flux.shape.from.one.point: Flux shape computing from one point

Description

flux.shape.from.one.point computes flux in every dimension (corresponding to each enzyme) from a given point (vector of concentrations)

Usage

flux.shape.from.one.point(Etot_fun, A_fun, correl_fun, beta_fun=NULL, 
E_ini_fun=NULL, from.eq=TRUE, E_fun=NULL, X_fun=1, with.alpha=FALSE, grp.reg=FALSE)

Arguments

Etot_fun

Numeric. The total concentration

A_fun

Numeric vector of activities

correl_fun

Character string indicating the abbreviation of the constraint applied on the system

beta_fun

Matrix of co-regulation coefficients

E_ini_fun

Numeric vector corresponding to initial concentrations.

from.eq

Logical. Is the analyzed point is the equilibrium point ? If TRUE, flux and selection coefficients are computed from the equilibrium, else E_fun is required. Default is TRUE.

E_fun

Numeric vector of the concentrations at analysed point. If from.eq=TRUE, E_fun is ignored.

X_fun

Numeric value. Default is 1

with.alpha

Logical. For case CR, is the computing method use alpha formula (TRUE) or pass by tau computing (FALSE) ?

grp.reg

Logical. Is there is some regulation groups in beta matrix ? If TRUE, tau will not be computed and give 0.

Value

Invisible list of 6 elements:

$x : Numeric vector of all values that mutated enzymes can take, between 0 and Etot_fun, by 0.01. Length of (Etot_fun-0)*100.
$J : Numeric matrix of n columns and (Etot_fun-0)*100 rows. Each column correspond to one direction (i.e. which enzyme is "mutated") and each row to each value of flux in this direction.
$sel_disc : Numeric matrix corresponding to discrete selection coefficient. Same properties.
$sel_cont : Numeric matrix corresponding to continuous selection coefficient. Same properties.
$tau : Numeric matrix corresponding to position $\tau$ in case of regulation. Same properties.
$param : List of input parameters

Details

Every enzyme correspond to one dimension in a n-dimensional graph.

From a given resident point E_fun, each value on dimension i is considered as a possible mutant of enzyme concentration $E_i$. Every "mutants" are taken between 0 and Etot_fun by 0.01 step. In every dimension, function flux.shape.from.one.point computes flux and selection coefficient (discrete coef_sel.discrete and continuous coef_sel.continue) from this point.

E_fun (resp. E_ini_fun) is rescaled by a cross product to have sum of E_fun (resp. E_ini_fun) equal to Etot_fun.

If from.eq=TRUE, analyzed point is:

the theoretical equilibrium in case of independence "SC" and competition only "Comp";
near the theoretical equilibrium (tau=0.95) in case of positive regulation only "RegPos" (due to infinite possible values for concentrations at this point);
the effective equilibrium in other cases.

Default of E_ini_fun is NULL and corresponds to correl_fun equal to "SC" or "Comp", but in other cases (due to presence of regulation, E_ini_fun is obligatory and needs to have the same length as A_fun).

Examples

Run this code

# NOT RUN {
fsfop <- flux.shape.from.one.point(100,c(1,10,30),"SC")
# }
# NOT RUN {
# }