This file explains how to use the mica library and the required files for the library. mica requires R version 3.0.0 or greater. mica depends on the igraph and fastICA library. Therefore, these libraries need to be installed before installing the mica library. To install these packages, just type inside R: >install.packages("igraph") >install.packages("fastICA") After downloading the mica library, call the following command to install it: install.packages("mica_1.0.tar.gz",repos=NULL) Basically, this commands allow installing the mica from the local directory instead of installing it from CRANE After installing mica, you can run the following commands to test the library: >library(mica) #Getting the data from the library >v<-data(package="mica") >data(list=v$results[,3]) #Calculating the z-score for miRNAs >miZ<-getZscore(cbind(miControl,miCase),nControl=ncol(miControl)) #Modifying the case samples expression using the z-score #modifyExp takes miZ in a data.frame format, therefore, it has #to be changed to data.frame. Also, miZ has z-scores for control #and case. >modCase<-modifyExp(data.frame(miZ[,104:253]),case,miMap) #Call icaSteps to calcuated ICA components >icaOut<-icaSteps(modCase,control,nLoops=20) Expected output from this step is as follows: NULL [1] 1 [1] 2 [1] 3 [1] 4 [1] 5 [1] 6 [1] 7 [1] 8 [1] 9 [1] 10 [1] 1 colstandard [1] 2 colstandard [1] 3 colstandard [1] 4 colstandard [1] 5 colstandard [1] 6 colstandard [1] 7 colstandard [1] 8 colstandard [1] 9 colstandard [1] 10 colstandard [1] 11 colstandard [1] 12 colstandard [1] 13 colstandard [1] 14 colstandard [1] 15 colstandard [1] 16 colstandard [1] 17 colstandard [1] 18 colstandard [1] 19 colstandard [1] 20 #Generate active modules using ica output >actMod<-genActiveModules(icaOut,ppiNet,nControl=106,nCases=150) Expected output from last step is: "number of sig components: "