Nothing
kfold.Divergence <-function(iicc,TF){
require("MEET")
require("seqinr")
write.fasta <- get("write.fasta",pos="package:seqinr")
read.fasta <- get("read.fasta",pos="package:seqinr")
Prob<-iicc$background
iicc$missing.fun=TRUE
k<-iicc$longDNA<-length(iicc$DNAreal)
x<-read.fasta(file=TF,forceDNAtolower=FALSE)
x<-x[-iicc$outsequence]
write.fasta(sequences=x,names=c(1:length(x)),file.out="setTF.fa",open="w")
factor<-switch(iicc$alignment, "CLUSTALW"=align.clustalw(filein="setTF.fa", fileout="Sq.fa", call=iicc$clustalw), "MUSCLE"=align.muscle(filein="setTF.fa", fileout="Sq.fa", gapopen=iicc$gapopen, maxiters=iicc$maxiters, gapextend=iicc$gapextend, call=iicc$muscle),"MEME"=align.MEME(filein="setTF.fa",fileout="Sq.fa",iicc),"NONE"=Read.aligned("setTF.fa"), stop("Alignment method not included"))
validation.set_x <- iicc$DNAreal
out<-lapply(seq(1, length(iicc$vector), 1), function(r){lapply(seq(1, length(x), 1), function(t){})})
seq.rand<-NULL
Resultats<-lapply(seq(1, length(iicc$vector), 1),function(i){
iicc$D <- iicc$correction_1rOrdre <- iicc$probparella<-NULL
iicc$correction_1rOrdre_m1<-iicc$Mperfil<-iicc$q<- NULL
iicc$HXmax<-iicc$HX<-iicc$q<-NULL
iicc$Divergence<-iicc$interA<-iicc$interB<-iicc$classentropy<-NULL
q<-iicc$q<-iicc$vector[[i]]
if (q==1) {iicc$classentropy<-"Shannon"
}else{
iicc$classentropy<-"Renyi"
}
iicc <- detector_2nOrdre_init(factor, val.set=seq.rand, iicc)
memory<-MImemory(iicc,factor)
iicc<-c(iicc,memory)
out[[i]]<-lapply(seq(1, length(x), 1), function(m){
y<-x[-m]
write.fasta(sequences=y,names=c(1:length(x)),file.out="factor.fa",open="w")
training.set<-switch(iicc$alignment, "CLUSTALW"=align.clustalw(filein="factor.fa", fileout="background.fa", call=iicc$call.clustalw), "MUSCLE"=align.muscle(filein="factor.fa", fileout="background.fa", gapopen=iicc$gapopen, maxiters=iicc$maxiters, gapextend=iicc$gapextend, call=iicc$call.muscle),"MEME"=align.MEME(filein="factor.fa",fileout="background.fa",iicc),"NONE"=Read.aligned("factor.fa"), stop("Alignment method not included"))
zout <- sapply( X=c(1:(iicc$longDNA-ncol(training.set)+1)),
FUN = function(X, training.set, seq.rand, iicc) {seq.rand <-validation.set_x[X:(X+ncol(training.set)-1)]
MIread(training.set=training.set, val.set= seq.rand, iicc)
}, training.set=training.set, seq.rand= seq.rand, iicc=iicc)
})
unlist(out[[i]])
})
return(Resultats)
}
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