\name{deregulation.scores} \alias{deregulation.scores} \title{ Calculating deregulation scores. } \description{ Deregulation scores quantify the extent to which the regulatory eflect of each regulator changes between the two compared cell populations.} \usage{deregulation.scores(reg.scores1, reg.scores2,verbose)} \arguments{ \item{reg.scores1}{ A matrix of regulation scores of the genes (rows) for the regulators (columns), compued with the \code{\link{regulation.scores}} function. Given for the first cell population. } \item{reg.scores2}{ The same as reg.scores1 but given for the second cell population. } \item{verbose}{When TRUE, the execution prints informative messages} } \details{The deregulation scores are computed by subtracting reg.scores1 from reg.scores2.} \value{ A matrix with columns for the regulators, rows for the genes, and entries giving the deregulation scores. } \references{ http://joda.molgen.mpg.de } \author{ Ewa Szczurek } \seealso{ \code{\link{differential.probs}}, \code{\link{regulation.scores}} } \examples{ data(damage) # Step 1 # Get the probabilities of differential expression # for the knockout of ATM in the healthy cells probs.healthy.ATM= differential.probs(data.healthy[,"ATM",FALSE], NULL) # Get the probabilities of differential expression # for the knockout of ATM in the damaged cells probs.damage.ATM= differential.probs(data.damage[,"ATM",FALSE], NULL) # Step 2 # Regulation scores for a dataset with only one regulator # equal the signed probabilities # Step 3 # Get the deregulation scores deregulation.ATM= deregulation.scores(probs.healthy.ATM, probs.damage.ATM, TRUE) \dontrun{ # Step 1 probs.healthy= differential.probs(data.healthy, beliefs.healthy) probs.damage= differential.probs(data.damage, beliefs.damage) # Step 2 regulation.healthy= regulation.scores(probs.healthy, model.healthy) regulation.damage= regulation.scores(probs.damage, model.damage) # Step 3 deregulation= deregulation.scores(regulation.healthy, regulation.damage, TRUE) } }