Description Usage Arguments Value Slots See Also Examples
This S4 class includes a series of methods to do gene set enrichment analysis and hypergeometric test for high-throughput data.
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listOfGeneSetCollections |
A list of gene set collections (a 'gene set collection' is a list of gene sets). |
geneList |
A numeric or integer vector of phenotypes named by gene identifiers. |
hits |
A character vector of the gene identifiers (used as hits in the hypergeometric tests).It's needed if you want to do GSOA (gene set overrepresentation analysis). |
This function will create a new object of 'GSCA' class.
paraA list of parameters for hypergeometric test and GSEA. These parameters are pValueCutoff, pAdjustMethod, nPermutations, minGeneSetSize and exponent.
resultA list of results.
summaryA list of summary information for listOfGeneSetCollections, geneList, hits, para, and result.
preprocessedA single logical value specifying whether or not the input data has been preprocessed.
preprocess,
analyze,
appendGSTerms,
summarize,
report
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | library(org.Hs.eg.db)
library(GO.db)
## load data for enrichment analyses
data(d7)
phenotype <- as.vector(d7$neg.lfc)
names(phenotype) <- d7$id
## select hits if you also want to do GSOA, otherwise ignore it
hits <- names(phenotype[which(abs(phenotype) > 2)])
## set up a list of gene set collections
GO_MF <- GOGeneSets(species="Hs", ontologies=c("MF"))
ListGSC <- list(GO_MF=GO_MF)
## Example1: create an object of class 'GSCA' with hits
gsca <- GSCA(listOfGeneSetCollections = ListGSC, geneList = phenotype, hits = hits)
getSummary(gsca)
## Example2: create an object of class 'GSCA' without hits
gsca <- GSCA(listOfGeneSetCollections = ListGSC, geneList = phenotype)
getSummary(gsca)
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