gCMAP (version 1.16.0)

wilcox_score-methods: Methods for Function wilcox_score in Package gCMAP

Description

These methods provide a wrapper for the Mean-rank Gene Set Test function wilcoxGST wilcox_score is a synonym for gst_score with ranks.only=TRUE. This test procedure was developed by Michaud et al (2008), who called it mean-rank gene-set enrichment.

Usage

"wilcox_score"(experiment, sets, adjust.ties=FALSE, keep.scores=FALSE, ...)
"wilcox_score"(experiment, sets,...)
"wilcox_score"(experiment, sets, element="z",...)
"wilcox_score"(experiment, sets,...)
"wilcox_score"(experiment, sets,...)
"wilcox_score"(experiment, sets, element="z",...)
"wilcox_score"(experiment, sets,...)
"wilcox_score"(experiment, sets,...)
"wilcox_score"(experiment, sets, element="z",...)
"wilcox_score"(experiment, sets, element="z",adjust.ties=FALSE, keep.scores=FALSE,...)
"wilcox_score"(experiment, sets,...)
"wilcox_score"(experiment, sets,...)
"wilcox_score"(experiment, sets,...)
"wilcox_score"(experiment, sets,...)
"wilcox_score"(experiment, sets,element="z",...)
"wilcox_score"(experiment, sets,...)
"wilcox_score"(experiment, sets,...)
"wilcox_score"(experiment, sets,element="z",...)

Arguments

sets

A CMAPCollection, GeneSetCollection or GeneSet object containing gene sets, with which to query the experiment object.

experiment

An eSet or matrix or vector with numeric data to compare the query object to.

element

Character vector specifying which channel of an eSet to extract (defaults to "exprs", alternatives may be e.g. "z", etc.)

...

Additional arguments passed on to downstream methods.

adjust.ties

Logical: adjust Wilcox-Mann-Whitney statistic in the presence of ties ? (Default: FALSE)

keep.scores

Logical: keep gene-level scores for all gene sets (Default: FALSE) ? The size of the generated CMAPResults object increases with the number of contained gene sets. For very large collections, setting this parameter to 'TRUE' may require large amounts of memory.

Examples

data(gCMAPData)
gene.set.collection <- induceCMAPCollection(gCMAPData, "z", higher=2, lower=-2)

profile <- assayDataElement(gCMAPData[,1], "z")
## one profile versus three sets
wilcox_score(profile, gene.set.collection)

## three sets versus three profiles
wilcox_score(gene.set.collection, gCMAPData)