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.