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

In cdiener/dycone: dycone - analyze the dynamic landscape of metabolome data

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

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

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.