initialise_model {dyngen} | R Documentation |
Initial settings for simulating a dyngen dataset
Description
Initial settings for simulating a dyngen dataset
Usage
initialise_model(
backbone,
num_cells = 1000,
num_tfs = nrow(backbone$module_info),
num_targets = 100,
num_hks = 50,
distance_metric = c("pearson", "spearman", "cosine", "euclidean", "manhattan"),
tf_network_params = tf_network_default(),
feature_network_params = feature_network_default(),
kinetics_params = kinetics_default(),
gold_standard_params = gold_standard_default(),
simulation_params = simulation_default(),
experiment_params = experiment_snapshot(),
verbose = TRUE,
download_cache_dir = getOption("dyngen_download_cache_dir"),
num_cores = getOption("Ncpus") %||% 1L,
id = NULL
)
Arguments
backbone |
The gene module configuration that determines the type of dynamic
process being simulated. See |
num_cells |
The number of cells to sample. |
num_tfs |
The number of transcription factors (TFs) to generate. TFs are the main drivers of the changes that occur in a cell. TFs are regulated only by other TFs. |
num_targets |
The number of target genes to generate. Target genes are regulated by TFs and sometimes by other target genes. |
num_hks |
The number of housekeeping genes (HKs) to generate. HKs are typically highly expressed, and are not regulated by the TFs or targets. |
distance_metric |
The distance metric to be used to calculate the distance
between cells. See |
tf_network_params |
Settings for generating the TF network with
|
feature_network_params |
Settings for generating the feature network with
|
kinetics_params |
Settings for determining the kinetics of the feature network
with |
gold_standard_params |
Settings pertaining simulating the gold standard with
|
simulation_params |
Settings pertaining the simulation itself with |
experiment_params |
Settings related to how the experiment is simulated with
|
verbose |
Whether or not to print messages during the simulation. |
download_cache_dir |
If not |
num_cores |
Parallellisation parameter for various steps in the pipeline. |
id |
An identifier for the model. |
Value
A dyngen model.
See Also
dyngen on how to run a complete dyngen simulation
Examples
model <- initialise_model(
backbone = backbone_bifurcating(),
num_cells = 555,
verbose = FALSE,
download_cache_dir = "~/.cache/dyngen"
)