Description Usage Arguments Value Author(s) Examples
This function wraps the topGO-package
an provides a streamlined appraoch to GO analysis.
Sensible defaults are included,
though may not be sufficient for all uses.
1 2 3 4 5 6 7 8 9 | runGOAnalysis(sigGenes,
expGenes,
goAnno,
pValThresh = 1,
plotGO = FALSE,
ontology = "BP",
algorithm = "weight",
statistic = "fisher",
description = NULL)
|
sigGenes |
A character vector with the names of significant genes. |
expGenes |
A character vector with the names of all reference genes, for example, those expressed in the tissu of interest. |
goAnno |
A (named) list of of character vectors with GO identifiers for each gene,
such as returned by |
pValThresh |
Numeric, what p-value (not corrected, see value below) threshold should be used to determine what should be returned. Defaults to 1 to return all GO terms analyzed to allow the user to perform multiple-testing corrections as desired. |
plotGO |
Logical - Should a plot be generated? If TRUE, plots to the currently active device. |
ontology |
Which ontology should be analyzed by |
algorithm |
Which algorithm should be used by |
statistic |
Which statistic should be used by |
description |
A string to use in describing the go data set. Not currently used because the GOData object is not returned. |
Returns a data.frame with a row for each significant GO term. Note that it returns p-values, rather than adjusted p-values. The authors of topGO appear to feel strongly about this, so I have deferred to their choice. I do agree with them that the GO graph is inherently non-independent making most methods for correction overly-conservative. In addition, the default method ("weight") has a built in correction.
Mark Peterson
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ## Only run if topGO is available
if(require(topGO)){
## Load the sample data from topGO
data(GOdata)
## Recreate the GO annotation
## NB: you will likely do this with readMappings()
goAnno <- inverseList(genesInTerm(GOdata,usedGO(GOdata)))
testOut <- runGOAnalysis(sigGenes(GOdata),
allGenes(GOdata),
goAnno,
algorithm = "classic",
pValThresh = 0.05)
head(testOut)
}
|
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