calculateCooperationIndex: Calculating the metabolic competition and complementarity index

Description

Calculating the metabolic competition complementarity index among all metabolic networks

Usage

calculateCooperationIndex(g, ..., threshold = 0, p = FALSE, nperm = 1000)

Arguments

igraph that represents a metabolic network, see reconstructGsMN

...,

a list of metabolic networks or a network append to g

threshold

threshold, the cutoff of confidence score to be serve as a seed set, default is 0.2

a logical value which determins whether the calculated index is statistical or biological significant. default is FALSE

nperm,

the number of permuations of metabolic network node labes, which is used for p value calculation, default is 1000.

Value

a cooperation index matrix whose nrow and ncol is equal to the number of species to be compared, for more see details.

Details

Metabolic competition index is defined as the fraction of compounds in a species seed set of metabolic network that are alse included in its partner; However, metabolic complementarity index is the fraction of compounds in one species seed set of metabolic network appearing in the metabolic network but not in the seed set of its partner; The biosynthetic support score represents the extent to which the metabolic requirements of a potential parasitic organism can be supported by the biosynthetic capacity of a potential host. It is measured by calculating the fraction of the source components of a, in which at least one of the compounds can be found in the network of b. However, seed compounds are associated with a confidence score (1/size of SCC), so this fraction is calculated as a mormalized weighted sum.

The ith row and jth col elements of the returnd matrix represents the metabolic competition index or complementarity index of the ith network on the jth metabolic network.

Examples

Run this code

## Not run: 
# ## metabolic network reconstruction and seed set identity of sample data anno.species
# net <- lapply(anno.species,reconstructGsMN)
# interactions <- calculateCooperationIndex(net)
# ## End(Not run)