collectionGsea: Compute observed and permutation-based enrichment scores for a collection (list) of gene sets

Description

This function computes observed and permutation-based scores associated with a gene set enrichment analysis for a collection of gene sets.

Usage

collectionGsea(collectionOfGeneSets, geneList, exponent=1, nPermutations=
1000, minGeneSetSize=15, verbose=TRUE)

Arguments

collectionOfGeneSets

a list of gene sets. Each gene set in the list is a character vector of gene identifiers.

geneList

a numeric or integer vector which has been named and ordered. It cannot contain any duplicates nor NAs.

exponent

a single numeric or integer value (set as 1 by default) specifying the exponent of the GSEA method.

nPermutations

a single numeric or integer value specifying the number of permutation tests for each gene set

minGeneSetSize

a single numeric or integer value specifying the minimum size required for a gene set to be considered.

verbose

a single logical value specifying to display detailed messages (when verbose=TRUE) or not (when verbose=FALSE)

Value

Observed.scores: The observed scores for the given gene sets (a named vector)
Permutation.scores: The scores for the permutation tests (one column for each permutation and a row for each gene set)

References

Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S. & Mesirov, J. P. (2005) Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 102, 15545-15550.

Examples

Run this code

##example 1
gl <- runif(100, min=0, max=5)
gl <- gl[order(gl, decreasing=TRUE)]
names(gl) <- as.character(sample(x=seq(from=1, to=100, by=1), size=100,
replace=FALSE))
gs1 <- sample(names(gl), size=20, replace=FALSE)
gs2 <- sample(names(gl), size=20, replace=FALSE)
gsc <- list(subset1=gs1, subset2=gs2)
GSCscores <- collectionGsea(collectionOfGeneSets=gsc, geneList=gl,
exponent=1, nPermutations=1000, minGeneSetSize=5)
GSCpvalues <- permutationPvalueCollectionGsea(permScores=
GSCscores$Permutation.scores, dataScores=GSCscores$Observed.scores)
##example 2
## Not run: 
# library(org.Dm.eg.db)
# library(KEGG.db)
# ##load phenotype vector (see the vignette for details about the
# ##preprocessing of this data set)
# data("KcViab_Data4Enrich")
# DM_KEGG <- KeggGeneSets(species="Dm")
# GSCscores <- collectionGsea(collectionOfGeneSets=DM_KEGG, geneList=
# KcViab_Data4Enrich, exponent=1, nPermutations=1000, minGeneSetSize=100)
# GSCpvalues <- permutationPvalueCollectionGsea(permScores=
# GSCscores$Permutation.scores, dataScores=GSCscores$Observed.scores)
# ## End(Not run)