
requirements.txtto thepython/directory listing all needed Python dependencies (rpy2,pandas,numpy, and optionallyipythonandjupyter) for easier environment setup. - Removed redundant code snippets from the Python bridge scripts.
- Added
p.adjust.methodparameter across all functions performing or depending on multiple testing correction, allowing users to specify any correction method supported bystats::p.adjust(), beyond the default Benjamini-Hochberg FDR. - Added Python bridge scripts in
inst/python/for users who wish to call markeR from a Python environment viarpy2. Includes a tutorial workflow script and a generic command-line wrapper capable of invoking any exported markeR function. Seeinst/python/README.mdfor installation and usage.
- Official Bioconductor Release.
- Minor fix in
.onAttach()to avoid errors when checkingggplot2version and ensure the startup warning works correctly.
- Addressed feedback from the Bioconductor review process with updates to documentation and vignette style.
- Updated vignette style to Bioconductor’s BiocStyle with automatic table of contents.
- Improved vignette content with small corrections.
- Revised dataset documentation by adding explicit
usage: data(object)entries.
- Updated
geneset_similarity()color handling: replaced the singlecolor_valuesparameter with three new parameters —color,neutral_color, andcold_color, for more interpretable visualization.
- Reduced package size below the 5 MB limit by converting long vignettes into
pkgdownarticles and keeping only a shorter vignette in the package. - Moved
inst/Paperto a dedicatedpaperbranch for better repository organization. - Removed unnecessary
LICENSEfile (already declared inDESCRIPTION).
- Added a concise main vignette (
markeR) with installation, introduction, and a basic workflow. - Converted three longer vignettes into
pkgdownarticles (linked at the end of the main vignette). - Added runnable examples for
VariableAssociation.
- Replaced broad imports with
importFrom()for most packages (exceptggplot2, retained as full import). - Removed unused
patchworkimport. - Added missing imports from
statsandgrDevicesto resolveR CMD checknotes.
- Replaced all
sapply()calls withvapply(). - Replaced
1:...usage withseq_len()orseq_along(). - Standardized assignment to
<-instead of=. - Fixed some redundant
stop()/warning()conditions to provide clearer input validation. - Addressed “no visible binding” notes by using
.data$orutils::globalVariables().
- Minor fixes in documentation
- 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
- First submission to Bioconductor
- 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
- Minor bug fix: corrected p-value rounding in
PlotScores
- Updated documentation and internal code to meet Bioconductor submission guidelines.
- Fixed minor bugs across multiple functions.
- Added unit tests using
testthatfor all exported functions. - Reduced size of demo data to improve package loading time and final size.
- Fixed broken links in README and vignettes
- Added GitHub Actions workflows:
R-CMD-check- Matrix-based check for minimal supported
Rversions
- Unified
VariableAssociation()function by modularly integratingGSEA_VariableAssociation()andScore_VariableAssociation() - Added scripts to fully reproduce all analyses from the original
markeRmanuscript (inst/Paper)
- 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
- 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/