Changelog

Source: NEWS.md

Changes in version 0.99.6

New features

• enrichment_CTD() gains an interaction_types argument: a character vector of CTD InteractionActions values (e.g. "increases^expression", "decreases^expression") that filters each chemical’s gene set at enrichment time. Gene sets are rebuilt on the fly from the new ctd_interactions.rda cache without re-importing; NULL (default) retains full backward compatibility. Supported by all four methods (ORA, GSEA, CAMERA, GSVA). Requires import_CTD() to be re-run once to generate ctd_interactions.rda.

• enrichment_CTD() gains a gene_id_type argument ("symbol" or "entrez") controlling whether the EnrichedGenes output column reports HGNC symbols (with Entrez ID fallback for unmapped genes) or raw Entrez IDs. Default "symbol" is backward compatible.

• enrichment_CTD(method = "ORA") now forwards universe, minGSSize, and maxGSSize to clusterProfiler::enricher() via .... Setting universe = de$EntrezID restricts the background to measured genes, avoiding inflated fold-enrichment estimates. GSEA and GSVA already exposed minSize/maxSize; CAMERA ... was already forwarded.

• import_CTD() now caches ctd_interactions.rda, a long-format table of (ChemicalID, EntrezID, InteractionActions) triples used by the new interaction_types filter.

• import_CTD() reports elapsed time, chemical count, and unique gene count on completion.

• import_CTD() detects and warns when the same ChemicalID appears with multiple ChemicalName values (CTD data quality issue; first name retained). Reports an informational message when the same name is shared by multiple ChemicalIDs (legitimate parent/derivative pairs).

Bug fixes

• Fixed EnrichedGenes column in GSEA output: was incorrectly set to data frame row indices instead of gene identifiers. Gene labels are now mapped via AnnotationDbi::mapIds() in .run_gsea().

• clusterProfiler::enricher() messages (“No gene can be mapped”, “Expected input gene ID”, etc.) are now suppressed via suppressMessages().

Documentation

• New pkgdown article vignettes/articles/tutorial_rnaseq_workflow.Rmd: a complete RNA-seq → chemical enrichment workflow using the full GSE311566 dataset (downloaded from GEO at runtime), limma DE, all four methods with recommended parameters, direction-aware GSEA, and a per-method Dexamethasone ranking recap.

• Vignette gains a “Gene set size filters and background universe” section documenting universe, minGSSize/maxGSSize (ORA), minSize/maxSize (GSEA, GSVA), and CAMERA’s implicit minimum of 2 genes.

• Added a new interaction_types parameter description to the vignette explaining the CTD verb^noun vocabulary and direction-aware analysis.

• Added a full end-to-end pipeline example at inst/scripts/example_gse311566_full_pipeline.R. The script downloads the complete GSE311566 Female PBMCs normalised-count matrix (Dex vs DMSO), computes an a-priori power analysis with declared alpha thresholds, runs limma-based differential expression, and exercises all four enrichment methods (ORA, GSEA, CAMERA, GSVA) with BH-adjusted significance cutoffs. It refuses to fall back to the bundled toy CTD sample; the user must populate the CTD cache with the real chemical-gene interactions file first. Complements the vignette (which uses the bundled subset without alpha cutoffs) by providing the production-shaped example linked from the README and the companion paper.

Changes in version 0.99.5

Documentation

• Added an end-to-end real-data example to the vignette using a small subset of GEO series GSE311566 (human PBMCs, dexamethasone vs. vehicle, female donors). The example walks through loading the bundled subset, a deliberately minimal base-R differential expression with t.test + p.adjust, and the four ctdR methods (ORA, GSEA, CAMERA, GSVA) on the resulting DE.
• Bundled inst/extdata/GSE311566_subset.rds (~34 KB) containing log2-normalised counts for 1,500 top-variance genes plus the 17 genes referenced by the toy CTD sample, across 7 samples (4 DMSO + 3 Dex).
• Added a reproducible provenance script at inst/scripts/make_gse311566_subset.R and a per-file documentation README at inst/extdata/README.md.
• The enrichment_CTD() @examples block no longer relies on \donttest{}: CAMERA and GSVA examples now run directly on the bundled subset, satisfying the BiocCheck recommendation against \dontrun{} / \donttest{} in man pages.

Testing

• New tests/testthat/test-e2e-gse311566.R runs the full data-to-enrichment pipeline on the bundled GSE311566 subset and asserts that Dexamethasone (D003907) ranks in the top 3 by GSEA p-value and in the top 6 by CAMERA p-value, plus structural checks on the GSVA output. Guards against silent regressions in ID mapping, output schema, or sort order that the vignette and man-page examples would only catch as “still runs”.

Changes in version 0.99.4

Breaking changes

These changes are made now, while the package is pre-1.0 and not yet accepted into Bioconductor, so that the public column schema is stable before any external code depends on it.

Input column name (ORA / GSEA)

• The input data frame must now provide an EntrezID column (was entrez_ids). The numeric value column can still be named freely.

Unified output schema (ORA, GSEA, CAMERA)

All three data-frame-returning methods now share the same leading columns, in this order:

ChemicalID, ChemicalName, Method, PValue, PValueAdjusted, ...

The new Method column carries the method label ("ORA", "GSEA", "CAMERA"), making cross-method rbind / dplyr::bind_rows straightforward.

Rows are sorted by PValueAdjusted ascending in all three methods (previously ORA results were unsorted).

Column renames (full table)

Method	Old column	New column
GSEA	pval	PValue
GSEA	ES	EnrichmentScore
GSEA	NES	NormalizedEnrichmentScore
GSEA	size	GeneSetSize
GSEA	leadingEdge	LeadingEdge
GSEA	Enriched_GENE	EnrichedGenes
ORA	pvalue	PValue
ORA	padj	PValueAdjusted
ORA	BgRatio	BackgroundRatio
ORA	qvalue	QValue
ORA	geneID	EnrichedGenes
ORA	foldEnrichment	FoldEnrichment
ORA	ID	ChemicalID
ORA	Description	(dropped — was always == ID)
CAMERA	PValue	(kept as) PValue
CAMERA	NGenes	GeneSetSize
CAMERA	FDR	(dropped — PValueAdjusted recomputed per pAdjustMethod)
All	(new)	Method

Cross-method semantic alignment: - GeneSetSize replaces both GSEA’s size and CAMERA’s NGenes - EnrichedGenes replaces both ORA’s geneID and GSEA’s Enriched_GENE - PValue / PValueAdjusted are spelled the same across all methods

Internal refactor

• enrichment_CTD() shrank from 101 lines to ~30 by delegating argument validation to .validate_enrichment_args() and adding .run_ora() / .run_gsea() runners mirroring the existing .run_camera() / .run_gsva() shape.
• .format_enrichment_result() is the single source of truth for the engine -> canonical-schema mapping: each runner passes a rename = c(old = "New") and drop = c(...) and the formatter handles padj recomputation, metadata merge, column ordering, sort and row-name reset.
• gsea() and ora() engines now return their underlying tool’s native column casing (pval / pvalue, ES, NES, …); the only semantic rename they apply themselves is lifting the primary-key column (pathway for fgsea, ID for clusterProfiler) to ChemicalID, so internal callers never see the misleading generic name.
• gsea() signature dropped the unused chemicals and pAdjustMethod arguments. Its entrez_ids parameter was renamed to gene_table (still internal-only).
• .run_camera() shrank to 48 lines (was 57) and .run_ora() / .run_gsea() are now under 30 lines each. BiocCheck’s “function length > 50” NOTE is satisfied for the enrichment-table pipeline.

Changes in version 0.99.2

New features

• enrichment_CTD() now supports four enrichment methods through a unified interface, selectable via the method argument:
  • "ORA" (default) — Over-Representation Analysis via clusterProfiler::enricher() (unchanged).
  • "GSEA" — rank-based Gene Set Enrichment Analysis via fgsea::fgsea() (unchanged).
  • "CAMERA" — competitive gene-set test accounting for inter-gene correlation, via limma::camera(). Input: a numeric expression matrix (genes x samples) plus a design matrix and a contrast.
  • "GSVA" — per-sample Gene Set Variation Analysis via GSVA::gsva(), returning a chemical x sample score matrix.
• New first argument x (polymorphic): a data frame for ORA/GSEA, a numeric matrix for CAMERA/GSVA. Auto-detects identifier type (Entrez vs HGNC SYMBOL) from rownames(x); an explicit id_type override is also accepted.
• plot_CTD() now dispatches on input class and method-specific columns: bar/dot plots of fold enrichment for ORA/GSEA, bar/dot plots of -log10(padj) coloured by direction of enrichment for CAMERA, and a sample-level heatmap of the top-variance chemicals for GSVA.

Deprecation

• The first argument of enrichment_CTD() was renamed entrez_ids -> x. Calls using the old name still work but emit a deprecation warning and will be removed in a future release.

Dependencies

• New Imports: limma, GSVA, stats.

Changes in version 0.99.1

Bioconductor reviewer feedback

• Removed renv from the package. Dependencies are managed via DESCRIPTION and installed by r-lib/actions/setup-r-dependencies (pak-based) in CI.

Bug fixes

• import_CTD() now stores ChemicalName_GeneSymbols$gene as a character vector instead of a factor, fixing “universe must be a character vector” in clusterProfiler::enricher().
• Inlined parse_ratio() as a private helper because DOSE::parse_ratio is no longer exported. DOSE is dropped from Imports.
• Aligned man/gsea.Rd parameter name with R/gsea.R (ChemicalName_GeneEntrezIds), removing a codoc-mismatch WARNING.
• Declared plot_CTD() ggplot2 NSE column references in utils::globalVariables(), removing “no visible binding” NOTEs.

Infrastructure

• Pinned trufflesecurity/trufflehog to a concrete version; the bare @v3 tag does not exist in the action repo.
• Made oysteR audit fail-soft when OSS Index credentials are missing (still fails the build on real vulnerabilities).
• Removed the dependency-review job: GitHub’s Dependency Graph does not support R DESCRIPTION files.

Changes in version 0.99.0

Improvements

• Bumped version to 0.99.0 for Bioconductor submission.
• Fixed R CMD check to pass with 0 errors, 0 warnings, 0 notes.
• Fixed CI workflows for macOS, Ubuntu, and Windows.
• Added Codecov integration for coverage reporting.
• Added GitHub Pages site with usage examples.
• Fixed broken README badges.

Changes in version 0.1.2

New features

• Added import_CTD() function to import and cache CTD chemical-gene interaction data from user-downloaded files.
• Added Over-Representation Analysis (ORA) method via clusterProfiler::enricher.
• enrichment_CTD() now supports two methods: "ORA" (default) and "GSEA".
• Clear error message when CTD data has not been imported, with instructions on how to download and import the required file.

Improvements

• Separated data import from analysis — users call import_CTD() once, then enrichment_CTD() as many times as needed.
• Added fold enrichment calculation to both ORA and GSEA results.
• gsea() now receives chemicals as an explicit parameter instead of relying on the parent environment.
• Removed deprecated nperm parameter from fgsea::fgsea call.
• Removed leftover browser() calls.

Documentation

• Added comprehensive roxygen documentation for all exported and internal functions, including parameter descriptions, return value tables, and examples.
• Added package-level help page (?ctdR) with quick start guide.
• Added data licensing disclaimer throughout documentation and DESCRIPTION.
• Added README.md with badges, installation instructions, and usage examples.
• Added vignette with complete workflow.

Testing

• Added testthat test suite with 100% line coverage.
• Tests cover: import validation, missing data errors, ORA enrichment, GSEA enrichment, NA handling, and column structure.

Infrastructure

• Added GitHub Actions CI for macOS, Ubuntu, and Windows.
• Added test coverage workflow with Codecov integration.

Changes in version 0.1.1

• Added GSEA analysis via fgsea::fgsea.
• Initial caching mechanism using rappdirs.

Changes in version 0.1.0

• Initial package skeleton.
• Basic gene-chemical interaction parsing from CTD CSV files.