Elastic: miRNA target prediction with the Elastic-net regression...

In miRLAB: Dry lab for exploring miRNA-mRNA relationships

Description

Calculate the Elastic-net regression coefficient of each pair of miRNA-mRNA,and return a matrix of correlation coefficients with columns are miRNAs and rows are mRNAs.

Usage

Elastic(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 Elastic-net regression coefficients. Columns are miRNAs, rows are mRNAs.

References

1. Le, T.D., Zhang, J., Liu, L., and Li, J. (2015) Ensemble Methods for miRNA Target Prediction from Expression Data, under review.

2. Zou, H., & Hastie, T. (2005). Regularization and variable selection via the elastic net. J. R. Stat. Soc. Series B Stat. Methodol., 67, 301-320.

Examples

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

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