NEWS.md

dyngen 1.1.1

• BUG FIX wrap_dataset(): Guard examples (anndata, sce, seurat, dyno) with requireNamespace() checks so CRAN tests do not fail when optional packages are unavailable.

dyngen 1.1.0

• BREAKING CHANGE: Minimum R version bumped to 4.1.0. This enables use of the native pipe operator (|>) and lambda functions (\(x) ...) throughout.

• BUG FIX get_timings(): Use reframe() instead of summarise() to fix compatibility with dplyr >= 1.1.0.

• BUG FIX bblego_linear(): Fix broken pipe chain in doublerep2 type that caused backbone_bifurcating() examples to fail.

• MINOR CHANGE plot_simulation_expression(): Move ggrepel from Imports to Suggests, falling back to geom_text() when ggrepel is not installed. This fixes installation on older R versions where ggrepel >= 1.0.0 requires R >= 4.5.0.

• MINOR CHANGE: Replace magrittr::%>% with the native pipe |> throughout the package.

• MINOR CHANGE: Replace deprecated dplyr::do() with reframe() or group_modify() throughout the package.

• MINOR CHANGE: Replace deprecated tidyr::gather() and dplyr::one_of() with tidyr::pivot_longer() and tidyselect::any_of() respectively.

• MINOR CHANGE: Replace deprecated ggplot2::aes_string() with aes() throughout plotting functions.

• MINOR CHANGE: Replace deprecated size aesthetic with linewidth for line geoms, and use scale_linewidth_manual() accordingly.

• MINOR CHANGE: Remove internal ggforce geom_edge_loop workaround that is no longer needed since ggforce >= 0.5.0.

• MINOR CHANGE: Use .data$ pronoun in data-masking contexts and bare names in tidyselect contexts, replacing the now-deprecated .data$ usage in select() and pull() calls.

• DOCUMENTATION: Fix unescaped braces in generate_kinetics() Rd file.

• CITATION: Replace deprecated citEntry() with bibentry().

• INFRASTRUCTURE: Update GitHub Actions workflows.

• INFRASTRUCTURE: Add tidyselect to Imports.

• DOCUMENTATION: Remove unused Docker vignette.

• MINOR CHANGE as_anndata(): Replace the anndata R package (Python-based) with anndataR (Bioconductor) for constructing AnnData objects. This removes the Python dependency from the anndata output format.

dyngen 1.0.5

• MINOR CHANGE: Refactor matrix coercion thanks to Matrix 1.5-0.

• DOCUMENTATION: Remove comments from generate_dataset().

• DOCUMENTATION: Extend usage of wrap_dataset().

• DOCUMENTATION: Document outputs of combine_models() and get_timings().

• BUG FIX calculate_dimred(): Force deep copy of matrix to avoid error message: "Error in x$.self$finalize() : attempt to apply non-function".

dyngen 1.0.4

• BUG FIX plot_feature_network(): Added workaround for thomasp85/ggforce#273.

dyngen 1.0.3

• BUG FIX generate_experiment(): Return timepoint groups for experiment_synchronised().

• BUG FIX unit tests: loosen generate partitions constraints.

dyngen 1.0.2

• MINOR CHANGE generate_dataset(): Fix subplot title.

• NEW FEATURE plot_summary(): Create a dedicated function for plotting a dyngen summary.

• BUG FIX generate_cells(): Fix incorrect cell count when one of the backbone segments does not have any simulations steps (#26).

• DOCUMENTATION: Update citation to NCOMMS publication.

dyngen 1.0.1

• MINOR CHANGE .download_cacheable_file(): Check the return value of utils::download.file(), since it is possible that the download will fail with a non-zero status but not an R error.

• MINOR CHANGE kinetics_random_distributions(): Add function for providing randomised distributions.

dyngen 1.0.0

This version mostly upgrades dyngen's ease-of-use, such as better vignettes, conversion functions for working with dyngen datasets in other packages, and more useful ways of specifying platform-specific parameters (i.e. number of cores and cache location). Perhaps more excitingly, the dyngen documentation is more readable online at https://dyngen.dynverse.org!

BREAKING CHANGES

• wrap_dataset(): Now returns a list instead of a dyno object. Use as_dyno(model) or wrap_dataset(model, format = "dyno") to replicate previous behaviour.

NEW FEATURES

• Added functions for converting the dyngen output to various data formats: as_anndata() for anndata, as_sce() for SingleCellExperiment, as_seurat() for Seurat, as_dyno() for dyno, as_list() for a simple list object.

• wrap_dataset(): Added 'format' argument which allows choosing the output format (#28).

• The default number of cores used can be set by adding options(Ncpus = ...) to your Rprofile.

• The default cache folder for dyngen can be set by adding options(dyngen_download_cache_dir = ...) to your Rprofile.

• Combine similar models with different outputs using the combine_models() function.

• Store the timings throughout the dyngen execution. Extract the timings from a model using get_timings().

MAJOR CHANGES

• generate_experiment(): Map count density of reference dataset to simulation expression before sampling molecules. Parameters are available for toggling off or on the mapping of the reference library size & CPM distribution.

MINOR CHANGES

• initialise_model(): Change defaults of num_cores and download_cache_dir to getOption("Ncpus") and getOption("dyngen_download_cache_dir") respectively.

• generate_experiment(): Drastically speed up sampling of molecules.

BUG FIX

• as_dyno(): Fix drop = FALSE bug when only one cell is being sampled.

• Removed names from feature ids in feature info (unname(model$feature_info$feature_id)). Thanks @milanmlft!

DOCUMENTATION

• Added and extended vignettes:

  • Advanced: Simulating batch effects
  • Advanced: Simulating a knockout experiment
  • Advanced: Running dyngen from a docker container
  • Advanced: Constructing a custom backbone
  • Advanced: Tweaking parameters
  • Advanced: Comparison of characteristic features between dyngen and reference datasets

• Created a website at https://dyngen.dynverse.org using pkgdown.

• Shortened examples to reduce r cmd check time.

dyngen 0.4.0

MAJOR CHANGES

• wrap_dataset(): Outputted $counts now contains counts of both spliced and unspliced reads, whereas $counts_unspliced and $counts_spliced contains separated counts.

• Added a docker container containing the necessary code to run a dyngen simulation.

MINOR CHANGES

• Added logo to package.

• Clean up internal code, mostly to satisfy R CMD check.

DOCUMENTATION

• Added two vignettes.

• Expanded the README.

dyngen 0.3.0 (2020-04-06)

NEW FEATURES

• Implement knockdown / knockouts / overexpression experiments.

• Implement better single-cell regulatory activity by determining the effect on propensity values after knocking out a transcription factor.

• Implement adding noise to the kinetic params of individual simulations.

• Kinetics (transcription rate, translation rate, decay rate, ...) are based on Schwannhausser et al. 2011.

• Changed many parameter names to better explain its purpose.

MINOR CHANGES

• Fix module naming of backbones derived from backbone_branching().

• Allow to plot labels in plot_simulation_expression().

• Improve backbone_disconnected() and backbone_converging().

• Rename required columns in backbone() input data.

• Use backbone_linear() to make backbone_cyclic() randomised.

• Added a decay rate for pre-mRNAs as well.

• Kinetics: redefine the decay rates in terms of the half-life of these molecules.

• Only compute dimred if desired.

• Allow computing the propensity ratios as ground-truth for rna velocity.

BUG FIXES

• Implement fix for double positives in bblego backbones.

• Fix graph plotting mixup of interaction effects (up/down).

• Made a fix to the computation of feature_info$max_protein.

dyngen 0.2.1 (2019-07-17)

• MAJOR CHANGES: Custom backbones can be defined using backbone lego pieces. See ?bblego for more information.

• MAJOR CHANGES: Splicing reactions have been reworked to better reflect biology.

dyngen 0.2.0 (2019-07-12)

Complete rewrite from dyngen from the bottom up.

• OPTIMISATION: All aspects of the pipeline have been optimised towards execution time and end-user usability.

• OPTIMISATION: dyngen 0.2.0 uses gillespie 0.2.0, which has also been rewritten entirely in Rcpp, thereby improving the speed significantly.

• OPTIMISATION: The transcription factor propensity functions have been refactored to make it much more computationally efficient.

• OPTIMISATION: Mapping a simulation to the gold standard is more automised and less error-prone.

• FEATURE: A splicing step has been added to the chain of reaction events.

dyngen 0.1.0 (2017-04-27)

• INITIAL RELEASE: a package for generating synthetic single-cell data from regulatory networks. Key features are:

  • The cells undergo a dynamic process throughout the simulation.
  • Many different trajectory types are supported.
  • dyngen 0.1.0 uses gillespie 0.1.0, a clone of GillespieSSA that is much less error-prone and more efficient than GillespieSSA.

dyngen 0.0.1 (2016-04-04)

• Just a bunch of scripts on a repository, which creates random networks using igraph and generates simple single-cell expression data using GillespieSSA.