kfold.transMEME: Leave-one-out cross-training for MEME/MAST through...
In MEET: MEET: Motif Elements Estimation Toolkit
Description
Usage
Arguments
Details
Author(s)
References
See Also
Examples
View source: R/kfold.transMEME.R
Description
This function does leave-one-out cross-training for MEME/MAST. In this case, a set of nucleotide sequences is lined up MUSCLE and CLUSTALW. This is main difference between transMEME and MEME.
Usage
1
kfold.transMEME(iicc, TF)
Arguments
iicc
Set of initial 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 sequence
Details
This function needs MEME/MAST software.
Author(s)
Erola Pairo <epairo@ibecbarcelona.eu> and Joan Maynou <joan.maynou@upc.edu>
References
T. Bailey and C. Elkan, Fitting a mixture model by expectation max- imization to discover motifs in biopolymers in Proc. 2nd Int. Conf. Intelligent Systems for Molecular Biology, Aug. 1994, pp. 28.
See Also
MEET, kfold.Entropy, kfold.transMEME,kfoldMEME, kfold.Divergence, kfold.PCA
Examples
1
2
3
data(iicc)
pathMEET<-system.file("exdata",package="MEET")
#kfold.transMEME(iicc,TF=paste(pathMEET,"AP1.fa",sep="/"))
MEET documentation built on May 2, 2019, 5:52 p.m.
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Description Usage Arguments Details Author(s) References See Also Examples
View source: R/kfold.transMEME.R
Description
This function does leave-one-out cross-training for MEME/MAST. In this case, a set of nucleotide sequences is lined up MUSCLE and CLUSTALW. This is main difference between transMEME and MEME.
Usage
1 | kfold.transMEME(iicc, TF)
|
Arguments
iicc |
Set of initial 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 sequence |
Details
This function needs MEME/MAST software.
Author(s)
Erola Pairo <epairo@ibecbarcelona.eu> and Joan Maynou <joan.maynou@upc.edu>
References
T. Bailey and C. Elkan, Fitting a mixture model by expectation max- imization to discover motifs in biopolymers in Proc. 2nd Int. Conf. Intelligent Systems for Molecular Biology, Aug. 1994, pp. 28.
See Also
MEET, kfold.Entropy, kfold.transMEME,kfoldMEME, kfold.Divergence, kfold.PCA
Examples
1 2 3 | data(iicc)
pathMEET<-system.file("exdata",package="MEET")
#kfold.transMEME(iicc,TF=paste(pathMEET,"AP1.fa",sep="/"))
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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