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sybil (version 2.2.0)

sysBiolAlg_room-class: Class "sysBiolAlg_room"

Description

The class sysBiolAlg_room holds an object of class '>optObj which is generated to meet the requirements of the ROOM algorithm.

Arguments

Objects from the Class

Objects can be created by calls of the form

sysBiolAlg(model, algorithm = "room", ...).

Arguments to ... which are passed to method initialize of class sysBiolAlg_room are described in the Details section.

Slots

wu:

Object of class "numeric" containing the upper threshold for a significant flux change, see Details below.

wl:

Object of class "numeric" containing the lower threshold for a significant flux change, see Details below.

fnc:

Object of class "integer" containing the number of reactions in the entire metabolic network (argument model to the constructor function sysBiolAlg).

fnr:

Object of class "integer" containing the number of metabolites in the entire metabolic network (argument model to the constructor function sysBiolAlg).

problem:

Object of class "optObj" containing the problem object.

algorithm:

Object of class "character" containing the name of the algorithm.

nr:

Object of class "integer" containing the number of rows of the problem object.

nc:

Object of class "integer" containing the number of columns of the problem object

fldind:

Object of class "integer" pointers to columns (variables) representing a flux (reaction) in the original network. The variable fldind[i] in the problem object represents reaction i in the original network.

alg_par:

Object of class "list" containing a named list containing algorithm specific parameters.

Extends

Class "'>sysBiolAlg", directly.

Methods

optimizeProb

signature(object = "sysBiolAlg_room"): runs optimization on the given problem object (see optimizeProb for details).

Details

The initialize method has the following arguments:

model

An object of class '>modelorg.

wtflux

A numeric vector holding an optimal wild type flux distribution for the given model. If missing, a default value is computed based on FBA. If given, arguments solver and method are used to calculate the dafault, but solverParm is not.

delta

A single numeric value giving the relative range of tolerance, see Details below. Default: 0.03.

epsilon

A single numeric value giving the absolute range of tolerance, see Details below. Default: 0.001.

LPvariant

Boolean. If TRUE, the problem object is formulated as linear program. See Details below. Default: FALSE.

LPvariant

Boolean. If TRUE, the problem object is formulated as linear program. See Details below. Default: FALSE.

absMAX

A single numerical value used as a maximum value for upper variable and contraint bounds. Default: SYBIL_SETTINGS("MAXIMUM").

cnames

A character vector giving the variable names. If set to NULL, the reaction id's of model are used. Default: NULL.

rnames

A character vector giving the constraint names. If set to NULL, the metabolite id's of model are used. Default: NULL.

pname

A single character string containing a name for the problem object. Default: NULL.

scaling

Scaling options used to scale the constraint matrix. If set to NULL, no scaling will be performed (see scaleProb). Default: NULL.

writeProbToFileName

A single character string containing a file name to which the problem object will be written in LP file format. Default: NULL.

...

Further arguments passed to the initialize method of '>sysBiolAlg. They are solver, method and solverParm.

The problem object is built to be capable to perform the ROOM algorithm with a given model, which is basically the solution of a mixed integer programming problem $$% \begin{array}{rll}% \min & \begin{minipage}[b]{5em} \[ \sum_{i=1}^n y_i \] \end{minipage} \\[2em] \mathrm{s.\,t.} & \mbox{\boldmath$Sv$\unboldmath} = 0 \\[1ex] & \alpha_i \leq v_i \leq \beta_i & \quad \forall i \in \{1, \ldots, n\} \\[1ex] & v_i - y(\beta_i - w_i^u) \leq w_i^u \\[1ex] & v_i - y(\alpha_i - w_i^l) \geq w_i^l \\[1ex] & y_i \in \{0, 1\} \\[1ex] & w_i^u = w_i + \delta |w_i| + \epsilon \\[1ex] & w_i^l = w_i - \delta |w_i| - \epsilon \\[1ex] \end{array}% $$ with \(\bold{S}\) being the stoichiometric matrix, \(\alpha_i\) and \(\beta_i\) being the lower and upper bounds for flux (variable) \(i\). The total number of fluxes of the optimization problem is denoted by \(n\). Here, \(w\) is the optimal wild type flux distribution. This can be set via the argument wtflux. If wtflux is NULL (the default), the wild type flux distribution will be calculated by a standard FBA. All variables \(y_i\) are binary, with \(y_i = 1\) for a significant flux change in \(v_i\) and \(y_i = 0\) otherwise. Thresholds determining the significance of a flux change are given in \(w^u\) and \(w^l\), with \(\delta\) and \(\epsilon\) specifying absolute and relative ranges in tolerance [Shlomi et al. 2005].

The Boolean argument LPvariant relax the binary contraints to \(0 \leq y_i \leq 1\) so that the problem becomes a linear program. The optimization can be executed by using optimizeProb.

References

Shlomi, T., Berkman, O. and Ruppin, E. (2005) Regulatory on/off minimization of metabolic flux changes after genetic pertubations. PNAS 102, 7695--7700.

See Also

Constructor function sysBiolAlg and superclass '>sysBiolAlg.

Examples

Run this code
# NOT RUN {
  showClass("sysBiolAlg_room")
# }

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