pGRN {pGRN}

pGRN: creates gene regulatory network based on single cell pseudotime information

Description

Given single cell matrix and pseudotime, construct gene regulatory network (GRN)

Usage

pGRN(
  expression_matrix,
  pseudotime_list,
  method = "DTW",
  slide_window_size = 20,
  slide_step_size = 10,
  centrality_degree_mod = "out",
  components_mod = "weak",
  network_min_genes = 10,
  quantile_cutoff = 5,
  order = 1,
  cores = 1
)

Arguments

expression_matrix

expression matrix data

pseudotime_list

list of pseudotime

method

method for GRN construction: DTW, granger

slide_window_size

sliding window size

slide_step_size

sliding window step size

centrality_degree_mod

(for DTW method) mode of centrality degree for popularity calculation

components_mod

(for DTW method) mode of sub-network extraction methods (weak or strong)

network_min_genes

minimal number of gene elements required for extracted sub-networks

quantile_cutoff

an integer value (1-99) for quantile cutoff

order

(for granger method) integer specifying the order of lags to include in the auxiliary regression

cores

number of cores for parallel computing

Value

a list of tabl_graph objects

Examples

example_data <- pGRNDB
expression_matrix <- example_data[["expression"]]
pseudotime_list <- example_data[["ptime"]]$PseudoTime

# try DTW method
nets <- pGRN(expression_matrix,
             pseudotime_list, 
             method= "DTW",
             quantile_cutoff=50,
             cores=1)
plot_network(nets[[1]])

# plot the network interactively
plot_network_i(nets[[1]])