Robustness Analysis

Share:

Description

Performs robustness analysis for a given metabolic model.

Usage

1
2
  robAna(model, ctrlreact, rng = NULL,
         numP = 20, verboseMode = 1, ...)

Arguments

model

An object of class modelorg.

ctrlreact

An object of class reactId, character or integer. Specifies the control reaction – the parameter to vary.

rng

A numeric vector of length two, giving the lower and upper bound of the control reaction. If set to NULL (the default), the range will be computed by flux variability analysis for the reaction given in ctrlreact.
Default: NULL

numP

The number of points to analyse.
Default: 20

verboseMode

An integer value indicating the amount of output to stdout, see optimizer for details.
Default: 1.

...

Further arguments passed to optimizer.

Details

The function robAna performs a robustness analysis with a given model. The flux of ctrlreact will be varied in numP steps between the maximum and minimum value the flux of ctrlreact can reach. For each of the numP datapoints the followong lp problem is solved

max c^T v s.t. Sv = 0 v_j = c_k a_i <= v_i <= b_i for i = 1, ..., n, i != j

with S being the stoichiometric matrix, a_i and b_i being the lower and upper bounds for flux (variable) i. The total number of variables of the optimization problem is denoted by n. The parameter c_k is varied numP times in the range of v_i,min to v_i,max. The result of the optimization is returned as object of class optsol_robAna containing the objective value for each datapoint.

The extreme points of the range for ctrlreact are calculated via flux balance analysis (see also sysBiolAlg_fba) with the objective function being minimization and maximization of the flux through ctrlreact.

Value

An object of class optsol_robAna.

Author(s)

Gabriel Gelius-Dietrich <geliudie@uni-duesseldorf.de>

Maintainer: Claus Jonathan Fritzemeier <clausjonathan.fritzemeier@uni-duesseldorf.de>

References

Becker, S. A., Feist, A. M., Mo, M. L., Hannum, G., Palsson, B. Ø. and Herrgard, M. J. (2007) Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox. Nat Protoc 2, 727–738.

Schellenberger, J., Que, R., Fleming, R. M. T., Thiele, I., Orth, J. D., Feist, A. M., Zielinski, D. C., Bordbar, A., Lewis, N. E., Rahmanian, S., Kang, J., Hyduke, D. R. and Palsson, B. Ø. (2011) Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0. Nat Protoc 6, 1290–1307.

Bernhard Ø. Palsson (2006). Systems Biology: Properties of Reconstructed Networks. Cambridge University Press.

Examples

1
2
3
  data(Ec_core)
  rb <- robAna(Ec_core, ctrlreact = "EX_o2(e)")
  plot(rb)

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.