simulate: Utilizes the change in expression value/s as triggering.

Description Usage Arguments Details Value Examples

View source: R/simulate.R

Description

simulate function uses the change in expression value/s as triggering.

Usage

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simulate(input_graph, cycle = 1, threshold = 0, knockdown = TRUE)

Arguments

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

knockdown

specifies gene knockdown with default TRUE

Details

The steady-state conditions of the system are disturbed after the change in the graph (with update_how or update_variables). In this case, the system tend to be steady state again. The arrangement of competetive profiles of the targets continue until all nodes are updated and steady-state nearly. Note that, If 'how' argument is specified as '0', *simulate()* and *update_how()* functions process the variables to knockdown of specified gene with default 'knockdown = TRUE' and knocked down competing RNA is kept at zero. However, if 'knockdown= FALSE' argument is applied, competing RNA which has initial expression level of zero is allowed to increase or fluctuate during calculations.

Value

The graph.

Examples

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data('minsamp')
data('new_counts')

## new_counts, the dataset that includes the current counts of nodes.

priming_graph(minsamp, Competing_expression, miRNA_expression)%>%
  update_variables(new_counts)%>%
  simulate()

priming_graph(minsamp, Competing_expression, miRNA_expression,
       aff_factor = c(seed_type,energy), deg_factor = region)%>%
  update_variables(new_counts)%>%
  simulate(cycle = 3)

selcenari/ceRNAnetsim documentation built on Nov. 27, 2020, 1:27 a.m.