## ---- 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=FALSE-------------------------------------------------------------- # 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=FALSE-------------------------------------------------------------- # 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=FALSE-------------------------------------------------------------- # library(miRLAB) # dataset=system.file("extdata", "ToyEMT.csv", package="miRLAB") # dataset=Read(dataset) # dataset[1:5,1:7] ## ---- eval=FALSE-------------------------------------------------------------- # library(miRLAB) # groundtruth=system.file("extdata", "Toygroundtruth.csv", package="miRLAB") # groundtruth=Read(groundtruth) # groundtruth[1:5,]