synRNASeqNet-package: Synthetic RNA-Seq Network Generation and Mutual Information...

In synRNASeqNet: Synthetic RNA-Seq Network Generation and Mutual Information Estimates

Description

It implements various estimators of mutual information, such as the maximum likelihood and the Millow-Madow estimator, various Bayesian estimators, the shrinkage estimator, and the Chao-Shen estimator. It also offers wrappers to the kNN and kernel density estimators.

Furthermore, it provides various index of performance evaluation such as precision, recall, FPR, F-Score, ROC-PR Curves and so on.

Lastly, it provides a brand new way of generating synthetic RNA-Seq Network with known dependence structure.

Index

synRNASeqNet-package:	Synthetic RNA-Seq Network Generation and Mutual Information Estimates
parMIEstimate:	Parallel Mutual Information Estimation
parEntropyEstimate:	Parallel Entropy Estimation
entropyML:	Maximum Likelihood Entropy Estimate
entropyMM:	Miller-Madow corrected Entropy Estimate
entropyBayes:	Bayesian Entropy Estimate
entropyCS:	Chao-Shen Entropy Estimate
entropyShrink:	James-Stein Shrinkage Entropy Estimate
parMIKD:	Parallel Kernel Density Mutual Information Estimate
simulatedData:	Random Generation Networks for RNA-Seq Data
mainNetFunction:	Main Estimation and Evaluation Function
plotROC:	Plot ROC Curve
plotPR:	Plot PR Curve
aucDisc:	Calculate Area Under a (ROC/PR) Curve
performanceIndex:	Evalutate Performance Indices
performanceNET:	Evalutate Performance Indices
YoudenIndex:	Youden's Index
Likelihoods:	Likelihood Indices
DiscriminantPower:	Discriminant Power

Author(s)

Luciano Garofano [e-mail], Stefano Maria Pagnotta, Michele Ceccarelli

synRNASeqNet documentation built on May 2, 2019, 6:01 a.m.