## ---- eval=FALSE--------------------------------------------------------- # # library(miRLAB) # # dataset=system.file("extdata", "EMT35.csv", package="miRLAB") # cause=1:35 #column 1:35 are miRNAs # effect=36:1189 #column 36:1189 are mRNAs # # #predict miRNA targets using Pearson correlation # pearson=Pearson(dataset, cause, effect) # # #predict miRNA targets using Mutual Information # mi=MI(dataset, cause, effect) # # #predict miRNA targets using causal inference # ida=IDA(dataset, cause, effect, "stable", 0.01) # # #predict miRNA targets using linear regression # lasso=Lasso(dataset, cause, effect) # ## ---- eval=TRUE---------------------------------------------------------- library(miRLAB) #validate the results of the top100 targets of each miRNA predicted #by the four methods dataset=system.file("extdata", "ToyEMT.csv", package="miRLAB") pearson=Pearson(dataset, 1:3, 4:18) miR200aTop10=bRank(pearson, 3, 10, TRUE) groundtruth=system.file("extdata", "Toygroundtruth.csv", package="miRLAB") miR200aTop10Confirmed = Validation(miR200aTop10, groundtruth) ## ---- eval=TRUE---------------------------------------------------------- library(miRLAB) #validate the results of the top100 targets of each miRNA predicted #by the four methods dataset=system.file("extdata", "ToyEMT.csv", package="miRLAB") EMTresults=Pearson(dataset, 1:3, 4:18) top10=Extopk(EMTresults, 10) groundtruth=system.file("extdata", "Toygroundtruth.csv", package="miRLAB") top10Confirmed = Validation(top10, groundtruth) ## ---- eval=TRUE---------------------------------------------------------- library(miRLAB) dataset=system.file("extdata", "ToyEMT.csv", package="miRLAB") dataset=Read(dataset) dataset[1:5,1:7] ## ---- eval=TRUE---------------------------------------------------------- library(miRLAB) groundtruth=system.file("extdata", "Toygroundtruth.csv", package="miRLAB") groundtruth=Read(groundtruth) groundtruth[1:5,]