Description Usage Arguments Details Value References See Also Examples
View source: R/RNV.delta.all.enz.R
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 |
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
.
1 2 3 4 5 6 7 8 9 10 | 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)
|
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