## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(echo = TRUE) ## ----eval=FALSE--------------------------------------------------------------- # if (!requireNamespace("BiocManager", quietly=TRUE)) # install.packages("BiocManager") # BiocManager::install( "psygenet2r" ) ## ----load_library, messages=FALSE--------------------------------------------- library( psygenet2r ) ## ----dataGenet1, echo=FALSE--------------------------------------------------- t1 <- psygenetGene( gene = 4852, database = "ALL") ## ----dataGenet2--------------------------------------------------------------- t1 class( t1 ) ## ----search_gene_1------------------------------------------------------------ t1 <- psygenetGene( gene = 4852, database = "ALL") t1 ## ----search_gene_2------------------------------------------------------------ t2 <- psygenetGene( gene = "NPY", database = "ALL" ) t2 ## ----searcg_gene_class-------------------------------------------------------- class( t1 ) class( t2 ) ## ----plot_disease, fig.width=8, fig.height=8---------------------------------- plot( t1, type = "GDA network" ) ## ----plot_psychiatric, fig.width=8, fig.height=8------------------------------ plot( t1, type = "GDCA network" ) ## ----search_multiple_genes---------------------------------------------------- genesOfInterest <- c( "COMT", "CLOCK", "DRD3", "GNB3", "HTR1A", "MAOA", "HTR2A","HTR2C", "HTR6", "SLC6A4", "ACE", "BDNF", "DRD4", "HTR1B", "HTR2B", "HTR2C", "MTHFR", "SLC6A3", "TPH1", "SLC6A2", "GABRA3" ) ## ----search_multiple_search--------------------------------------------------- m1 <- psygenetGene( gene = genesOfInterest, database = "ALL", verbose = TRUE ) ## ----show_multiple------------------------------------------------------------ m1 ## ----plot_psychiatric1a, fig.height=8, fig.width=8--------------------------- plot( m1 ) ## ----plot_psychiatric1b, warning=FALSE, fig.height=8, fig.width=8------------ plot( m1, type = "GDCA network" ) ## ----heatmap_disease_m, fig.height=8, fig.width=8---------------------------- plot( m1, type="GDA heatmap" ) ## ----plot_psychiatric_heamap, warning = FALSE, fig.height=8, fig.width=8----- plot( m1, type = "GDCA heatmap" ) ## ----panther_gene, fig.height=8, fig.width=8--------------------------------- genesOfInterest <- unique( genesOfInterest ) pantherGraphic( genesOfInterest, "ALL" ) ## ----plot_diseaseBarplot, fig.height=8, fig.width=8-------------------------- geneAttrPlot( m1, type = "disease category" ) ## ----plot_diseaseBarplotGene, fig.height=8, fig.width=8---------------------- geneAttrPlot( m1, type = "gene" ) ## ----plot_pie, fig.width=8, fig.height=8-------------------------------------- geneAttrPlot( m1, type = "pie" ) ## ----barplotIP, fig.width=8, fig.height=8------------------------------------- geneAttrPlot( m1, type = "evidence index" ) ## ----enrichment--------------------------------------------------------------- tbl <- enrichedPD( genesOfInterest, database = "ALL") tbl ## ----topAnat, eval=FALSE------------------------------------------------------ # tpAnat <- topAnatEnrichment( genesOfInterest, cutOff = 1 ) ## ----load_topAnat, echo=FALSE------------------------------------------------- load( system.file( "extdata", "topAnat.RData", package="psygenet2r" ) ) ## ----show_topAnat------------------------------------------------------------- head( tpAnat ) ## ----gda_sentenceGene--------------------------------------------------------- genesOfInterest sss <- psygenetGeneSentences( geneList = genesOfInterest, database = "ALL") sss geneSentences <- extractSentences( object = sss, disorder = "alcohol abuse") head(geneSentences) dim( geneSentences ) ## ----getUMLS------------------------------------------------------------------ getUMLs( "depressive", database = "ALL" ) ## ----search_diseaseId_1------------------------------------------------------- d1 <- psygenetDisease( disease = "umls:C1839839", database = "ALL", evidenceIndex = c('>', 0.5 ) ) d1 ## ----search_diseaseName_1----------------------------------------------------- d2 <- psygenetDisease( disease = "major affective disorder 2", database = "ALL", evidenceIndex = c('>', 0.5 ) ) d2 ## ----search_gene_class-------------------------------------------------------- class( d1 ) class( d2 ) ## ----plot_visualizing_single_disease_search, fig.width=8, fig.height=8-------- plot ( d1, geneColor = "turquoise2", diseaseColor = "black") ## ----diseaseList-------------------------------------------------------------- diseasesOfInterest <- c( "chronic schizophrenia","alcohol use disorder" ) ## ----search_diseases_1-------------------------------------------------------- tt <- psygenetDisease( disease = diseasesOfInterest, database = "ALL" ) tt ## ----search_diseases_2-------------------------------------------------------- dm <- psygenetDisease( disease = c( "umls:C0221765", "umls:C0001956" ), database = "ALL" ) dm ## ----search_diseases_3-------------------------------------------------------- tm <- psygenetDisease( disease = c( "chronic schizophrenia","umls:C0001956" ), database = "ALL" ) tm ## ----search_gene_class_2------------------------------------------------------ class( tt ) class( dm ) class( tm ) ## ----plot_disease_tm---------------------------------------------------------- plot( tm ) ## ----heatmap_disease_tm, warning = FALSE, fig.wide = TRUE-------------------- plot( tm, type = "GDCA heatmap" ) ## ----barplot_visualizing_single_disease_search, fig.width=8, fig.height=8----- plot( d1, name = "major affective disorder 2", type = "publications" ) ## ----barplot_visualizing_single_gene_search, fig.width=8, fig.height=8-------- plot( t1, name = "NPY", type = "publications", barColor = "blue") ## ----jaccardObjectEx1, echo=FALSE, warning=FALSE, message=FALSE--------------- genes_interest <- c("SLC6A4", "DRD2", "HTR1B", "PLP1", "TH", "DRD3") ji1 <- jaccardEstimation(genes_interest, database = "ALL") ## ----jaccardObjectEx2--------------------------------------------------------- ji1 class( ji1 ) ## ----ji_1, warnings=FALSE----------------------------------------------------- genes_interest <- c("SLC6A4", "DRD2", "HTR1B", "PLP1", "TH", "DRD3") ji1 <- jaccardEstimation(genes_interest, database = "ALL") ## ----ji_2, warnings=FALSE----------------------------------------------------- disease_interest <- c("delirium", "bipolar i disorder", "severe depression", "cocaine dependence") ji2 <- jaccardEstimation(genes_interest, disease_interest, database = "ALL") ## ----ji_3, warnings=FALSE----------------------------------------------------- ji3 <- jaccardEstimation(disease_interest, database = "ALL") ## ----ji1_extract-------------------------------------------------------------- head(extract(ji1)) tail(extract(ji1)) ## ----ji1_plot, fig.width=8, fig.height=8-------------------------------------- plot(ji1, cutOff = 0.1) ## ----ji2_plot, fig.width=8, fig.height=8-------------------------------------- plot(ji2) ## ----ji3_plot, fig.width=8, fig.height=8-------------------------------------- plot(ji3)