## ------------------------------------------------------------------------ # source("https://bioconductor.org/biocLite.R") # biocLite("BgeeDB") ## ---- message = FALSE, warning = FALSE----------------------------------- library(BgeeDB) ## ------------------------------------------------------------------------ listBgeeSpecies() ## ------------------------------------------------------------------------ listBgeeSpecies(release = "13.2", order = 2) ## ------------------------------------------------------------------------ bgee <- Bgee$new(species = "Mus_musculus", dataType = "rna_seq") ## ------------------------------------------------------------------------ annotation_bgee_mouse <- getAnnotation(bgee) # list the first experiments and libraries lapply(annotation_bgee_mouse, head) ## ------------------------------------------------------------------------ # download all RNA-seq experiments from mouse data_bgee_mouse <- getData(bgee) # number of experiments downloaded length(data_bgee_mouse) # check the downloaded data lapply(data_bgee_mouse, head) # isolate the first experiment data_bgee_experiment1 <- data_bgee_mouse[[1]] ## ------------------------------------------------------------------------ # download data for GSE30617 data_bgee_mouse_gse30617 <- getData(bgee, experimentId = "GSE30617") ## ------------------------------------------------------------------------ # use only present calls and fill expression matric with RPKM values gene.expression.mouse.rpkm <- formatData(bgee, data_bgee_mouse_gse30617, callType = "present", stats = "rpkm") gene.expression.mouse.rpkm ## ------------------------------------------------------------------------ # Creating new Bgee class object bgee <- Bgee$new(species = "Danio_rerio") ## ------------------------------------------------------------------------ # Loading calls of expression myTopAnatData <- loadTopAnatData(bgee) # Look at the data str(myTopAnatData) ## ---- eval=FALSE--------------------------------------------------------- ## ## Loading only high-quality expression calls from affymetrix data made on embryonic samples only ## ## This is just given as an example, but is not run in this vignette because only few data are returned ## ## bgee <- Bgee$new(species = "Danio_rerio", dataType="affymetrix") ## ## myTopAnatData <- loadTopAnatData(bgee, stage="UBERON:0000068", confidence="high_quality") ## ------------------------------------------------------------------------ # source("https://bioconductor.org/biocLite.R") # biocLite("biomaRt") library(biomaRt) ensembl <- useMart("ensembl") ensembl <- useDataset("drerio_gene_ensembl", mart=ensembl) # Foreground genes are those with GO annotation "spermatogenesis" myGenes <- getBM(attributes= "ensembl_gene_id", filters=c("go_id"), values=list(c("GO:0007283")), mart=ensembl) # Background are all genes with GO annotation universe <- getBM(attributes= "ensembl_gene_id", filters=c("with_go_go"), values=list(c(TRUE)), mart=ensembl) # Prepare the gene list vector geneList <- factor(as.integer(universe[,1] %in% myGenes[,1])) names(geneList) <- universe[,1] head(geneList) summary(geneList == 1) # Prepare the topGO object myTopAnatObject <- topAnat(myTopAnatData, geneList) ## ------------------------------------------------------------------------ results <- runTest(myTopAnatObject, algorithm = 'classic', statistic = 'fisher') ## ---- eval=FALSE--------------------------------------------------------- ## results <- runTest(myTopAnatObject, algorithm = 'weight', statistic = 'fisher') ## ------------------------------------------------------------------------ # Display results sigificant at a 5% FDR threshold makeTable(myTopAnatData, myTopAnatObject, results, cutoff = 0.05)