fva: Performs flux variance analysis for a given objective...

Description Usage Arguments Value Examples

Description

Performs flux variance analysis for a given objective reaction. Thus, FVA obtains lower and upper bounds for the fluxes under a given (sub-)optimal solution.

Usage

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fva(obj, S, alpha = 1, v_min = 0, v_max = 1)

Arguments

obj

The objective reaction, whose flux will be be maximized. Can be any of the following three:

  • A list containing at least the four vectors S, P, N_S, and N_P, which which contain the names of substrates and products and their respective stochiometries.

  • A unnamed vector containing the corresponding column in the stochiometric matrix.

  • A named vector containing only the non-zero entries in the respective column of the stochiometric matrix being named by their respective metabolite.

  • A single integer indicating which column of the stoichiometric contains the objective reaction.

S

The stochiometrix matrix to be used (must be irreversible).

alpha

A positive scalar <=1. FVA is performed assuming that the optimal solution can not be less than alpha*opt.

v_min

Lower bounds for the reaction fluxes. Can be a single value or a vector containing one value for each reaction.

v_max

Upper bounds for the reaction fluxes. Can be a single value or a vector containing one value for each reaction.

Value

A data frame with two columns, min and max, denoting the respective minimum and maximum fluxes for each reaction.

Examples

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S <- matrix(c(1, 0, -2, 1), ncol = 2)
rownames(S) <- c("A", "B")
fva(c(B = -1), S=S)

cdiener/dycone documentation built on May 13, 2019, 2:41 p.m.