generate_feature_network: Generate a target network

In dyngen: A Multi-Modal Simulator for Spearheading Single-Cell Omics Analyses

Generate a target network

Description

generate_feature_network() generates a network of target genes that are regulated by the previously generated TFs, and also a separate network of housekeeping genes (HKs). feature_network_default() is used to configure parameters pertaining this process.

Usage

generate_feature_network(model)

feature_network_default(
  realnet = NULL,
  damping = 0.01,
  target_resampling = Inf,
  max_in_degree = 5
)

Arguments

model	A dyngen intermediary model for which the transcription network has been generated with generate_tf_network().
realnet	The name of a gene regulatory network (GRN) in realnets. If NULL, a random network will be sampled from realnets. Alternatively, a custom GRN can be used by passing a weighted sparse matrix.
damping	A damping factor used for the page rank algorithm used to subsample the realnet.
target_resampling	How many targets / HKs to sample from the realnet per iteration.
max_in_degree	The maximum in-degree of a target / HK.

Value

A dyngen model.

See Also

dyngen on how to run a complete dyngen simulation

Examples

model <- 
  initialise_model(
    backbone = backbone_bifurcating(),
    feature_network = feature_network_default(damping = 0.1)
  )
  

data("example_model")
model <- example_model %>%
  generate_tf_network() %>% 
  generate_feature_network()

plot_feature_network(model)

dyngen documentation built on Oct. 12, 2022, 5:06 p.m.