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# Randomly perturb a supplied network.
# <perturb="functions"> perturbs the functions associated with the genes directly.
# <perturb="states"> perturbs a maximum of <numStates> states
# in the transition table resulting from the functions.
# <method="bitflip"> randomly flips up to <maxNumBits> in the functions or states.
# <method="shuffle"> randomly permutes the bits in the functions or states.
# If <simplify> is set, the perturbed network is simplified to remove irrelevant input functions.
# If <excludeFixed> is set, fixed genes are excluded from the perturbations and stay as they are.
perturbNetwork <- function(network,perturb=c("functions","transitions"),method=c("bitflip","shuffle"),
simplify=(perturb[1]!="functions"),readableFunctions=FALSE,excludeFixed=TRUE,
maxNumBits=1,numStates=max(1,2^length(network$genes)/100))
{
stopifnot(inherits(network,"BooleanNetwork") | inherits(network,"ProbabilisticBooleanNetwork"))
fixedGenes <- which(network$fixed != -1)
if (length(perturb) == 1 && perturb == "states")
{
warning("perturb=\"states\" is deprecated. Use perturb=\"transitions\" instead!")
perturb <- "transitions"
}
if (inherits(network,"BooleanNetwork"))
# deterministic network
{
switch(match.arg(perturb,c("functions","transitions")),
functions=
switch(match.arg(method,c("bitflip","shuffle")),
bitflip =
{
# choose the function to be perturbed
if (length(fixedGenes) > 0 & excludeFixed)
functionIdx <- sample((seq_along(network$interactions))[-fixedGenes],size=1)
else
functionIdx <- sample(seq_along(network$interactions),size=1)
# choose the indices of the truth table to be flipped
flipIndices <- sample(seq_along(network$interactions[[functionIdx]]$func),
size=runif(n=1,min=1,
max=min(maxNumBits,
length(network$interactions[[functionIdx]]$func))),
replace=FALSE)
# flip the bits
network$interactions[[functionIdx]]$func[flipIndices] <-
as.integer(!network$interactions[[functionIdx]]$func[flipIndices])
network$interactions[[functionIdx]]$expression <-
getInteractionString(readableFunctions,
network$interactions[[functionIdx]]$func,
network$genes[network$interactions[[functionIdx]]$input])
},
shuffle=
{
# choose the function to be perturbed
if (length(fixedGenes) > 0 & excludeFixed)
functionIdx <- sample((seq_along(network$interactions))[-fixedGenes],size=1)
else
functionIdx <- sample(seq_along(network$interactions),size=1)
# draw a random permutation of bit positions
flipIndices <- sample(seq_along(network$interactions[[functionIdx]]$func),
size=length(network$interactions[[functionIdx]]$func),
replace=FALSE)
# permute the bits
network$interactions[[functionIdx]]$func <-
network$interactions[[functionIdx]]$func[flipIndices]
network$interactions[[functionIdx]]$expression <-
getInteractionString(readableFunctions,
network$interactions[[functionIdx]]$func,
network$genes[network$interactions[[functionIdx]]$input])
},
stop("'method' must be one of \"bitflip\",\"shuffle\"")),
transitions =
{
# turn off gene fixing - otherwise reverse-engineering of the transition table is not possible
oldFixed <- network$fixed
network$fixed <- rep(-1,length(network$genes))
names(network$fixed) <- network$genes
# calculate transition table
table <- t(sapply(getAttractors(network)$stateInfo$table,dec2bin,length(network$genes)))
# determine the states to be perturbed
statesToChange <- sample(seq_len(nrow(table)),min(numStates,nrow(table)),replace=FALSE)
lapply(statesToChange,function(state)
{
# choose the indices of the states that are allowed to be changed
flipIndices <- seq_along(network$genes)
if (length(fixedGenes) > 0 & excludeFixed)
flipIndices <- flipIndices[-fixedGenes]
switch(match.arg(method,c("bitflip","shuffle")),
bitflip =
{
# choose the actual indices to be changed
flipIndex <- sample(flipIndices,
size=runif(n=1,min=1,
max=min(maxNumBits,
length(flipIndices))),
replace=FALSE)
# flip the bits at these positions
table[state,flipIndex] <<-
as.integer(!table[state,flipIndex])
},
shuffle =
{
# determine a permutation of the bit indices
flipIndex <- sample(flipIndices,
size=length(flipIndices),
replace=FALSE)
# permute the state
table[state,] <<-
as.integer(table[state,flipIndex])
},
stop("'method' must be one of \"bitflip\",\"shuffle\"")
)
NULL})
# restore network by assigning the columns of the state table to the corresponding genes
network$interactions <- apply(table,2,function(gene)
{
input = seq_along(network$genes)
# encoding is reversed in the transition table
input <- input[length(input):1]
list(input=input,
func=gene,
expression= getInteractionString(readableFunctions,
gene,
network$genes[input]))
})
# reactivate fixed genes
network$fixed <- oldFixed
},
stop("'perturb' must be one of \"functions\",\"transitions\""))
}
else
# probabilistic network
{
if (match.arg(perturb) != "functions")
stop("In probabilistic Boolean networks, only perturb=functions is allowed!")
switch(match.arg(method,c("bitflip","shuffle")),
bitflip =
{
# choose the gene and the function to be perturbed
if (length(fixedGenes) > 0 & excludeFixed)
geneIdx <- sample((seq_along(network$interactions))[-fixedGenes],size=1)
else
geneIdx <- sample(seq_along(network$interactions),size=1)
functionIdx <- sample(seq_along(network$interactions[[geneIdx]]),size=1)
# choose the indices of the truth table to be flipped
flipIndices <- sample(seq_along(network$interactions[[geneIdx]][[functionIdx]]$func),
size=runif(n=1,min=1,
max=min(maxNumBits,
length(network$interactions[[geneIdx]][[functionIdx]]$func))),
replace=FALSE)
# flip the bits
network$interactions[[geneIdx]][[functionIdx]]$func[flipIndices] <-
as.integer(!network$interactions[[geneIdx]][[functionIdx]]$func[flipIndices])
network$interactions[[geneIdx]][[functionIdx]]$expression <-
getInteractionString(readableFunctions,
network$interactions[[geneIdx]][[functionIdx]]$func,
network$genes[network$interactions[[geneIdx]][[functionIdx]]$input])
},
shuffle=
{
# choose the function to be perturbed
if (length(fixedGenes) > 0 & excludeFixed)
geneIdx <- sample((seq_along(network$interactions))[-fixedGenes],size=1)
else
geneIdx <- sample(seq_along(network$interactions),size=1)
functionIdx <- sample(seq_along(network$interactions[[geneIdx]]),size=1)
# draw a random permutation of bit positions
flipIndices <- sample(seq_along(network$interactions[[geneIdx]][[functionIdx]]$func),
size=length(network$interactions[[geneIdx]][[functionIdx]]$func),
replace=FALSE)
# permute the bits
network$interactions[[geneIdx]][[functionIdx]]$func <-
network$interactions[[geneIdx]][[functionIdx]]$func[flipIndices]
network$interactions[[geneIdx]][[functionIdx]]$expression <-
getInteractionString(readableFunctions,
network$interactions[[geneIdx]][[functionIdx]]$func,
network$genes[network$interactions[[geneIdx]][[functionIdx]]$input])
},
stop("'method' must be one of \"bitflip\",\"shuffle\""))
}
# simplify the network if necessary
if (simplify)
network <- simplifyNetwork(network,readableFunctions)
return(network)
}
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