## ---- include = FALSE--------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----installation_bioc, eval = FALSE------------------------------------------ # if (!requireNamespace("BiocManager", quietly = TRUE)) # install.packages("BiocManager") # # BiocManager::install("PanomiR") ## ----installation_git, eval = FALSE------------------------------------------- # devtools::install_github("pouryany/PanomiR") ## ----load_package------------------------------------------------------------- library(PanomiR) # Pathway reference from the PanomiR package data("path_gene_table") data("miniTestsPanomiR") # Generating pathway summary statistics summaries <- pathwaySummary(miniTestsPanomiR$mini_LIHC_Exp, path_gene_table, method = "x2", zNormalize = TRUE, id = "ENSEMBL") head(summaries)[,1:2] ## ----differential------------------------------------------------------------- output0 <- differentialPathwayAnalysis( geneCounts = miniTestsPanomiR$mini_LIHC_Exp, pathways = path_gene_table, covariates = miniTestsPanomiR$mini_LIHC_Cov, condition = 'shortLetterCode') de.paths <- output0$DEP head(de.paths,3) ## ----pcxn--------------------------------------------------------------------- # using an updated version of pcxn set.seed(2) pathwayClustsLIHC <- mappingPathwaysClusters( pcxn = miniTestsPanomiR$miniPCXN, dePathways = de.paths[1:300,], topPathways = 200, outDir=".", plot = FALSE, subplot = FALSE, prefix='', clusteringFunction = "cluster_louvain", correlationCutOff = 0.1) head(pathwayClustsLIHC$Clustering) ## ----miRNA-------------------------------------------------------------------- set.seed(1) output2 <- prioritizeMicroRNA(enriches0 = miniTestsPanomiR$miniEnrich, pathClust = miniTestsPanomiR$miniPathClusts$Clustering, topClust = 1, sampRate = 50, method = c("aggInv"), outDir = "Output/", dataDir = "outData/", saveSampling = FALSE, runJackKnife = FALSE, numCores = 1, prefix = "outmiR", saveCSV = FALSE) head(output2$Cluster1) ## ----customized_mir, eval = FALSE--------------------------------------------- # # # # using an updated version of pcxn # data("msigdb_c2") # data("targetScan_03") # # # customeTableEnrich <- miRNAPathwayEnrichment(mirSets = targetScan_03, # pathwaySets = msigdb_c2, # geneSelection = yourGenes, # mirSelection = yourMicroRNAs, # fromID = "ENSEMBL", # toID = "ENTREZID", # minPathSize = 9, # numCores = 1, # outDir = ".", # saveOutName = NULL) # ## ----customized_mir2---------------------------------------------------------- # using an updated version of pcxn data("msigdb_c2") data("targetScan_03") tempEnrich <-miRNAPathwayEnrichment(targetScan_03[1:30],msigdb_c2[1:30]) head(reportEnrichment(tempEnrich)) ## ----customized_gsc----------------------------------------------------------- data("gscExample") newPathGeneTable <-tableFromGSC(gscExample) ## ----customized_gsc2, eval = FALSE-------------------------------------------- # # library(GSEABase) # # yourGeneSetCollection <- getGmt("YOUR GMT FILE") # newPathGeneTable <- tableFromGSC(yourGeneSetCollection) # ## ----sessionInfo-------------------------------------------------------------- sessionInfo()