Description Usage Arguments Value Author(s) Examples
View source: R/GetFoldChanges.R
Calculate the fold change equivalent for the final state of two simulated datasets e.g. with vs without influx.
1 2 | GetFoldChanges(ReferenceDataObject, AlternativeDataObject,
plot_out = TRUE, bw = 0.05, plot_title = NULL)
|
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. |
A list with: the time vector and a matrix with the simulated data. (1 row per node)
Charlie Beirnaert, charlie.beirnaert@uantwerpen.be
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | 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)
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