runGeneSetAnalysis | R Documentation |
This function performs gene set enrichment analysis using either ORA, fgsea, GSA, ks, or wilcox approaches.
runGeneSetAnalysis(
summarizedExperiment,
genesets,
method = c("ora", "fgsea", "gsa", "ks", "wilcox"),
ORAArgs = list(pThreshold = 0.05),
FgseaArgs = list(sampleSize = 101, minSize = 1, maxSize = Inf, eps = 1e-50, scoreType =
"std", nproc = 0, gseaParam = 1, BPPARAM = NULL, nPermSimple = 1000, absEps = NULL),
GSAArgs = list(method = "maxmean", random.seed = NULL, knn.neighbors = 10, s0 = NULL,
s0.perc = NULL, minsize = 15, maxsize = 500, restand = TRUE, restand.basis =
"catalog", nperms = 200, xl.mode = "regular", xl.time = NULL, xl.prevfit = NULL)
)
summarizedExperiment |
The generated SummarizedExpriment object from DE analysis result. |
genesets |
The gene sets definition, ex. KEGG genesets from getGeneSets function. |
method |
The gene set enrichment analsyis method, including ORA, fgsea, GSA, ks, and wilcox. |
ORAArgs |
A list of other passed arguments to ORA. pThreshold is used as p.value cutoff to pick DE genes. |
FgseaArgs |
A list of other passed arguments to fgsea. See fgsea function. |
GSAArgs |
A list of other passed arguments to GSA. See GSA function. |
A dataframe of gene set enrichment 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
The returned data frame is sorted based on the pathways' nominal p-values.
library(RCPA)
RNASeqDEExperiment <- loadData("RNASeqDEExperiment")
genesets <- loadData("genesets")
oraResult <- runGeneSetAnalysis(RNASeqDEExperiment, genesets,
method = "ora",
ORAArgs = list(pThreshold = 0.05))
print(head(oraResult))
fgseaResult <- runGeneSetAnalysis(RNASeqDEExperiment, genesets,
method = "fgsea",
FgseaArgs = list(minSize = 10, maxSize = Inf))
print(head(fgseaResult))
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