geneScoring: The core function to score a gene

Description Usage Arguments Value Author(s) References Examples

Description

This function is the core function to test whether a query gene is statistically associated with a set of seed genes.

Usage

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geneScoring(Nseed, Cg, Pfcutoff = 0.1)

Arguments

Nseed

Number of seed genes

Cg

Pre-calcuated weight for this gene

Pfcutoff

Percentage of top genes considered, should be less than 0.1.

Value

p-value

Author(s)

Jiantao Shi

References

Jiantao Shi: NetGPA, a package for network-based gene prioritization analysis.

Examples

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# load package and data
library("NetGPA")
data("Example_NetGPA")

# load data base
data(text_2006_12_NetGPA)

# Compare FGF pathway and a random gene set
exampleSeedFGFR <- Example_NetGPA$Cancer_GeneSet[["SIGNALING_BY_FGFR"]]

pGenes <- intersect(exampleSeedFGFR, colnames(text_2006_12_NetGPA))
rGenes <- sample(colnames(text_2006_12_NetGPA), length(pGenes)) 

res    <- NetGPA(as.list(pGenes), pGenes, text_2006_12_NetGPA, progressBar = FALSE)
pTable <- res$queryTable
pTable$group <- "Pathway"

res    <- NetGPA(as.list(rGenes), rGenes, text_2006_12_NetGPA, progressBar = FALSE)
rTable <- res$queryTable
rTable$group <- "Random"

mT <- rbind(pTable, rTable)

boxplot(-log10(queryP)~group, data = mT, ylab = "-log10(p-value)")

JiantaoShi/NetGPA documentation built on May 28, 2019, 12:43 p.m.