Changes in version 1.3.3 New features - method argument from orthogene::create_background and orthogene::convert_orthologs is now passed up as an argument to EWCE functions to give users more control. "homologene" chosen as default for all functions. "homologene" has fewer species than "orthogene" but doesnt need to import data from the web. It also has more 1:1 mouse:human orthologs. - Include notes on mismatches between GitHub documentation and current Bioc release version. - Allow bin_specificity_into_quantiles to set specificity matrix name produced. - Merge GHA workflow yamls into one. Bug fixes - Add try({}) and error=TRUE to avoid "polygon edge not found" error in vignettes. Changes in version 1.3.1 New features - Major changes: Pull Request from bschilder_dev branch. - All functions can now use lists and CellTypeDatasets (CTD) from any species and convert them to a common species (human by default) via orthogene. - Automated CTD standardisation via standardise_ctd. - Can handle (sparse) matrices. - Can create CTD from very large datasets using DelayedArray object class. - All functions automatically create appropriate gene backgrounds given species. - More modular, simplified vignettes. - Additional gene pre-filtering options (DESeq2, MAST, variance quantiles). - New/improved plotting functions (e.g. plot_ctd). - Added example bootstrapping enrichment results as extdata to speed up examples (documented in data.R). Accessed via EWCE::example_bootstrap_results(). - Replaced GHA workflow with check-bioc to automatically: run R-CMD checks, run BiocCheck, and rebuild/deploy pkgdown site. - Parallelised functions: - drop_uninformative_genes - generate_celltype-data - bootstrap_enrichment_test - Added tests (multiple functions tests per file to reduce number of times ewceData files have to be downloaded): - test-DelayedArray - test-merge_sce - test-get_celltype_table - test-list_species - test-run_DGE - test-check_percent_hits - Added function is_32bit() to all tests to ensure they don't get run twice on Windows OS. - Added GitHub Actions workflows: - check-bioc-docker.yml: Runs CRAN/Bioc checks, rebuilds and pushes pkgdown website, runs and uploads test coverage report, - dockerhub.yml: Builds Bioconductor Docker container with EWCE installed, runs CRAN checks and (if checks are successful) pushes container to neurogenomicslab DockerHub. - Removed docs folder, as the documentation website comes from the gh-pages branch now, and is automatically built by GHA workflow after each push to main branch. - Added new exported function fix_celltype_names to help with standardising celltype names in alignment with standardise_ctd. - generate_bootstrap_plots_for_transcriptome: Now supports any species (not just mouse or human). - Converts CTD and DGE table (tt) into output_species gene symbols. - Automatically generates appropriate gene background. - Faster due to now having the option to only generate certain plot types. - Provide precomputed results from ewce_expression_data via new example_transcriptome_results function. - Reduced build runtime and oversized vignettes by not evaluating certain code chunks. - Prevent extended vignette from running entirely. - @return documentation for internal functions. - Added more installation checks to GHA. - Fixed inconsistent naming of unit test files: test_ ==> test- - Removed DGE args in drop_uninformative_genes for now until we run benchmarking to see how each affects the EWCE results. - Make bootstrap_plots function internal. - Add report on how orthogene improve within- and across-species gene mappings in extended vignette. - Record extra info in standardise_ctd output: - "species": both input_species and output_species - "versions": of EWCE, orthogene, and homologene Changes in version 1.0.0 New Features - EWCE v1.0 on Bioconductor replaces the defunct EWCE v1.3.0 available on Bioconductor v3.5. - EWCE has been rendered scalable to the analysis of large datasets - drop_uninformative_genes() has been expanded to allow the utilisation of differential expression approaches - EWCE can now handle SingleCellExperiment (SCE) objects or other Ranged SummarizedExperiment (SE) data types and as input as well as the original format, described as a single cell transcriptome (SCT) object. Deprecated & Defunct - The following functions have been renamed to use underscore in compliance with Bioconductor nomenclature: - check.ewce.genelist.inputs - cell.list.dist - bootstrap.enrichment.test - bin.specificity.into.quantiles - bin.columns.into.quantiles - add.res.to.merging.list - prepare.genesize.control.network - prep.dendro - get.celltype.table - calculate.specificity.for.level - calculate.meanexp.for.level - generate.celltype.data - generate.bootstrap.plots - generate.bootstrap.plots.for.transcriptome - fix.bad.mgi.symbols - fix.bad.hgnc.symbols - filter.genes.without.1to1.homolog - ewce.plot - cells.in.ctd - drop.uninformative.genes