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### -----------------------------------------------------------------
### PFMSimilarity method. compare two position frequency matrix.
### PFMSimilarity Exported!
compareMatrix = function(pfmSubject, pfmQuery, openPenalty, extPenalty){
# The true aligning engine. Taking two ordinary matrixs.
pfmSubject = normargPfm(pfmSubject)
pfmQuery = normargPfm(pfmQuery)
ans = .Call("matrixAligner", pfmQuery, pfmSubject, openPenalty, extPenalty)
return(ans)
}
setMethod("PFMSimilarity", signature(pfmSubject="matrix", pfmQuery="matrix"),
function(pfmSubject, pfmQuery, openPenalty=3, extPenalty=0.01){
score = compareMatrix(pfmSubject, pfmQuery, openPenalty=openPenalty,
extPenalty=extPenalty)
relScore = 100 * score / min(ncol(pfmSubject), ncol(pfmQuery)) / 2
return(c(score=score, relScore=relScore))
}
)
setMethod("PFMSimilarity", signature(pfmSubject="PFMatrix",
pfmQuery="PFMatrix"),
function(pfmSubject, pfmQuery, openPenalty=3, extPenalty=0.01){
ans = PFMSimilarity(Matrix(pfmSubject), Matrix(pfmQuery),
openPenalty=openPenalty, extPenalty=extPenalty)
return(ans)
}
)
setMethod("PFMSimilarity", signature(pfmSubject="PFMatrix", pfmQuery="matrix"),
function(pfmSubject, pfmQuery, openPenalty=3, extPenalty=0.01){
ans = PFMSimilarity(Matrix(pfmSubject), pfmQuery,
openPenalty=openPenalty, extPenalty=extPenalty)
return(ans)
}
)
setMethod("PFMSimilarity", signature(pfmSubject="matrix", pfmQuery="PFMatrix"),
function(pfmSubject, pfmQuery, openPenalty=3, extPenalty=0.01){
ans = PFMSimilarity(pfmSubject, Matrix(pfmQuery),
openPenalty=openPenalty, extPenalty=extPenalty)
return(ans)
}
)
setMethod("PFMSimilarity", signature(pfmSubject="PFMatrixList",
pfmQuery="matrix"),
function(pfmSubject, pfmQuery, openPenalty=3, extPenalty=0.01){
ans = lapply(pfmSubject, PFMSimilarity, pfmQuery,
openPenalty=openPenalty, extPenalty=extPenalty)
return(ans)
}
)
setMethod("PFMSimilarity", signature(pfmSubject="PFMatrixList",
pfmQuery="PFMatrix"),
function(pfmSubject, pfmQuery, openPenalty=3, extPenalty=0.01){
ans = lapply(pfmSubject, PFMSimilarity, pfmQuery,
openPenalty=openPenalty, extPenalty=extPenalty)
return(ans)
}
)
setMethod("PFMSimilarity", signature(pfmSubject="matrix", pfmQuery="character"),
function(pfmSubject, pfmQuery, openPenalty=3, extPenalty=0.01){
pfmQueryMatrix <- IUPAC2Matrix(pfmQuery)
PFMSimilarity(pfmSubject, pfmQueryMatrix,
openPenalty=openPenalty, extPenalty=extPenalty)
}
)
setMethod("PFMSimilarity", signature(pfmSubject="PFMatrix",
pfmQuery="character"),
function(pfmSubject, pfmQuery, openPenalty=3, extPenalty=0.01){
PFMSimilarity(Matrix(pfmSubject), pfmQuery,
openPenalty=openPenalty, extPenalty=extPenalty)
}
)
setMethod("PFMSimilarity", signature(pfmSubject="PFMatrixList",
pfmQuery="character"),
function(pfmSubject, pfmQuery, openPenalty=3, extPenalty=0.01){
ans = lapply(pfmSubject, PFMSimilarity, pfmQuery,
openPenalty=openPenalty, extPenalty=extPenalty)
return(ans)
}
)
### -----------------------------------------------------------------
### permute the PFM
### Exported!
setMethod("permuteMatrix", "matrix",
function(x, type="intra"){
if(type == "inter")
stop("Only permutation within matrix is
available for single matrix!")
type = match.arg(type, c("intra", "inter"))
x = normargPfm(x)
index = sample(seq_len(ncol(x)), ncol(x), replace=FALSE)
x = x[ , index]
return(x)
}
)
setMethod("permuteMatrix", "PFMatrix",
function(x, type="intra"){
Matrix(x) = permuteMatrix(Matrix(x), type=type)
return(x)
}
)
setMethod("permuteMatrix", "PFMatrixList",
function(x, type="intra"){
type = match.arg(type, c("intra", "inter"))
if(type == "intra"){
for(i in seq_len(length(x))){
x[[i]] = permuteMatrix(x[[i]])
}
}else if(type =="inter"){
allMatrix = do.call(cbind, Matrix(x))
lengths = sapply(Matrix(x), ncol)
lengths = c(0, cumsum(lengths))
index = sample(seq_len(ncol(allMatrix)),
ncol(allMatrix), replace=FALSE)
for(i in seq_len(length(x))){
Matrix(x[[i]]) =
allMatrix[ , index[(lengths[i]+1):lengths[i+1]]]
}
}
return(x)
}
)
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