Restructure package to repo root for devtools::install_github compati…#1
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khoindd2000
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May 22, 2026
khoindd2000
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- Moved DeOPUS/ inner package to repo root so install_github("tinnlab/DeOPUS") works
- Fixed DESCRIPTION: removed unused imports, fixed URL, added R>=3.5.0 dep and testthat edition 3
- Fixed R/deconvolve.R: corrected indentation bug, added stats:: namespacing, updated examples to use built-in data
- Generated NAMESPACE via roxygen2 (exports deconvolve, imports from parallel/stats/Matrix)
- Added data/simulated.rda (xz-compressed, 9.8MB) from simulated benchmark dataset
- Added inst/extdata/GSE77343.rds (88MB real GEO dataset)
- Added R/data.R with full dataset documentation
- Moved scripts/ to inst/scripts/ so they install with the package
- Expanded test suite: 62 tests across test-deconvolve.R and test-data.R
- Updated vignette and README with accurate sample code for both datasets
- Added .github/workflows/R-CMD-check.yaml (Linux/macOS/Windows, release+devel)
- Added .github/workflows/release.yaml (auto-release on version tags)
- Added environment.yml for conda env decopus
- Passes R CMD check --as-cran: 0 errors, 0 warnings, 0 notes
added 4 commits
May 22, 2026 14:44
…bility
- Moved DeOPUS/ inner package to repo root so install_github("tinnlab/DeOPUS") works
- Fixed DESCRIPTION: removed unused imports, fixed URL, added R>=3.5.0 dep and testthat edition 3
- Fixed R/deconvolve.R: corrected indentation bug, added stats:: namespacing, updated examples to use built-in data
- Generated NAMESPACE via roxygen2 (exports deconvolve, imports from parallel/stats/Matrix)
- Added data/simulated.rda (xz-compressed, 9.8MB) from simulated benchmark dataset
- Added inst/extdata/GSE77343.rds (88MB real GEO dataset)
- Added R/data.R with full dataset documentation
- Moved scripts/ to inst/scripts/ so they install with the package
- Expanded test suite: 62 tests across test-deconvolve.R and test-data.R
- Updated vignette and README with accurate sample code for both datasets
- Added .github/workflows/R-CMD-check.yaml (Linux/macOS/Windows, release+devel)
- Added .github/workflows/release.yaml (auto-release on version tags)
- Added environment.yml for conda env decopus
- Passes R CMD check --as-cran: 0 errors, 0 warnings, 0 notes
L-BFGS-B can return tiny negative values (~-1e-16) on macOS and Windows due to floating-point differences in bound enforcement. Add pmax(proportions, 0) before normalization to guarantee non-negative output on all platforms.
- Remove inst/extdata/GSE77343.rds (88 MB) - too heavy for an R package - Rename data/simulated.rda -> data/sampleData.rda (object renamed as well) - Fix correlation-against-ground-truth code in README, vignette, R/data.R examples, and tests/testthat/test-data.R: sampleData$bulkRatio rows are in a DIFFERENT order from sampleData$cellTypeExpr columns, so cor() must align by cell-type name first (previous naive code returned -1 for the 2-cell-type case) - Integration test asserts code logic only (finiteness, positive sign) and intentionally does NOT lock in a numeric accuracy threshold, since the deconvolution method may evolve - Restore Benchmarking, Reproducing Paper Results, Data Availability, and Output sections in README (script paths updated to inst/scripts/) - Update .gitignore with standard R package entries - Local R CMD check --as-cran: 0 errors, 0 warnings, 0 notes; 55 tests pass
- generate_figures.R: Resolve visualize_results.R via system.file() with in-repo fallback so the script works both after install and from a clone root. Previous "scripts/analysis/..." was broken in both scenarios. - README §Dependencies: Replace incomplete pair (Matrix, parallel) with the actual packages required by the inst/scripts/ pipeline (RhpcBLASctl, dplyr, tidyverse, scales, cowplot, gridExtra, ComplexHeatmap, circlize), and call out DeconBenchmark+Docker as optional for competing methods. - README §Running Benchmarks: Replace non-working snippet (referenced undefined benchmark_data and ran with default data_dir that doesn't exist) with a self-contained example using data(sampleData) that produces benchmark_data via aggregate_results(). - README §Reproducing Paper Results: Add mkdir -p data/real_datasets/ step so the documented bash workflow actually finds inputs and produces results/real_benchmark/ + figures/. - README §Data Availability: Use system.file() to source the prep script and show how to call create_simulated_dataset(). Verified end-to-end: §Running Benchmarks produces 1024 rows; bash workflow produces both PDFs and aggregated rds; 55 tests pass; R CMD check --as-cran reports 0 errors / 0 warnings / 0 notes.
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