simulate_vis | R Documentation |
simulate_vis provides visualisation of the graph in addition to simulate function.
simulate_vis(
input_graph,
cycle = 1,
threshold = 0,
save = FALSE,
Competing_color = "green",
mirna_color = "orange",
Upregulation = "red",
Downregulation = "blue",
title = "GRAPH",
layout = "kk"
)
input_graph |
The graph object that processed in previous steps. |
cycle |
Optimal iteration number for gaining steady-state. |
threshold |
absolute minimum amount of change required to be considered as up/down regulated element |
save |
provides to save graph output |
Competing_color |
The color of competing elements on the graph with "green" default. |
mirna_color |
The color of miRNAs on the graph with "orange" default. |
Upregulation |
The color of Upregulated elements on the graph with "red" default. |
Downregulation |
The color of Downregulated elements on the graph with "blue" default. |
title |
Title of the given graph. |
layout |
The layout that will be used for visualisation of the graph. |
simulate_vis gives the last graph object and each iterations' image.
It gives a graph and the images of states in each iteration until the end of the simulation.
# When does the system gain steady-state conditions again?
## new_counts, the dataset that includes the current counts of nodes.
data("minsamp")
data("new_counts")
priming_graph(minsamp, Competing_expression, miRNA_expression)%>%
update_variables(new_counts)%>%
simulate_vis()
priming_graph(minsamp, Competing_expression, miRNA_expression,
aff_factor = c(seed_type,energy), deg_factor = c(region))%>%
update_variables(new_counts)%>%
simulate_vis(cycle = 12)
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