RNV.delta.all.enz: Delta at RNV for all enzymes
In SimEvolEnzCons: Simulation of Evolution of Enzyme Under Constraints

Description Usage Arguments Details Value References See Also Examples

This function computes actual mutation effect δ at RNV for each enzyme

1	RNV.delta.all.enz(E_res_fun,A_fun,N_fun,correl_fun,beta_fun=NULL,tol_fun=0.0001)

`E_res_fun`	Numeric vector of enzyme concentrations (resident)
`A_fun`	Numeric vector of activities
`N_fun`	Numeric. Population size
`correl_fun`	Character string indicating the abbreviation of the constraint applied on the system
`beta_fun`	Matrix of co-regulation coefficients
`tol_fun`	Numeric and positive value. Accuracy for delta bounds. Default is `0.0001`

The Range of Neutral Variations (RNV) are mutant concentration values such as coefficient selection is between 1/(2N) and -1/(2N).

Inferior (resp. superior) bound of RNV corresponds to selection coefficient equal to -1/(2N) (resp. 1/(2N)).

Function RNV.delta.all.enz computes the actual mutation effect delta_i at RNV bounds, where i is the enzyme targeted by the mutation.

Depending on applied constraints correl_fun, it exists 1 or 2 RNV. In case of independence ("SC") or positive regulation between all enzymes ("RegPos"), flux has no limit and there is only one RNV. In other cases (competition and/or negative regulation), because flux can reach a maximum, there is two RNV: a "near" one, for small mutations, and a "far" one for big mutations that put mutants in the other side of flux dome.

Known bug

Due to use of range_delta to limit search area, output δ is computed to have mutant concentration between 0 and sum(E_res_fun) (resident total concentration). If δ is too high (mutant concentration over resident total concentration), output δ could be NA rather than a numeric value. This case might happen when N_fun is too low and correl_fun="SC" or "RegPos" (no limit on total concentration),

List of n elements, one for each enzyme i considering that i is targeted by the mutation.

For each element of the list, we have a vector of length 2 or 4, depending on applied constraint correl_fun. Values of this vector are:

delta_i value for inferior bounds of the near RNV
delta_i value for superior bounds of the near RNV
delta_i value for inferior bounds of the far RNV (if exists)
delta_i value for superior bounds of the far RNV (if exists)

If superior bound is not accessible, value is NA.

Note that n is the number of enzymes, which is the length of E_ini_fun.

Coton et al. (2021)

delta at RNV bounds is obtained by nullify the expression in odd.discrete.sel.coef.

Er <- c(30,30,30)
A <- c(1,10,30)
beta <- matrix(c(1,10,5,0.1,1,0.5,0.2,2,1),nrow=3)
correl <- "CRPos"
N <- 1000

RNV.delta.all.enz(Er,A,N,correl,beta)

correl <- "SC"
RNV.delta.all.enz(Er,A,N,correl)