Example data for use with the beadarray package
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1 Example data for use with the beadarray package Mark Dunning November 1, 2018 Contents 1 Data Introduction 1 2 Loading the data 2 3 Data creation 4 1 Data Introduction This package provides a lightweight dataset for those wishing to try out the examples within the beadarray package. The data in this package are a subset of the MAQC bead-level data available in the beadarrayusecases package. Bead-level refers to the availability of intensity and location information for each bead on each BeadArray in an experiment. In this dataset, BeadArrays were hybridized with either Universal Human Reference RNA (UHRR, Stratagene) or Brain Reference RNA (Ambion) as used in the MAQC project. This pacakge includes a representation of the bead-level data for 2 arrays in the data object examplebldata, which was created by beadarray. The summarised data for all 12 arrays are given in the examplesummarydata object, which was creating by first reading the bead-level data for all 12 sections into beadarray and then summarising using the procedures described in the vignette for BeadArrayUseCases. 1
2 2 Loading the data The example datasets can be loaded using the data function. The first dataset comprises two sections from the bead-level MAQC dataset generated at Cancer Research Uk (Cambridge Research Institute) that have been read in using the beadarray package. The second dataset is the summarised data of all sections from the same dataset. > library(beadarrayexampledata) > data(examplebldata) > examplebldata Experiment information $sdffile [1] "/home/dunnin01/software/r-devel/library/beadarrayusecases/extdata/beadlevelbabfile $platformclass [1] "Slide" $annotation [1] "Humanv3" Per-section data Targets directory 1 /home/dunnin01/software/r-devel/library/beadarrayusecases/extdata/beadlevelbabfiles 2 /home/dunnin01/software/r-devel/library/beadarrayusecases/extdata/beadlevelbabfiles sectionname textfile greenimage greenlocs greenxml _B _B.bab <NA> _B.bab <NA> _A _A.bab <NA> _A.bab <NA> Metrics Date Matrix Section RegGrn FocusGrn SatGrn 1 3/13/2009 6:45:04 PM B /01/09 04: A P95Grn P05Grn RegRed FocusRed SatRed P95Red P05Red 2
3 SampleGroup [1] " _B" " _A" numbeads [1] Per-bead data (@beaddata) Raw data from section _B ProbeID GrnX GrnY Grn wts [1,] [2,] [3,] [4,] [5,] more rows of data... data for 1 more section/s > data(examplesummarydata) > examplesummarydata ExpressionSetIllumina (storagemode: list) assaydata: features, 12 samples element names: exprs, se.exprs, nobservations protocoldata: none phenodata rownames: _B _B _A (12 total) varlabels: sampleid SampleFac varmetadata: labeldescription featuredata featurenames: ILMN_ ILMN_ ILMN_ (49576 total) 3
4 fvarlabels: ArrayAddressID IlluminaID Status fvarmetadata: labeldescription experimentdata: use 'experimentdata(object)' Annotation: Humanv3 QC Information Available Slots: QC Items: Date, Matrix,..., SampleGroup, numbeads samplenames: _B, _B,..., _A, _A > pdata(examplesummarydata) sampleid SampleFac _B _B UHRR _B _B UHRR _B _B UHRR _B _B UHRR _B _B UHRR _B _B UHRR _B _B Brain _H _H Brain _B _B Brain _A _A Brain _A _A Brain _A _A Brain 3 Data creation The following commands were used to create the data included with this package. > require(beadarrayusecases) > targets <- read.table(system.file("extdata/beadlevelbabfiles/targetsht12.txt", packa > sn <- paste(targets[,3], targets[,4], sep="_") > babfilepath <- system.file("extdata/beadlevelbabfiles", package = "BeadArrayUseCases > examplebldata <- readillumina(dir=babfilepath, sectionnames=sn[c(1,12)], useimages=f > bsh <- BASH(exampleBLData,array=c(1,2)) > examplebldata <- setweights(examplebldata, wts = bsh$wts, array=1:2) > data <- readillumina(dir=babfilepath, sectionnames=sn, useimages=false, illuminaanno > grnchannel <- new("illuminachannel", transfun = loggreenchanneltransform, outlierfun > grnchannel.unlogged <- new("illuminachannel", transfun = greenchanneltransform, outl 4
5 > examplesummarydata <- summarize(data, list(grnchannel, grnchannel.unlogged), usesamp > pdata(examplesummarydata)[,2] <- targets[,2] > > 5
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