FVA
Flux variability analysis
FVA class
Performs Flux Variability Analysis (FVA). It calculates the minimum and maximum flux values for each reaction in a metabolic network while satisfying certain constraints;
It is based on the paper of (Gudmundsson and Thiele, Bioinformatics 2010). See also:
Steinn Gudmundsson & Ines Thiele, Computationally efficient flux variability analysis, BMC Bioinformatics, volume 11, Article number: 489 (2010), https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-489
Input
Output
Configuration
biomass_optimization
Biomass optimization
stringmaximize minimize fluxes_to_maximize
The fluxes to maximize
listfluxes_to_minimize
The fluxes to minimize
listsolver
The optimization solver. It is recommended to use `quad`. Other solvers are in `beta` versions.
stringquad highs-ds highs-ipm highs interior-point quadrelax_qssa
True to relaxing the quasi-steady state assumption (QSSA) constrain (`quad` solver is used). False otherwise.
boolqssa_relaxation_strength
Used only if the QSSA is relaxed. The higher is the strength, the stronger is the QSSA. Hint: Set to the number of reactions to have strong QSSA contrain.
floatparsimony_strength
Set True to perform parsimonious FBA (pFBA). In this case the quad solver is used. Set False otherwise
floatnumber_of_simulations
Set the number of simulations to perform. You must provide at least the same number of measures in the context. By default, keeps all simulations.
intgamma
γ determines whether the analysis is conducted with respect to suboptimal network states (where 0 ≤ γ < 1) or to the optimal state (where γ = 1). A value of 0.9 implies that the objective must be at least 90% of its maximum.
float1