Simulation {CoRegFlux} | R Documentation |
Simulation using Dynamic Flux balance analysis over time as in varma
Simulation(model, time = c(0, 1), metabolites, initial_biomass, biomass_flux_index = CoRegFlux::get_biomass_flux_position(model), coregnet = NULL, regulator_table = NULL, gene_table = NULL, gene_state_function = NULL, time_step_fba_bounds = NULL, softplus_parameter = 0, aliases = NULL)
model |
An object of class modelOrg, the genome-scale metabolic model (GEM). |
time |
Timepoints at which the flux balance analysis solution will be evaluated. |
metabolites |
A data.frame containing the extraneous metabolites and the initial concentrations |
initial_biomass |
The value of the biomass at the beginning of the simulation |
biomass_flux_index |
index of the flux corresponding to the biomass reaction. |
coregnet |
Object of class CoRegNet, containing the regulatory and coregulatory interactions. |
regulator_table |
A data.frame containing 3 columns: "regulator", "influence","expression" containing respectively the name of a TF present in the CoRegNet object as a string, its influence in the condition of interest as a numerical and an expression factor of 0 for a KO, or an integer >1 for an overexpression |
gene_table |
A data.frame containing 2 columns: "gene" and "expression" containing respectively the name of a gene present in the modelOrg as a string and an expression factor of 0 for a KO, or an integer >1 for an overexpression |
gene_state_function |
Function to obtain the gene state for a given subset of gene |
time_step_fba_bounds |
Bounds for the fba problem at each time point, overrides any other form of constraining for a given flux. |
softplus_parameter |
the softplus parameter identify through calibration |
aliases |
Optional. A data.frame containing the gene names currently used in the network under the colname "geneName" and the alias under the colnames "alias" |
The simulation function allows the user to run several kind of simulations based on the provided arguments. When providing only the GEM, time, initial biomass and the metabolites, a classical dFBA is carried out. To integrate the gene expression to the GEM, the gene_state_function must be provided while if the user wants to simulate a TF knock-out or overexpression, then a coregnet object and the regulator table should also be provided. See the vignette and quick-user guide for more examples.
Return a list containing the simulation information such as the objective_history, fluxes_history, met_concentration_history, biomass_history
data("SC_GRN_1") data("SC_EXP_DATA") data("SC_experiment_influence") data("iMM904") data("aliases_SC") data("PredictedGeneState") metabolites<-data.frame("name"=c("D-Glucose","Glycerol"), "concentrations"=c(16,0)) result_without_any_constraint<-Simulation(iMM904,time=seq(1,10,by=1), metabolites, initial_biomass=0.45, aliases = aliases_SC) GeneState<-data.frame("Name"=names(PredictedGeneState), "State"=unname(PredictedGeneState)) result<-Simulation(iMM904,time=seq(1,10,by=1), metabolites, initial_biomass=0.45, gene_state_function=function(a,b){GeneState}, aliases = aliases_SC) result$biomass_history