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Selecting the optimal trajectory inference based on a given dataset and user input 🔮

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Selecting the most optimal TI methods

This package summarises the results from the dynbenchmark evaluation of trajectory inference methods. Both programmatically and through a (shiny) app, users can select the most optimal set of methods given a set of user and dataset specific parameters.

Installing the app:

# install.packages("devtools")
devtools::install_github("dynverse/dynguidelines")

Running the app:

dynguidelines::guidelines_shiny()

See dyno for more information on how to use this package to infer and interpret trajectories.

demo

Latest changes

Check out news(package = "dynguidelines") or NEWS.md for a full list of changes.

Recent changes in dynguidelines 1.0.1 (29-06-2020)

Fixes

  • Fix get_questions(): Remove accidental reliance on list name autocompletion, which has been removed from R.

Minor changes

  • Migrate from Travis CI to Github Actions for CMD check and codecov, not yet for automated deployment.

Recent changes in dynguidelines 1.0 (29-03-2019)

Minor changes

  • Remove dyneval dependency
  • Minor changes due to changes in dynwrap v1.0

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Selecting the optimal trajectory inference based on a given dataset and user input 🔮

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