MI: miRNA target prediction with mutual information method

In miRLAB: Dry lab for exploring miRNA-mRNA relationships

Description

Calculate the mutual information of each pair of miRNA-mRNA,and return a matrix of mutual information values with columns are miRNAs and rows are mRNAs.

Usage

MI(datacsv, cause, effect, targetbinding = NA)

Arguments

datacsv	the input dataset in csv format
cause	the column range that specifies the causes (miRNAs), e.g. 1:35
effect	the column range that specifies the effects (mRNAs), e.g. 36:2000
targetbinding	the putative target, e.g. "TargetScan.csv". If targetbinding is not specified, only expression data is used. If targetbinding is specified, the prediction results using expression data with be intersected with the interactions in the target binding file.

Value

A matrix that includes the mutual information values. Columns are miRNAs, rows are mRNAs.

References

Moon, Y.I., Balaji, R., and Lall, U. (1995) Estimation of mutual information using kernel density estimators. Phys. Rev. E, 52, 2318 - 21.

Examples

dataset=system.file("extdata", "ToyEMT.csv", package="miRLAB")
results=MI(dataset, 1:3, 4:18) 

miRLAB documentation built on Nov. 8, 2020, 5:45 p.m.