sampleFluxEnsemble: Sample a posterior ensemble of feasible flux configurations...
In hettling/BiGGR: Constraint based modeling in R using metabolic reconstruction databases

Description Usage Arguments Value Note Author(s) References See Also Examples

This function uses a Markov chain Monte Carlo algorithm to sample an ensemble of flux vectors that satisfy the constrained posed by the model. To account for inaccuracy in certain fluxes, the user can specify uncertain fluxes and provide standard deviations. The function uses the xsample function from the package limSolve.

1	sampleFluxEnsemble(model, uncertain.vars=NULL, iter=3000, ...)

`model`	Either an object of class LIM as generated by `createLIMFromBiGG` or `createLIMFromSBML`, a `character` with the full path to a LIM model file or an object of class `Model` from the package `rsbml`
`uncertain.vars`	An object of class `data.frame` containing three columns: 1. The identifier for the flux(es) to be constrained within its uncertainty limits (linear combinations of fluxes e.g. F1 + F2 - F3 are also allowed), 2. the value of the constrained flux and 3. its standard deviation. If uncertain.vars is NULL, the ensemble is sampled without approximate equality constraints
`iter`	Number of iterations in the Monte Carlo procedure
`...`	Additional arguments to `xsample`

A matrix with the posterior flux ensemble. The number of columns is equal to the number of fluxes in the provided model, the number of rows is equal to iter.

This function is a wrapper for the function xsample.

Hannes Hettling

K. V. den Meersche, K. Soetaert, and D. V. Oevelen: xsample(): An R function for sampling linear inverse problems,Journal of Statistical Software, Code Snippets, vol. 30, pp. 1-15, 4 2009.

xsample

##get example model file of glycolysis and TCA cycle 
limfile.path <- system.file("extdata", "Glycolysis_TCA.LIM",
package="BiGGR")

##Specify uncertainty of fluxes "R_GLCt1r", "R_O2t"
uncertain.vars <- data.frame(var=c("R_GLCt1r", "R_O2t"), value=c(0.4, 2.4), sd=c(0.08, 0.48))
##sample ensemble
ensemble <- sampleFluxEnsemble(limfile.path, uncertain.vars)

##Example in which linear combination of fluxes is constrained
atp.reacs <- "R_ATPS4m - R_NDPK1m - R_HEX1 - R_PFK - R_PGK + R_PYK"
uncertain.vars <- data.frame(var=atp.reacs, value=10, sd=1)
ensemble <- sampleFluxEnsemble(limfile.path, uncertain.vars)