MetaboLouise (version 1.0.0)

GetFoldChanges: GetFoldChanges

Description

Calculate the fold change equivalent for the final state of two simulated datasets e.g. with vs without influx.

Usage

GetFoldChanges(ReferenceDataObject, AlternativeDataObject,
  plot_out = TRUE, bw = 0.05, plot_title = NULL)

Arguments

ReferenceDataObject

The reference data object (result from DataSimulateR function)

AlternativeDataObject

The alternative situation data object (result from DataSimulateR function)

plot_out

Whether to plot the Fold change distribution.

bw

The bw for the density plot.

plot_title

Optional plot title.

Value

A list with: the time vector and a matrix with the simulated data. (1 row per node)

Examples

# NOT RUN {
Nmetabos <- 20L
Nrates <- 10L

Network <- NetworkCreateR(N = Nmetabos, BA_power = 0.5, BA_mValue = 4)

Rate_function <- RateFunctionBuildR(type = "sigmoid")

rate_vector <- round(5*runif(Nrates))

rate_mapping <- Network
active_rates <- which(Network == 1, arr.ind = TRUE)
for(rr in 1:nrow(active_rates)){
    rate_mapping[active_rates[rr,1], active_rates[rr,2]] <- sample(seq_along(rate_vector), size = 1)
    }
    
 No_influx <- DataSimulateR(NetworkMatrix = Network, dT = 0.01, Tstart = 0, Tstop = 3, 
                            T0_nodes = 100, rate_vector = rate_vector, rate_mapping = rate_mapping, 
                            RateFunctionObject = Rate_function, plot_out = FALSE)
                            
 influx_vector <- c(rep(1,10),rep(0,Nmetabos-10))                           
 With_influx <- DataSimulateR(NetworkMatrix = Network, dT = 0.01, Tstart = 0, Tstop = 3,
                              T0_nodes = 100, influx_vector = influx_vector, influx_Tframe = 0.5,
                              rate_vector = rate_vector, rate_mapping = rate_mapping, 
                              RateFunctionObject = Rate_function, plot_out = FALSE)

GetFoldChanges(ReferenceDataObject = No_influx, AlternativeDataObject = With_influx)

# }