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

1 2 | ```
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.

`FDRcollectionGsea`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | ```
##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)
``` |

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