evaluatePopulationSignficance: Determine the significance of a population of...

In princeew/PFFindR: Identify, evaluate, and visualize enriched Prix Fixe subnetworks

Description

Given a population (i.e., list) of PrixFixeNetworks calculate the mean network density across the population. Compare the mean density to a distribution of random network densities.

Usage

evaluatePopulationSignficance(pf_data, population, num_trials = 10)

Arguments

pf_data	a PFData object generated by PFDataLoader
population	a list of PrixFixeNetwork objects
num_trials	The number of random trials to generate the null distribution

Value

a p-value

Calculating the null model distribtion

In order to calculate the null model we want to sample genes from the total co-function network to generate random loci. In order to mitigate problems with node-degree effects, we first categorically bin the cofunction network and then replace original loci genes with a random choice from the same bin.

Calculating the p-value

The p-value here is defined as the fraction of null model densities that are greater than the average true network density.

Examples

## Not run: 
# load example PFData (FA genes)
data(PF_FanconiAnemia)
# generate population of subnetworks
population <- initializePopulation(PF_FanconiAnemia, population_size=100, "true_members")
# evaluate population significance
population_significance <- evaluatePopulationSignificance(pf_data, population, 100)

## End(Not run)

princeew/PFFindR documentation built on Dec. 31, 2020, 2:06 a.m.