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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 (29-03-2019)

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

Recent changes in dynguidelines 0.3.2 (17-12-2018)

New features

  • Enable automatic deployment via travis-ci

Fixes

  • Justify lens buttons
  • Use master branch of dynwrap instead of devel
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