## ----------------------------------------------------------------------------- #if (!requireNamespace("BiocManager", quietly=TRUE)) #install.packages("BiocManager") #BiocManager::install("BgeeDB") ## ----message = FALSE, warning = FALSE----------------------------------------- library(BgeeDB) ## ----------------------------------------------------------------------------- listBgeeSpecies() ## ----------------------------------------------------------------------------- listBgeeSpecies(release = "13.2", order = 2) ## ----------------------------------------------------------------------------- bgee <- Bgee$new(species = "Mus_musculus", dataType = "rna_seq") ## ----------------------------------------------------------------------------- annotation_bgee_mouse <- getAnnotation(bgee) # list the first experiments and libraries lapply(annotation_bgee_mouse, head) ## ----------------------------------------------------------------------------- # download all RNA-seq experiments from mouse data_bgee_mouse <- getData(bgee) # number of experiments downloaded length(data_bgee_mouse) # check the downloaded data lapply(data_bgee_mouse, head) # isolate the first experiment data_bgee_experiment1 <- data_bgee_mouse[[1]] ## ----------------------------------------------------------------------------- # download data for GSE30617 data_bgee_mouse_gse30617 <- getData(bgee, experimentId = "GSE30617") ## ----eval=FALSE--------------------------------------------------------------- # # Examples of data downloading using different filtering combination # # retrieve mouse RNA-Seq data for heart or brain # data_bgee_mouse_filters <- getData(bgee, anatEntityId = c("UBERON:0000955","UBERON:0000948")) # # retrieve mouse RNA-Seq data for heart (UBERON:0000955) or brain (UBERON:0000948) part of the experiment GSE30617 # data_bgee_mouse_filters <- getData(bgee, experimentId = "GSE30617", anatEntityId = c("UBERON:0000955","UBERON:0000948")) # # retrieve mouse RNA-Seq data for heart (UBERON:0000955) or brain (UBERON:0000948) from post-embryonic stage (UBERON:0000092) # data_bgee_mouse_filters <- getData(bgee, stageId = "UBERON:0000092", anatEntityId = c("UBERON:0000955","UBERON:0000948")) ## ----------------------------------------------------------------------------- # use only present calls and fill expression matric with FPKM values gene.expression.mouse.fpkm <- formatData(bgee, data_bgee_mouse_gse30617, callType = "present", stats = "fpkm") gene.expression.mouse.fpkm ## ----------------------------------------------------------------------------- # Creating new Bgee class object bgee <- Bgee$new(species = "Danio_rerio") ## ----------------------------------------------------------------------------- # Loading calls of expression myTopAnatData <- loadTopAnatData(bgee) # Look at the data ## str(myTopAnatData) ## ----eval=FALSE--------------------------------------------------------------- # ## Loading silver and gold 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$new(species = "Danio_rerio", dataType="affymetrix") # myTopAnatData <- loadTopAnatData(bgee, stage="UBERON:0000068", confidence="silver") ## ----eval=FALSE--------------------------------------------------------------- # # if (!requireNamespace("BiocManager", quietly=TRUE)) # # install.packages("BiocManager") # # BiocManager::install("biomaRt") # library(biomaRt) # ensembl <- useMart("ENSEMBL_MART_ENSEMBL", dataset="drerio_gene_ensembl", host="mar2016.archive.ensembl.org") # # # get the mapping of Ensembl genes to phenotypes. It will corresponds to the background genes # universe <- getBM(filters=c("phenotype_source"), value=c("ZFIN"), attributes=c("ensembl_gene_id","phenotype_description"), mart=ensembl) # # # select phenotypes related to pectoral fin # phenotypes <- grep("pectoral fin", unique(universe$phenotype_description), value=T) # # # Foreground genes are those with an annotated phenotype related to "pectoral fin" # myGenes <- unique(universe$ensembl_gene_id[universe$phenotype_description %in% phenotypes]) # # # Prepare the gene list vector # geneList <- factor(as.integer(unique(universe$ensembl_gene_id) %in% myGenes)) # names(geneList) <- unique(universe$ensembl_gene_id) # summary(geneList) # # # Prepare the topGO object # myTopAnatObject <- topAnat(myTopAnatData, geneList) ## ----------------------------------------------------------------------------- data(geneList) myTopAnatObject <- topAnat(myTopAnatData, geneList) ## ----------------------------------------------------------------------------- results <- runTest(myTopAnatObject, algorithm = 'weight', statistic = 'fisher') ## ----------------------------------------------------------------------------- # Display results sigificant at a 1% FDR threshold tableOver <- makeTable(myTopAnatData, myTopAnatObject, results, cutoff = 0.01) head(tableOver) ## ----------------------------------------------------------------------------- # In order to retrieve significant genes mapped to the term " paired limb/fin bud" term <- "UBERON:0004357" termStat(myTopAnatObject, term) # 198 genes mapped to this term for Bgee 14.0 and Ensembl 84 genesInTerm(myTopAnatObject, term) # 48 significant genes mapped to this term for Bgee 14.0 and Ensembl 84 annotated <- genesInTerm(myTopAnatObject, term)[["UBERON:0004357"]] annotated[annotated %in% sigGenes(myTopAnatObject)] ## ----eval = FALSE------------------------------------------------------------- # bgee <- Bgee$new(species="Mus_musculus", release = "14.1") # # delete all old .rds files of species Mus musculus # deleteOldData(bgee) ## ----eval = FALSE------------------------------------------------------------- # bgee <- Bgee$new(species="Mus_musculus", release = "14.1") # # delete local SQLite database of species Mus musculus from Bgee 14.1 # deleteLocalData(bgee)