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dyngen 1.0.0

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@rcannood rcannood released this 12 May 12:11
· 55 commits to master since this release
1.0.0
e0f53c9

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.

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