## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(echo=TRUE, comment="", dev="png") ## ----load_library, message=FALSE---------------------------------------------- # We'll also be using some functions from dplyr # BiocManager::install("pathlinkR", version="devel") library(dplyr) library(pathlinkR) ## ----datasets_and_preliminary_volcano_plot, message=FALSE--------------------- ## A quick look at the DESeq2 results table data("exampleDESeqResults") knitr::kable(head(exampleDESeqResults[[1]])) ## Generate a volcano plot from the first data frame, with default thresholds eruption( rnaseqResult=exampleDESeqResults[[1]], title=names(exampleDESeqResults[1]) ) ## ----plot_fold_changes_I, fig.height=8---------------------------------------- plotFoldChange( inputList=exampleDESeqResults, pathName="Interferon alpha/beta signaling" ) ## ----ppi_networks, fig.width=10, fig.height=8, warning=FALSE------------------ exNetwork <- ppiBuildNetwork( rnaseqResult=exampleDESeqResults[[1]], filterInput=TRUE, order="zero" ) ppiPlotNetwork( network=exNetwork, title=names(exampleDESeqResults)[1], fillColumn=LogFoldChange, fillType="foldChange", label=TRUE, labelColumn=hgncSymbol, legend=TRUE ) ## ----ppiEnrichNetwork, message=FALSE------------------------------------------ exNetworkPathways <- ppiEnrichNetwork( network=exNetwork, analysis="hallmark", filterResults="default", geneUniverse = rownames(exampleDESeqResults[[1]]) ) ## ----ppiExtractSubnetwork, warning=FALSE, message=FALSE----------------------- exSubnetwork <- ppiExtractSubnetwork( network=exNetwork, pathwayEnrichmentResult=exNetworkPathways, pathwayToExtract="INTERFERON GAMMA RESPONSE" ) ppiPlotNetwork( network=exSubnetwork, fillType="oneSided", fillColumn=degree, label=TRUE, labelColumn=hgncSymbol, legendTitle="Degree" ) ## ----sigora_enrichment-------------------------------------------------------- ## Note the structure of `exampleDESeqResults`: a named list of results from ## DESeq2 exampleDESeqResults enrichedResultsSigora <- pathwayEnrichment( inputList=exampleDESeqResults, analysis="sigora", filterInput=TRUE, gpsRepo="default" ) head(enrichedResultsSigora) ## ----hallmark_enrichment------------------------------------------------------ enrichedResultsHm <- pathwayEnrichment( inputList=exampleDESeqResults, analysis="hallmark", filterInput=TRUE, split=TRUE ) head(enrichedResultsHm) ## ----plot_pathways_I, fig.width=10, fig.height=8------------------------------ pathwayPlots( pathwayEnrichmentResults=enrichedResultsSigora, columns=2 ) ## ----pathway_network_I, fig.width=12, fig.height=10, warning=FALSE, message=FALSE---- data("sigoraDatabase") pathwayDistancesJaccard <- getPathwayDistances(pathwayData = sigoraDatabase) startingPathways <- pathnetFoundation( mat=pathwayDistancesJaccard, maxDistance=0.8 ) # Get the enriched pathways from the "COVID Pos Over Time" comparison exPathwayNetworkInput <- enrichedResultsSigora %>% filter(comparison == "COVID Pos Over Time") myPathwayNetwork <- pathnetCreate( pathwayEnrichmentResult=exPathwayNetworkInput, foundation=startingPathways ) ## ----plot_pathnet_I, warning=FALSE, fig.height=7------------------------------ pathnetGGraph( myPathwayNetwork, labelProp=0.1, nodeLabelSize=3, nodeLabelOverlaps=8, segColour="red", themeBaseSize = 12 ) ## ----session_information, echo=FALSE------------------------------------------ sessionInfo()