enrichedIn | R Documentation |
This function builds a cross-tabulation of enriched (TRUE) and non-enriched (FALSE) GO terms vs. gene lists
enrichedIn(x, ...)
## Default S3 method:
enrichedIn(
x,
geneUniverse,
orgPackg,
onto,
GOLevel,
pAdjustMeth = "BH",
pvalCutoff = 0.01,
qvalCutoff = 0.05,
parallel = FALSE,
nOfCores = 1,
...
)
## S3 method for class 'character'
enrichedIn(
x,
geneUniverse,
orgPackg,
onto,
GOLevel,
pAdjustMeth = "BH",
pvalCutoff = 0.01,
qvalCutoff = 0.05,
parallel = FALSE,
nOfCores = 1,
...
)
## S3 method for class 'list'
enrichedIn(
x,
geneUniverse,
orgPackg,
onto,
GOLevel,
pAdjustMeth = "BH",
pvalCutoff = 0.01,
qvalCutoff = 0.05,
parallel = FALSE,
nOfCores = min(detectCores() - 1, length(x)),
...
)
x |
either an object of class "character" (or coerzable to "character") or "list". In the "character" interface, these values should represent Entrez gene (or, in general, feature) identifiers. In the "list" interface, each element of the list must be a "character" vector of Entrez identifiers |
... |
Additional parameters |
geneUniverse |
character vector containing the universe of genes from where gene lists have been extracted. This vector must be obtained from the annotation package declared in |
orgPackg |
A string with the name of the genomic annotation package corresponding to a specific species to be analyzed, which must be previously installed and activated. For more details see README File. |
onto |
string describing the ontology. Belongs to c('BP', 'MF', 'CC') |
GOLevel |
GO level, an integer |
pAdjustMeth |
string describing the adjust method. Belongs to c('BH', 'BY', 'Bonf') |
pvalCutoff |
adjusted pvalue cutoff on enrichment tests to report |
qvalCutoff |
qvalue cutoff on enrichment tests to report as significant. Tests must pass i) pvalueCutoff on unadjusted pvalues, ii) pvalueCutoff on adjusted pvalues and iii) qvalueCutoff on qvalues to be reported |
parallel |
Logical. Only in "list" interface. Defaults to FALSE but put it at TRUE for parallel computation |
nOfCores |
Number of cores for parallel computations. Only in "list" interface |
The arguments 'parallel' and 'nOfCores' are ignored in the 'default' and "character" interfaces because (in the present implementation) parallelisation is only applied to repeated calls to function 'clusterProfiler::enrichGO' which, in turn, does not provide for the possibility of parallelisation. They only apply to the "list" interface.
In the "character" interface, a length k vector of TRUE/FALSE values corresponding to enrichment or not, where k stands for the total number of GO terms at level 'GOLev' in ontology 'onto'. In the "list" interface, a boolean matrix of TRUE/FALSE values indicating enrichment or not, with k rows and s columns, where k corresponds to the total number of GO terms at level 'GOLev' in ontology 'onto' and s corresponds to the length of "list" 'x'.
enrichedIn(default)
: S3 default method
enrichedIn(character)
: S3 method for class "character"
enrichedIn(list)
: S3 method for class "list"
# Obtaining ENTREZ identifiers for the gene universe of humans:
library(org.Hs.eg.db)
humanEntrezIDs <- keys(org.Hs.eg.db, keytype = "ENTREZID")
# Gene lists to be explored for enrichment:
data(allOncoGeneLists)
?allOncoGeneLists
# Computing the cross table:
enrichd <- enrichedIn(allOncoGeneLists[["Vogelstein"]],
geneUniverse = humanEntrezIDs, orgPackg = "org.Hs.eg.db",
onto = "MF", GOLevel = 6)
enrichd
# Cross table of enriched GO terms (GO ontology MF, level 6) for all gene
# lists in 'allOncoGeneLists':
enrichedAllOncoMF.6 <- enrichedIn(allOncoGeneLists,
geneUniverse = humanEntrezIDs, orgPackg = "org.Hs.eg.db",
onto = "MF", GOLevel = 6)
enrichedAllOncoMF.6
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