kfold.MEME: Leave-one-out cross-training for MEME

Description Usage Arguments Details Author(s) References See Also Examples

View source: R/kfold.MEME.R

Description

Given a training sequence set, the optimal length and number motif has been estimated by means of leave-one-out cross-training from length and number motif set. From each value, the ROC curve has been calculated. From this results, the optimal value has been considered according to the area under conver surface maximum

Usage

1

Arguments

iicc

A set of inicial conditions for the MEET-package (mode, method, background, alignment, threshold, parameters, Transcriptionfactor, nummotif, lenmotif, sentit, position, missing, vector, gapopen, maxiters, gapextend)

TF

A set of nucleotide sequences

Details

This function needs MEME/MAST software.

Author(s)

Joan Maynou <joan.maynou@upc.edu>

References

[5] T. Bailey and C. Elkan, Fitting a mixture model by expectation maximization to discover motifs in biopolymers, in Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology.AAAI Press, August 1994, pp. 28.

See Also

kfold.PredictDivergence, kfold.PredictInformationTheory, MDscan, kfold.MATCH and kfold.PCA

Examples

1
2
3
data(iicc)
pathMEET<-system.file("exdata",package="MEET")
#kfold.MEME(iicc,TF=paste(pathMEET,"AP1.fa",sep="/"))

MEET documentation built on May 2, 2019, 5:52 p.m.