Initial settings for simulating a dyngen dataset

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,
num_cores = getOption("Ncpus") %||% 1L,
id = NULL
)

## Arguments

backbone The gene module configuration that determines the type of dynamic process being simulated. See list_backbones() for a full list of different backbones available in this package. The number of cells to sample. 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. The number of target genes to generate. Target genes are regulated by TFs and sometimes by other target genes. The number of housekeeping genes (HKs) to generate. HKs are typically highly expressed, and are not regulated by the TFs or targets. The distance metric to be used to calculate the distance between cells. See dynutils::calculate_distance() for a list of possible distance metrics. Settings for generating the TF network with generate_tf_network(), see tf_network_default(). Settings for generating the feature network with generate_feature_network(), see feature_network_default(). Settings for determining the kinetics of the feature network with generate_kinetics(), see kinetics_default(). Settings pertaining simulating the gold standard with generate_gold_standard(), see gold_standard_default(). Settings pertaining the simulation itself with generate_cells(), see simulation_default(). Settings related to how the experiment is simulated with generate_experiment(), see experiment_snapshot() or experiment_synchronised(). Whether or not to print messages during the simulation. If not NULL, temporary downloaded files will be cached in this directory. Parallellisation parameter for various steps in the pipeline. An identifier for the model.

## Value

A dyngen model.

model <- initialise_model(