Awesome
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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.
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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