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+#-------------------------------------------------------------------------------------------------
+#-------------------------------------------------------------------------------------------------
+##  AMARETTO: Regulatory network inference and driver gene evaluation using
+##            integrative multi-omics analysis and penalized regression
+##  For details on the implementation visit
+##  https://github.com/gevaertlab/AMARETTO
+#-------------------------------------------------------------------------------------------------
+#-------------------------------------------------------------------------------------------------
+##########################################################
+###################### Example R Script ##################
+##########################################################
+#-----------------------------------------------------------------------------------------
+# 1. Installing AMARETTO and loading the package:
+#-----------------------------------------------------------------------------------------
+install.packages("BiocManager")
+BiocManager::install("gevaertlab/AMARETTO")
+library(AMARETTO)
+
+resdir <- file.path("AMARETTO_Results");if(!file.exists(resdir))	dir.create(resdir) #Absolute path to data results directory
+setwd(resdir)
+#-----------------------------------------------------------------------------------------
+# 2. Dowloading TCGA input data for analysis
+#-----------------------------------------------------------------------------------------
+TargetDirectory <- file.path(getwd(),"Downloads/");if(!file.exists(TargetDirectory))	dir.create(TargetDirectory) #Absolute path to data download directory
+CancerSite <- "LIHC"
+DataSetDirectories <- AMARETTO_Download(CancerSite,TargetDirectory = TargetDirectory)
+
+#-----------------------------------------------------------------------------------------
+# 3. Preprocessing the downloaded TCGA data
+#-----------------------------------------------------------------------------------------
+#ProcessedData <- AMARETTO_Preprocess(DataSetDirectories,BatchData)
+
+#load(inst/extdata//MethylStates.rda) #MethylMix preprocessed data for CancerSite
+#ProcessedData[[3]] <- MethylStates[CancerSite] #MethylMix preprocessed data for CancerSite
+
+#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#
+# Loading preprocessed TCGA-LAML example dataset:
+#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#
+data("ProcessedDataLIHC")
+
+#-----------------------------------------------------------------------------------------
+# 4. Running AMARETTO
+#-----------------------------------------------------------------------------------------
+AMARETTOinit <- AMARETTO_Initialize(ProcessedDataLIHC,NrModules = 2, VarPercentage = 60)
+
+
+AMARETTOresults <- AMARETTO_Run(AMARETTOinit)
+
+AMARETTOtestReport <- AMARETTO_EvaluateTestSet(AMARETTOresults = AMARETTOresults,
+                                               MA_Data_TestSet = AMARETTOinit$MA_matrix_Var,
+                                               RegulatorData_TestSet = AMARETTOinit$RegulatorData)
+
+#-----------------------------------------------------------------------------------------
+# 4. Visualize AMARETTO modules
+#-----------------------------------------------------------------------------------------
+ModuleNr <- 1 #define the module number to visualize
+
+AMARETTO_VisualizeModule(AMARETTOinit = AMARETTOinit,AMARETTOresults = AMARETTOresults,
+                         ProcessedData = ProcessedDataLIHC,ModuleNr = ModuleNr)
+
+#-----------------------------------------------------------------------------------------
+# 5. Get HTML report for AMARETTO modules
+#-----------------------------------------------------------------------------------------
+
+AMARETTO_HTMLreport(AMARETTOinit,AMARETTOresults,ProcessedDataLIHC,VarPercentage=10,hyper_geo_test_bool=FALSE,output_address=resdir)