collectionGsea {HTSanalyzeR} | R Documentation |
This function computes observed and permutation-based scores associated with a gene set enrichment analysis for a collection of gene sets.
collectionGsea(collectionOfGeneSets, geneList, exponent=1, nPermutations= 1000, minGeneSetSize=15, verbose=TRUE)
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) |
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) |
Camille Terfve, Xin Wang
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.
##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)