ValidateAll: Validate the targets of all miRNA using both experimentally...

In miRLAB: Dry lab for exploring miRNA-mRNA relationships

Description

Given the predicted target of all miRNA, the function returns a list of targets of each miRNA that are confirmed based on the experimentally validated interactions or curated transfection data. Users need to download the file logFC.imputed.rda from nugget.unisa.edu.au/Thuc/miRLAB/ and place it in the working directory (this file is obtained from the TargetScoreData package)

Usage

ValidateAll(CEmatrix, topk, groundtruth, LFC, downreg = TRUE)

Arguments

CEmatrix	the matrix of correlation/causal effects/scores with columns are miRNAs and rows are mRNAs
topk	the number of targets of each miRNA that are being validated.
groundtruth	the csv file containing the ground truth.
LFC	the log fold change threshold for the transfection data. The targets that have the absolute value of log fold change greater than the LFC will be regarded as the confirmed targets.
downreg	if TRUE the negative correlation/causal effect/score values will be ranked on the top of the ranking. This is to favour the down regulations.

Value

a list of matrices that contains the confirmed interactions by both provided ground truth and built-in transfection data.

Examples

print("ps=Pearson(dataset, cause=1:3, effect=4:18)")
print("results=ValidateAll(ps, 10, groundtruth, LFC=0.5, downreg=TRUE)")

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