## ----style, echo=FALSE, results='asis'------------------------------------- BiocStyle::markdown() ## ----include = FALSE------------------------------------------------------- # download current version of SE diagram #download.file("https://docs.google.com/feeds/download/drawings/Export?id=18OcDb80FpvSGRYnFl-8vUqwNNLaNHrG1I9SWKHCselo&exportFormat=svg", "SE.svg") download.file("https://docs.google.com/feeds/download/drawings/Export?id=1kiC8Qlo1mhSnLDqkGiRNPSo6GWn3C2duBszCFbJCB-g&exportFormat=svg", "SE.svg") ## ---- 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) ## ----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) ## ----rseSubclass----------------------------------------------------------- setClass("MyRSESubclass", contains="RangedSummarizedExperiment", representation=representation( slot1="integer", slot2="function" ## ... maybe more ... ) )