MEET (version 5.1.1)

MIread: To read PredictDivergence values

Description

This function reads divergence values saved in memory. From the divergence values, MIread calculates the variation of the total divergence when the candidate sequence is added to the set.

Usage

MIread(training.set,val.set,iicc)

Arguments

training.set

A set of nucleotide sequences

val.set

A candidate sequence

iicc

A set of inicial conditions for the MEET-package

See Also

MImemory

Examples

require("MEET")
data(DrosophilaDivergence)
model<-list()
model$D<-iicc[["a1"]]$model$parameterModel$D
model$HXmax<-iicc[["a1"]]$model$parameterModel$HXmax
model$correctioc_1rOrdre<-iicc[["a1"]]$model$parameterModel$correction_1rOrdre
model$Entropy<-iicc[["a1"]]$model$parameterModel$HX
model$Mperfil<-iicc[["a1"]]$model$parameterModel$Mperfil
model$interA<-iicc[["a1"]]$model$parameterModel$interA
model$interB<-iicc[["a1"]]$model$parameterModel$interB
model$Divergence<-iicc[["a1"]]$model$model

test<-MIread(training.set=iicc[["a1"]]$Transcriptionfactor, val.set=iicc[["a1"]]$Transcriptionfactor[1,],iicc=model)