generate_edge_weight: Compute edge weight

In aaronwolen/dmGWAS2: A fork of EW_dmGWAS

Description

generate_edge_weight computes differential gene co-expression (i.e., the change of gene co-expression between case and control samples) to infer the edge weight of PPI network. generate_edge_weight is generally called by generate_graph. Typically users do not need to call it.

Usage

generate_edge_weight(expr1, expr2, network, geneweight)

Arguments

expr1	A data frame containing gene expression data from case samples. The first column is gene identifier (should be coordinate with the node symbol used in PPI
expr2	A data frame containing gene expression data from control samples. The first column should be the same as expr1
network	A data frame containing a symbolic edge list of the PPI network
geneweight	A data frame containing two columns: the first is unique gene identifier (should be coordinate with the node symbol used in PPI); the second is gene-based p-value derived from GWAS

Value

A co-expression matrix is returned

Examples

## Not run: 
edgeweight <- generate_edge_weight(expr1, expr2, network, geneweight)

## End(Not run)

aaronwolen/dmGWAS2 documentation built on May 10, 2019, 4:04 a.m.