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Toy synthetic data for testing and prototyping trajectory inference methods 🎲

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dyntoy

dyntoy simulates single-cell expression data in which a single-cell trajectory is present. Even though the model to generate the data is very simplistic (and far from realistic), it can simulate very complex trajectory models, such as large trees, convergences and loops.

As the data is relatively easy, it can be used to quickly test and prototype a TI method. However, for more realistic synthetic data, check out our dyngen package.

Installation

Install using devtools:

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

Example

dyntoy contains some pre-generated toy data within the toy_datasets data object:

data("toy_datasets", package = "dyntoy")

Data can be generated using generate_dataset:

library(dyntoy)
dataset <- generate_dataset(
  model = model_bifurcating(),
  num_cells = 1000,
  num_features = 1000
)

dataset$milestone_network
#> # A tibble: 3 x 4
#>   from  to    length directed
#>   <chr> <chr>  <dbl> <lgl>   
#> 1 M3    M4    0.191  TRUE    
#> 2 M1    M3    0.417  TRUE    
#> 3 M3    M2    0.0432 TRUE

Related work

Latest changes

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

Recent changes in dyntoy 1.0.0 (unreleased)

  • Initial release of dyntoy

  • Generates simple toy datasets containg trajectories, with expression, RNA velocity, differentially expressed features

Dynverse dependencies

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Toy synthetic data for testing and prototyping trajectory inference methods 🎲

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