minimal_perturbation_lp: Assemble the LP problem for minimal perturbation.

Description Usage Arguments Value Examples

View source: R/minimal_perturbation.R

Description

Assemble the LP problem for minimal perturbation.

Usage

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minimal_perturbation_lp(ma_terms, samples, S, v_min = 0, v_max = 1000,
  min_obj = 100)

Arguments

ma_terms

A matrix or data frame containing the metabolic terms in the columns.

samples

A factor or character string with either "normal" and "disease" entries.

S

The stoichiometric matrix or a list containing one matrix for each sample.

v_min

The lower bounds for the fluxes. Either a single value for the min bounds for all reactions or a matrix/data.frame with two columns and as many rows as irreversible reactions where the columns contain the lower bounds for each factor level in 'samples'.

v_max

The upper bounds for the fluxes. Either a single value for the max bounds for all reactions or a matrix/data.frame with two columns and as many rows as irreversible reactions where the columns contain the upper bounds for each factor level in 'samples'.

min_obj

Constraints for growth rate. If a vector with two elements the first will be interpreted as the index of the objective reaction and the second value as its lower bound. If only a single value will constrain the absolute sum of fluxes (sum |v_i|) and take the value as the lower bound.

Value

A list with the following components:

coefficients

The coefficients for the equalities/inequalities in the LP. Each row denotes one equation.

type

The type of the (in)equalities. A character vector with as many entries as rows in 'coefficients' being either "equal", "less" or "larger"

bounds

A matrix with two columns containing the upper and lower variable (flux) bounds.

row_bounds

Vector containing the right sides to the (in)equalities.

obj_coefs

The objective coefficients. Containing one number for each variable.

Examples

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cdiener/dycone documentation built on Sept. 26, 2017, 9:11 p.m.