## ----style, echo=FALSE, results='asis'---------------------------------------- BiocStyle::markdown() ## ----echo=FALSE--------------------------------------------------------------- suppressPackageStartupMessages(library(SummarizedExperiment)) suppressPackageStartupMessages(data(airway, package="airway")) ## ----------------------------------------------------------------------------- library(SummarizedExperiment) data(airway, package="airway") se <- airway se ## ----assays, eval = FALSE----------------------------------------------------- # assays(se)$counts ## ----assays_table, echo = FALSE----------------------------------------------- knitr::kable(assays(se)$counts[1:10,]) ## ----rowRanges---------------------------------------------------------------- rowRanges(se) ## ----colData------------------------------------------------------------------ colData(se) ## ----columnSubset------------------------------------------------------------- # subset for only those samples treated with dexamethasone se[, se$dex == "trt"] ## ----metadata----------------------------------------------------------------- metadata(se) ## ----metadata-formula--------------------------------------------------------- metadata(se)$formula <- counts ~ dex + albut metadata(se) ## ----constructRSE------------------------------------------------------------- nrows <- 200 ncols <- 6 counts <- matrix(runif(nrows * ncols, 1, 1e4), nrows) rowRanges <- GRanges(rep(c("chr1", "chr2"), c(50, 150)), IRanges(floor(runif(200, 1e5, 1e6)), width=100), strand=sample(c("+", "-"), 200, TRUE), feature_id=sprintf("ID%03d", 1:200)) colData <- DataFrame(Treatment=rep(c("ChIP", "Input"), 3), row.names=LETTERS[1:6]) SummarizedExperiment(assays=list(counts=counts), rowRanges=rowRanges, colData=colData) ## ----constructSE-------------------------------------------------------------- SummarizedExperiment(assays=list(counts=counts), colData=colData) ## ----construct_se3------------------------------------------------------------ a1 <- matrix(runif(24), ncol=6, dimnames=list(letters[1:4], LETTERS[1:6])) a2 <- matrix(rpois(24, 0.8), ncol=6) a3 <- matrix(101:124, ncol=6, dimnames=list(NULL, LETTERS[1:6])) se3 <- SummarizedExperiment(SimpleList(a1, a2, a3)) ## ----top_level_dimnames------------------------------------------------------- dimnames(se3) ## ----top_level_dimnames_are_propagated---------------------------------------- assay(se3, 2) # this is 'a2', but with the top-level dimnames on it assay(se3, 3) # this is 'a3', but with the top-level dimnames on it ## ----assay_level_dimnames----------------------------------------------------- assay(se3, 2, withDimnames=FALSE) # identical to 'a2' assay(se3, 3, withDimnames=FALSE) # identical to 'a3' rownames(se3) <- strrep(letters[1:4], 3) dimnames(se3) assay(se3, 1) # this is 'a1', but with the top-level dimnames on it assay(se3, 1, withDimnames=FALSE) # identical to 'a1' ## ----2d----------------------------------------------------------------------- # subset the first five transcripts and first three samples se[1:5, 1:3] ## ----colDataExtraction-------------------------------------------------------- se[, se$cell == "N61311"] ## ----getSet------------------------------------------------------------------- counts <- matrix(1:15, 5, 3, dimnames=list(LETTERS[1:5], LETTERS[1:3])) dates <- SummarizedExperiment(assays=list(counts=counts), rowData=DataFrame(month=month.name[1:5], day=1:5)) # Subset all January assays dates[rowData(dates)$month == "January", ] ## ----assay_assays------------------------------------------------------------- assays(se) assays(se)[[1]][1:5, 1:5] # assay defaults to the first assay if no i is given assay(se)[1:5, 1:5] assay(se, 1)[1:5, 1:5] ## ----overlap------------------------------------------------------------------ # Subset for only rows which are in the interval 100,000 to 110,000 of # chromosome 1 roi <- GRanges(seqnames="1", ranges=100000:1100000) subsetByOverlaps(se, roi) ## ----------------------------------------------------------------------------- sessionInfo()