How-to: run EGAD

EGAD is an R package for the functional analysis of gene networks. It contains a series of tools to calculate functional properties in networks based on the guilt-by-association principle.

The functions implemented here can be applied to gene networks constructed from a range of data types (e.g., protein-protein interactions, expression, etc) across a subset of species with available functional annotations (e.g., human, mouse, zebrafish, worm, fly and yeast).

Installation

You will need the latest version of R. Then install via bioconductor.

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("EGAD")

library(EGAD)

Set up your annotations and network

Protein-protein interaction network

genelist <- make_genelist(biogrid)
gene_network <- make_gene_network(biogrid,genelist)

Aggregate co-expression network

netfile="blood.rerank.Rdata"
label="blood.rerank"
nettype= label
load(netfile)
gene_network = diag(length(genes.t))
bottom = row(gene_network) > col(gene_network)
colnames(gene_network) = genes.t
rownames(gene_network) = genes.t
gene_network[bottom] = temp
gene_network = gene_network + t(gene_network)
diag(gene_network) = 1

GO annotations

gogenes <- unique(GO.human[,2])
goterms <- unique(GO.human[,3])
annotations <- make_annotations(GO.human[,c(2,3)],gogenes,goterms)

Running GBA

aurocs_GO <- run_GBA(gene_network, annotations)

Comparing AUROCs

aurocs_GO_nv = aurocs_GO[[1]][,1]
aurocs_GO_nd = aurocs_GO[[1]][,3]
plot_density_compare(auc_GO_nv, auc_GO_nd) 
Senior Lecturer

My research interests include functional genomics, transcriptomics, X-linked disorders, sex differences in disease, X-inactivation and skewing, and meta-analysis.