RCPA (version 0.2.6)

runPathwayAnalysis: Topology-based Pathway Analysis

Description

This function performs patwhay analysis using SPIA, CePaORA, and CePaGSA methods.

Usage

runPathwayAnalysis(
  summarizedExperiment,
  network,
  method = c("spia", "cepaORA", "cepaGSA"),
  SPIAArgs = list(all = NULL, nB = 2000, verbose = TRUE, beta = NULL, combine = "fisher",
    pThreshold = 0.05),
  CePaORAArgs = list(bk = NULL, cen = c("equal.weight", "in.degree", "out.degree",
    "betweenness", "in.reach", "out.reach"), cen.name = c("equal.weight", "in.degree",
    "out.degree", "betweenness", "in.reach", "out.reach"), iter = 1000, pThreshold =
    0.05),
  CePaGSAArgs = list(cen = c("equal.weight", "in.degree", "out.degree", "betweenness",
    "in.reach", "out.reach"), cen.name = c("equal.weight", "in.degree", "out.degree",
    "betweenness", "in.reach", "out.reach"), nlevel = "tvalue_abs", plevel = "mean", iter
    = 1000)
)

Value

A dataframe of pathway analysis result, which contains the following columns

• ID: The ID of the gene set

• p.value: The p-value of the gene set

• pFDR: The adjusted p-value of the gene set using the Benjamini-Hochberg method

• score: The enrichment score of the gene set

• normalizedScore: The normalized enrichment score of the gene set

• sampleSize: The total number of samples in the study

• name: The name of the gene set

• pathwaySize: The size of the gene set

Arguments

summarizedExperiment

The generated SummarizedExpriment object from DE analysis result.

network

The pathways network object.

method

The pathway analsyis method, including SPIA, cepaORA, and cepaGSA.

SPIAArgs

A list of other passed arguments to spia. See spia function.

CePaORAArgs

A list of other passed arguments to CePaORA. See CePa function.

CePaGSAArgs

A list of other passed arguments to CePaGSA. See CePa function.

Examples

# \donttest{
library(RCPA)
RNASeqDEExperiment <- loadData("RNASeqDEExperiment")
spiaNetwork <- loadData("spiaNetwork")
cepaNetwork <- loadData("cepaNetwork")

spiaResult <- runPathwayAnalysis(RNASeqDEExperiment, spiaNetwork, method = "spia")
cepaORAResult <- runPathwayAnalysis(RNASeqDEExperiment, cepaNetwork, method = "cepaORA")
# }