Description Usage Arguments Details Value Examples
Evaluates a set of gene modules (e.g., the output from
predictModules
) by checking them for enrichment of gene
annotations.
1 | checkModules(x, a, p = 0.05, return.p.matrix = FALSE)
|
x |
a binary matrix indicating module membership (genes in rows, modules in columns) |
a |
a binary gene annotation matrix (genes in rows, annotations in columns) |
p |
FDR-adjusted p-value below which to consider an annotation significant |
return.p.matrix |
logical value indicating whether the full p-value matrix should be returned in the output |
This function evaluates a set of predicted gene modules by testing whether
each module is enriched for any gene annotations. Enrichment p-values are calculated using
hypergeometric statistics (see phyper
). If x is not a binary matrix,
module membership is determined using partition
with default
paramaters. The FDR-correction (see p.adjust
) is applied to all
p-values prior to determining signficance.
A list with the following elements:
Number of annotations tested (number of columns in a)
Number of modules tested (number of columns in x)
Number of annotations that were significant in at least one module
Number of modules that were significant for at least one annotation
The module-by-annotation p-value matrix (if return.p.matrix == TRUE)
1 2 3 4 5 6 7 | x = matrix(rnorm(100), 10, 10)
a = matrix(sample(c(0,1), size = 100, replace = TRUE), 10, 10)
m = predictModules(x)$S
rownames(a) = rownames(m) = as.character(1:10)
m.p = partition(m, t = 2)
m.p2 = splitMatrix(m.p)
checkModules(m.p2, a)
|
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