exp2flux: Convert gene expression data to FBA fluxes

In gibbslab/ex2flux: Convert Gene EXPression Data to FBA FLUXes

Description

This function calculates the flux boundaries for each reaction based in their associated GPR. The value es obtained as follows: When two genes are associated by an AND operation according to the GPR rule, a min function is applied to their associated expression values. In the AND case, downregulated genes alter the reaction acting as enzyme formation limitant due two are required to complex formation. In turn, when the genes are associated by an OR rule, each one of then can code an entire enzyme to act as reaction catalyst. In this case, a sum function is applied for their associated expression values.To missing gene expression values, the function assigns one of: 'min', '1q', 'mean', 'median', '3q', or 'max' expression value calculated from the genes associated to the same metabolic pathway. In case of not possible pathway assignment to a gene, the value is calculated from all gene expression values. The fluxes boundaries of exchange reactions are not modified.

Usage

exp2flux(model, expression, organism = NULL, typeID = NULL,
  missing = "mean", scale = FALSE)

Arguments

model	A valid model for the 'sybil' package.
expression	A valid ExpressionSet object (one by treatment).
organism	A valid organism identifier for the KEGG database. List of valid organism identifiers are available in: http://rest.kegg.jp/list/organism.
typeID	A string to define the type of ID used in GPR's. One of "entrez" or "kegg" must be given.
missing	A character string specifying the value to be used in missing cases; must be one of 'min', '1q', 'mean', 'median', '3q', or 'max'
scale	A boolean value to specify if data must be scaled to assign a value of 1000 as max.

Author(s)

Daniel Camilo Osorio <[e-mail]> and Kelly Botero <[e-mail]>

Examples

## Not run: 
# Loading a model
library("sybil")
library("Biobase")

# Original model:
data("Ec_core")

# Original model evaluation:
optimizeProb(Ec_core)

# Generating simulated expressionSets
expressionData <- matrix(data = runif(3*length(Ec_core@allGenes),min = 1,max = 100),
                         nrow = length(Ec_core@allGenes),
                         dimnames = list(c(Ec_core@allGenes),c()))
expressionData <- ExpressionSet(assayData = expressionData)

# Applying exp2flux
Ec_coreGE <- exp2flux(model = Ec_core,
                      expression = expressionData,
                      missing = "mean")
# Evaluating exp2flux model
optimizeProb(Ec_coreGE)
                
## End(Not run)

gibbslab/ex2flux documentation built on May 17, 2019, 4:19 a.m.