dyngen (version 0.4.0)

generate_tf_network: Generate a transcription factor network from the backbone

Description

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.

Usage

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.

Examples

# NOT RUN {
model <- 
  initialise_model(
    backbone = backbone_bifurcating(),
    tf_network = tf_network_default(min_tfs_per_module = 1L)
  ) %>%
  generate_tf_network()
  
plot_feature_network(model)
  
# }
# NOT RUN {
model <- model %>%
  generate_feature_network() %>%
  generate_kinetics() %>%
  generate_gold_standard() %>%
  generate_cells() %>%
  generate_experiment()
  
dataset <- wrap_dataset(model)
# }
# NOT RUN {
# }