msviperCombinatorial: msviper combinatorial analysis
In viper: Virtual Inference of Protein-activity by Enriched Regulon analysis

Description Usage Arguments Value See Also Examples

This function performs combinatorial analysis for msviper objects

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msviperCombinatorial(mobj, regulators = 100, nullmodel = NULL,
  minsize = NULL, adaptive.size = NULL, level = 10, cores = 1,
  processAll = FALSE, verbose = TRUE)

`mobj`	msviper object generated by `msviper` function
`regulators`	Either a number between 0 and 1 indicating the p-value cutoff for individual TFs to be included in the combinations analysis; (>1) indicating the number of top TFs to be included in the combinations analysis; or a vector of character strings indicating the TF IDs to be included in the analysis
`nullmodel`	Matrix of genes by permutations containing the NULL model signatures. Taken from `mobj` by default
`minsize`	Number indicating the minimum allowed size for the regulons, taken from `mobj` by default
`adaptive.size`	Logical, whether the weight (likelihood) should be used for computing the size, taken from `mobj` by default
`level`	Integer, maximum level of combinatorial regulation
`cores`	Integer indicating the number of cores to use (only 1 in Windows-based systems)
`processAll`	Logical, whether all pairs, even if not significant, should be processed for synergy
`verbose`	Logical, whether progression messages should be printed in the terminal

A msviper object

msviper

data(bcellViper, package="bcellViper")
sig <- rowTtest(dset, "description", c("CB", "CC"), "N")$statistic
dnull <- ttestNull(dset, "description", c("CB", "CC"), "N", per=100) # Only 100 permutations to reduce computation time, but it is recommended to perform at least 1000 permutations
mra <- msviper(sig, regulon, dnull)
mra <- msviperCombinatorial(mra, 20)
plot(mra, cex=.7)