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# @rdname regFET
# @export
setGeneric("regFET", def = function(object, ...) standardGeneric("regFET"))
.regFET = function(object, namedScores, namedScoresCutoffs = 0.05,
minSize = 5, maxSize = 5000, pvalueCutoff = 0.05,
pAdjustMethod = "BH",
qvalueCutoff = 0.2, regAltName = NULL, universe = NULL) {
netTable = object@elementset
network = .net(object)
tarReg = .tarReg(object)
stopifnot(length(names(namedScores)) == length(namedScores))
if (is.null(regAltName)) {
regAltName = names(network)
}
stopifnot(is.numeric(namedScoresCutoffs))
stopifnot(length(network) == length(regAltName))
# The data format for enricher_internal()
netENV = list(PATHID2NAME = stats::setNames(names(network), regAltName),
EXTID2PATHID = tarReg, PATHID2EXTID = network)
netENV = as.environment(netENV)
topGene = names(namedScores[namedScores <= namedScoresCutoffs])
# Fisher exact test
enricher_internal = utils::getFromNamespace("enricher_internal", ns = "DOSE")
y = enricher_internal(gene = topGene, pvalueCutoff = 1,
pAdjustMethod = pAdjustMethod, universe = universe,
minGSSize = minSize,
maxGSSize = maxSize, qvalueCutoff = 1, USER_DATA = netENV)
# The results to show
newEnrich(topResult = as_tibble(y@result[(y@result$pvalue <= pvalueCutoff) &
(y@result$p.adjust <= pvalueCutoff) &
(y@result$qvalue <= qvalueCutoff), ]),
allResult = as_tibble(y@result),
gene = y@gene, namedScores = namedScores, type = "FET")
# new(Class = "Enrich",
# topResult = y@result[(y@result$pvalue <= pvalueCutoff) &
# (y@result$p.adjust <= pvalueCutoff) &
# (y@result$qvalue <= qvalueCutoff), ],
# allResult = y@result,
# gene = y@gene, namedScores = namedScores, type = "FET")
}
# Enrichment analysi by Fisher's exact test.
# @description Enrichment for regulators based on Fisher exact test.
# @param object a topNetwork object, The result returned from
# \code{\link{topNet}} function.
# @param namedScores a named numeric vector of scores,
# the names of the scores are the genes to perform enrichment analysis.
# And the names should be the same as in the topNetwork object.
# Here the scores are p-value of each gene.
# @param namedScoresCutoffs the cutoff of \code{namedScores}.
# @param minSize the minimum number (default 5) of target genes.
# @param maxSize the maximum number (default 5000) of target genes.
# @param pvalueCutoff numeric, the cutoff for adjusted enrichment p value.
# This is used for obtaining the `topResult` slot in the final `Enrich`
# object. Default is 0.05.
# @param pAdjustMethod p adjust method, one of 'holm', 'hochberg',
# 'hommel', 'bonferroni', 'BH', 'BY', 'fdr', 'none'.
# @param qvalueCutoff cutoff of q-value.
# @param regAltName alternative names of the regulators in the pathway.
# @param universe a vector of charactors. Background target genes.
# @param ... additional arguments.
# @return An \code{enrichFET} object, consisting of 5 elements:\cr
# \code{topResult}, the enrichment information of regulators that
# pass minSize maxSize pvalueCutoff and qvalueCutoff cutoffs;\cr
# \code{allResult}, the enrichment information of all regulators;\cr
# \code{gene}, the genes pass the \code{namedScoresCutoffs}; \cr
# \code{universe}, total target genes in the network;\cr
# and \code{geneSets}, a list of regulators (the names of the list)
# and their targets (the elements of the list).
# @include regenrichClasses.R
# @import DOSE
# @importClassesFrom DOSE enrichResult
# @rdname regFET
# @seealso \code{\link{regSEA}}
# @export
setMethod("regFET", c("TopNetwork"), .regFET)
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