Each synthetic dataset is based on some characteristics of some real datasets. These characteristics include:
- The number of cells and features
- The number of features which are differentially expressed in the trajectory
- Estimates of the distribution of the library sizes, average expression, dropout probabilities, … estimated by Splatter.
Here we estimate the parameters of these “platforms” and use them to simulate datasets using different simulators. Each simulation script first creates a design dataframe, which links particular platforms, different topologies, seeds and other parameters specific for a simulator.
The data is then simulated using wrappers around the simulators (see /package/R/simulators.R), so that they all return datasets in a format consistent with dynwrap.
| # | script/folder | description |
|---|---|---|
| 1 | 📄estimate_platform.R |
Estimation of the platforms from real data done by dynbenchmark::estimate_platform |
| 2a | 📄simulate_dyngen_datasets.R |
dyngen, simulations of regulatory networks which will produce a particular trajectory |
| 2b | 📄simulate_prosstt_datasets.R |
PROSSTT, expression is sampled from a linear model which depends on pseudotime |
| 2c | 📄simulate_splatter_datasets.R |
Splatter, simulations of non-linear paths between different states |
| 2d | 📄simulate_dyntoy_datasets.R |
dyntoy, simulations of toy data using random expression gradients in a reduced space |
| 3 | 📄gather_metadata.R |
Gathers some metadata about all the synthetic datasets |
| 4 | 📄dyngen_samplers_table.R |