generate_tf_network() generates the transcription factors (TFs) that drive the dynamic process a cell undergoes. tf_network_default() is used to configure parameters pertaining this process.

generate_tf_network(model)

tf_network_default(
  min_tfs_per_module = 1L,
  sample_num_regulators = function() 2,
  weighted_sampling = FALSE
)

Arguments

model

A dyngen initial model created with initialise_model().

min_tfs_per_module

The number of TFs to generate per module in the backbone.

sample_num_regulators

A function to generate the number of TFs per module each TF will be regulated by.

weighted_sampling

When determining what TFs another TF is regulated by, whether to perform weighted sampling (by rank) or not.

Value

A dyngen model.

See also

dyngen on how to run a complete dyngen simulation

Examples

model <- initialise_model( backbone = backbone_bifurcating() ) model <- model %>% generate_tf_network()
#> Generating TF network
# \donttest{ plot_feature_network(model)
# }