CombineZscores: Combines two Z scores for each gene

In lancour/ignition: INTEGRATION OF GENETIC ASSOCIATIONS WITH NETWORK DIFFUSION

Description

If a user has some form of gene-level significance data, for example from a genetic case control analysis, they can use this method to combine those measures with network Zscores

Usage

CombineZscores(gene.names, gene.z, net.z, gene.weight = 0.73)

Arguments

gene.names	Required. Gene identifiers for each row of the inputted Zscores. Should be the same length as gene.z and net.z.
gene.z	Required. Z scores for each gene taken from significance in a case control genetic study, for example. Note that these should be one directional Z scores, such that positive Z scores are highly significant and negative Z scores are highly insignificant.
net.z	Required. Z scores for each gene produced by GeneratePredictions
gene.weight	Optional. Defaults to 0.73 as determined in our original paper. This is the weight that is assigned to gene.z scores (and then net.z scores is assigned a weight of (1 - gene.weight)

Value

A data frame containing the combined Z scores for each gene.

Examples

data(ignition.example.edges)
data(ignition.example.genetic)
known.gene.set = c('B', 'I')
adj.matrix = CreateAdjMatrix(ignition.example.edges)
kernel = CreateKernel(adj.matrix)
net.predictions = GeneratePredictions(kernel, known.gene.set)
ignition.example.genetic$gwasz = qnorm(ignition.example.genetic$pvals, lower.tail = FALSE)
merged.data.frame = merge(net.predictions, ignition.example.genetic, by = "gene")
CombineZscores(merged.data.frame$gene,merged.data.frame$gwasz,merged.data.frame$netz)

lancour/ignition documentation built on May 29, 2019, 3:41 a.m.