## ----pubmed1, fig.cap="Psychiatric disorders in PubMed. It has been obtained querying **psychiatric disorder [Title/Abstract] from 1955 to 2016**.", echo=FALSE, fig.wide = TRUE---- library(ggplot2) data.file <- system.file( paste0("extdata", .Platform$file.sep, "psychiatricDisordersPubmed.csv"), package="psygenet2r" ) pmid <- read.delim(data.file, header=TRUE, sep=",") pmid <- pmid[pmid$year<2017 & pmid$year>1950,] pmid$year <- factor(pmid$year) labels <- as.integer(seq(1950, 2016, by=5)) p <- ggplot(pmid, aes ( x = year, y = count ) ) + geom_bar ( stat = "identity", fill = "grey" ) + labs ( title = "Number of publications for psychiatric disorders in PubMed" , x = "year", y = "# of pmids") + theme_classic( ) + scale_x_discrete(breaks=labels, labels=as.character(labels))+ theme( plot.margin = grid::unit ( x = c ( 5, 15, 5, 15 ), units = "mm" ), axis.line = element_line ( size = 0.7, color = "black" ), text = element_text ( size = 14 ) , axis.text.x = element_text ( angle = 45, size = 11, hjust = 1 ) ) p ## ----bioC, eval=FALSE--------------------------------------------------------- # if (!requireNamespace("BiocManager", quietly=TRUE)) # install.packages("BiocManager") # BiocManager::install( "psyGeNET2R" ) ## ----load_library, messages=FALSE--------------------------------------------- library( psygenet2r ) ## ----genes-------------------------------------------------------------------- genesOfInterest <- c("ADCY2", "AKAP13", "ANK3", "ANKS1A", "ATP6V1G3", "ATXN1", "C11orf80", "C15orf53", "CACNA1C", "CACNA1D", "CACNB3", "CROT", "DLG2", "DNAJB4", "DUSP22", "FAM155A", "FLJ16124", "FSTL5", "GATA5", "GNA14", "GPR81", "HHAT", "IFI44", "ITIH3", "KDM5B", "KIF1A", "LOC150197", "MAD1L1", "MAPK10", "MCM9", "MSI2", "NFIX", "NGF", "NPAS3", "ODZ4", "PAPOLG", "PAX1", "PBRM1", "PTPRE", "PTPRT", "RASIP1", "RIMBP2", "RXRG", "SGCG", "SH3PXD2A", "SIPA1L2", "SNX8", "SPERT", "STK39", "SYNE1", "THSD7A", "TNR", "TRANK1", "TRIM9", "UBE2E3", "UBR1", "ZMIZ1", "ZNF274") ## ----search_multiple---------------------------------------------------------- m1 <- psygenetGene( gene = genesOfInterest, database = "ALL", verbose = FALSE, warnings = FALSE ) m1 ## ----gene-disease, fig.height=8, fig.width=8, fig.cap = "Gene-Disease Association Network", fig.wide = TRUE---- plot( m1 ) ## ----gene-psy, fig.cap="Association type barplot according to psychiatric category", fig.wide = TRUE---- geneAttrPlot( m1, type = "evidence index" ) ## ----panther, fig.cap="Panther class analysis of the genes of interest.", message=FALSE, warning=FALSE, fig.wide = TRUE---- pantherGraphic( genesOfInterest, "ALL") ## ----gene-disease-2, fig.cap="Gene-Disease Association Heatmap", fig.wide = TRUE---- plot( m1, type="GDA heatmap") ## ----sentences1_query--------------------------------------------------------- m2 <- psygenetGeneSentences( geneList = genesOfInterest, database = "ALL" ) m2 ## ----sentences2_extraction, warnings=FALSE------------------------------------ sentences <- extractSentences( m2, disorder = "bipolar disorder" ) head(sentences$PUBMED_ID) ## ----jaccard_1, warning=FALSE------------------------------------------------- xx <- jaccardEstimation( genesOfInterest, "bipolar disorder", database = "ALL", nboot = 500 ) xx ## ----jaccard_2---------------------------------------------------------------- extract( xx ) ## ----jaccard_3, warning=FALSE------------------------------------------------- xx <- jaccardEstimation( genesOfInterest, database = "ALL", nboot = 500 ) ## ----bpGenes, fig.cap="Barplot: Genes associated to each of the psychiatric disorders", fig.wide = TRUE---- geneAttrPlot( m1, type = "disease category" ) ## ----bpDis, fig.cap="Barplot: CUIs and psychiatric categories associated to each gene", fig.wide = TRUE---- geneAttrPlot( m1, type = "gene" )