PredictDivergence: A set of functions for detection of Transcription Factor...
In MEET: MEET: Motif Elements Estimation Toolkit
Description
Usage
Arguments
Details
Author(s)
References
See Also
Examples
View source: R/PredictDivergence.R
Description
PredictDivergence contains a set of functions for detection of Transcription Factor Binding sites through parametric divergence. This algorithm evaluates the variation on the total Renyi entropy of a set of sequences assuming correlation between positions in the bindng sequence.
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). It should include a constructed model
Details
This function integrates the Mutual Information (Renyi order equal 1) and parametric divergence (Renyi order different 1)
Author(s)
Joan Maynou <joan.maynou@upc.edu>
References
J. Maynou, M. Vallverdu, F. Claria, J.J. Gallardo-Chacon, P. Caminal and A. Perera, Transcription Factor Binding Site Detection through Position Cross-Mutual Information variability analysis. 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
See Also
PredictEntropy, PredictMEME, PredictMDscan, PredictPCA and PredictMATCH
Examples
1
2
3
4
data(iicc)
iicc$parametersIdeal<-1
iicc$model<-ModelDivergence(iicc)
PredictDivergence(iicc)
MEET documentation built on May 2, 2019, 5:52 p.m.
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.
Description Usage Arguments Details Author(s) References See Also Examples
View source: R/PredictDivergence.R
Description
PredictDivergence contains a set of functions for detection of Transcription Factor Binding sites through parametric divergence. This algorithm evaluates the variation on the total Renyi entropy of a set of sequences assuming correlation between positions in the bindng sequence.
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). It should include a constructed model |
Details
This function integrates the Mutual Information (Renyi order equal 1) and parametric divergence (Renyi order different 1)
Author(s)
Joan Maynou <joan.maynou@upc.edu>
References
J. Maynou, M. Vallverdu, F. Claria, J.J. Gallardo-Chacon, P. Caminal and A. Perera, Transcription Factor Binding Site Detection through Position Cross-Mutual Information variability analysis. 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
See Also
PredictEntropy, PredictMEME, PredictMDscan, PredictPCA and PredictMATCH
Examples
1 2 3 4 | data(iicc)
iicc$parametersIdeal<-1
iicc$model<-ModelDivergence(iicc)
PredictDivergence(iicc)
|
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.