beadarray package: problem with object made by createBeadSummaryData
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Krys Kelly ▴ 270
@krys-kelly-1768
Last seen 9.7 years ago
Hello Using R 2.5.1, I have read in and explored the bead level data from 5 Illumina mouse-6 slides which have 6 arrays per slide and 2 images per array. I have also created and saved bead summary data trying out a few options for the background correction. When I was using R 2.5.1 and the corresponding versions of bioconductor and beadarray and everything worked fine. But I want to upgrade to R 2.6.0. I have installed R 2.6.0 and the corresponding versions of bioconductor and beadarray. I now find that se.exprs is completely filled with NAs. I have compared the documentation from the two versions of beadarray expecting that there was a new option that I needed to specify, but I can't find anything that would account for the NAs Please can you suggest what the problem is. My program code, output from the BSData object and sessionInfo() are pasted below. Thanks Krys PROGRAM CODE ------------ # Read the bead level data BLData39A <- readIllumina(arrayNames=c("1863191039_A_1", "1863191039_A_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData39B <- readIllumina(arrayNames=c("1863191039_B_1", "1863191039_B_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData39C <- readIllumina(arrayNames=c("1863191039_C_1", "1863191039_C_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData39D <- readIllumina(arrayNames=c("1863191039_D_1", "1863191039_D_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData39E <- readIllumina(arrayNames=c("1863191039_E_1", "1863191039_E_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData39F <- readIllumina(arrayNames=c("1863191039_F_1", "1863191039_F_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData46A <- readIllumina(arrayNames=c("1863191046_A_1", "1863191046_A_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData46B <- readIllumina(arrayNames=c("1863191046_B_1", "1863191046_B_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData46C <- readIllumina(arrayNames=c("1863191046_C_1", "1863191046_C_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData46D <- readIllumina(arrayNames=c("1863191046_D_1", "1863191046_D_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData46E <- readIllumina(arrayNames=c("1863191046_E_1", "1863191046_E_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData46F <- readIllumina(arrayNames=c("1863191046_F_1", "1863191046_F_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData49A <- readIllumina(arrayNames=c("1863191049_A_1", "1863191049_A_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData49B <- readIllumina(arrayNames=c("1863191049_B_1", "1863191049_B_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData49C <- readIllumina(arrayNames=c("1863191049_C_1", "1863191049_C_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData49D <- readIllumina(arrayNames=c("1863191049_D_1", "1863191049_D_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData49E <- readIllumina(arrayNames=c("1863191049_E_1", "1863191049_E_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData49F <- readIllumina(arrayNames=c("1863191049_F_1", "1863191049_F_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData50A <- readIllumina(arrayNames=c("1863191050_A_1", "1863191050_A_2"), textType=".txt", backgroundMethod="none", rmoffset=0,normalizeMethod="none", metrics=FALSE) BLData50B <- readIllumina(arrayNames=c("1863191050_B_1", "1863191050_B_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData50C <- readIllumina(arrayNames=c("1863191050_C_1", "1863191050_C_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData50D <- readIllumina(arrayNames=c("1863191050_D_1", "1863191050_D_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData50E <- readIllumina(arrayNames=c("1863191050_E_1", "1863191050_E_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData50F <- readIllumina(arrayNames=c("1863191050_F_1", "1863191050_F_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData52A <- readIllumina(arrayNames=c("1863191052_A_1", "1863191052_A_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData52B <- readIllumina(arrayNames=c("1863191052_B_1", "1863191052_B_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData52C <- readIllumina(arrayNames=c("1863191052_C_1", "1863191052_C_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData52D <- readIllumina(arrayNames=c("1863191052_D_1", "1863191052_D_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData52E <- readIllumina(arrayNames=c("1863191052_E_1", "1863191052_E_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) BLData52F <- readIllumina(arrayNames=c("1863191052_F_1", "1863191052_F_2"), textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", metrics=FALSE) # Creation of summary data BSData39A <- createBeadSummaryData(BLData39A, log=FALSE,n=3, imagesPerArray=2) BSData39B <- createBeadSummaryData(BLData39B, log=FALSE,n=3, imagesPerArray=2) BSData39C <- createBeadSummaryData(BLData39C, log=FALSE,n=3, imagesPerArray=2) BSData39D <- createBeadSummaryData(BLData39D, log=FALSE,n=3, imagesPerArray=2) BSData39E <- createBeadSummaryData(BLData39E, log=FALSE,n=3, imagesPerArray=2) BSData39F <- createBeadSummaryData(BLData39F, log=FALSE,n=3, imagesPerArray=2) BSData46A <- createBeadSummaryData(BLData46A, log=FALSE,n=3, imagesPerArray=2) BSData46B <- createBeadSummaryData(BLData46B, log=FALSE,n=3, imagesPerArray=2) BSData46C <- createBeadSummaryData(BLData46C, log=FALSE,n=3, imagesPerArray=2) BSData46D <- createBeadSummaryData(BLData46D, log=FALSE,n=3, imagesPerArray=2) BSData46E <- createBeadSummaryData(BLData46E, log=FALSE,n=3, imagesPerArray=2) BSData46F <- createBeadSummaryData(BLData46F, log=FALSE,n=3, imagesPerArray=2) BSData49A <- createBeadSummaryData(BLData49A, log=FALSE,n=3, imagesPerArray=2) BSData49B <- createBeadSummaryData(BLData49B, log=FALSE,n=3, imagesPerArray=2) BSData49C <- createBeadSummaryData(BLData49C, log=FALSE,n=3, imagesPerArray=2) BSData49D <- createBeadSummaryData(BLData49D, log=FALSE,n=3, imagesPerArray=2) BSData49E <- createBeadSummaryData(BLData49E, log=FALSE,n=3, imagesPerArray=2) BSData49F <- createBeadSummaryData(BLData49F, log=FALSE,n=3, imagesPerArray=2) BSData50A <- createBeadSummaryData(BLData50A, log=FALSE,n=3, imagesPerArray=2) BSData50B <- createBeadSummaryData(BLData50B, log=FALSE,n=3, imagesPerArray=2) BSData50C <- createBeadSummaryData(BLData50C, log=FALSE,n=3, imagesPerArray=2) BSData50D <- createBeadSummaryData(BLData50D, log=FALSE,n=3, imagesPerArray=2) BSData50E <- createBeadSummaryData(BLData50E, log=FALSE,n=3, imagesPerArray=2) BSData50F <- createBeadSummaryData(BLData50F, log=FALSE,n=3, imagesPerArray=2) BSData52A <- createBeadSummaryData(BLData52A, log=FALSE,n=3, imagesPerArray=2) BSData52B <- createBeadSummaryData(BLData52B, log=FALSE,n=3, imagesPerArray=2) BSData52C <- createBeadSummaryData(BLData52C, log=FALSE,n=3, imagesPerArray=2) BSData52D <- createBeadSummaryData(BLData52D, log=FALSE,n=3, imagesPerArray=2) BSData52E <- createBeadSummaryData(BLData52E, log=FALSE,n=3, imagesPerArray=2) BSData52F <- createBeadSummaryData(BLData52F, log=FALSE,n=3, imagesPerArray=2) BSData <- combine( BSData39A, BSData39B, BSData39C, BSData39D, BSData39E, BSData39F, BSData46A, BSData46B, BSData46C, BSData46D, BSData46E, BSData46F, BSData49A, BSData49B, BSData49C, BSData49D, BSData49E, BSData49F, BSData50A, BSData50B, BSData50C, BSData50D, BSData50E, BSData50F, BSData52A, BSData52B, BSData52C, BSData52D, BSData52E, BSData52F) OUTPUT FROM SESSSION USING BSData --------------------------------- > BSData ExpressionSetIllumina (storageMode: list) assayData: 48358 features, 30 samples element names: exprs, se.exprs, NoBeads phenoData rowNames: 1863191039_A_1, 1863191039_B_1, ..., 1863191052_F_1 (30 total) varLabels and varMetadata description: arrayName: NA featureData featureNames: fvarLabels and fvarMetadata description: none experimentData: use 'experimentData(object)' Annotation: illuminaProbeIDs > slotNames(BSData) [1] "QC" "assayData" "phenoData" [4] "featureData" "experimentData" "annotation" [7] ".__classVersion__" > names(assayData(BSData)) [1] "exprs" "se.exprs" "NoBeads" > dim(assayData(BSData)$exprs) [1] 48358 30 > dim(assayData(BSData)$se.exprs) [1] 48358 30 > exprs(BSData)[1:10,1:2] 1863191039_A_1 1863191039_B_1 10243 84.31794 90.07728 10280 77.86524 78.17629 10575 148.53714 154.93587 20048 74.88917 71.63645 20296 18520.55707 20620.06535 20343 60.40684 61.49921 20373 64.48009 63.93970 20431 26997.07647 29130.48258 50008 114.36110 267.88378 50014 47.48685 43.68849 > se.exprs(BSData)[1:10,1:2] 1863191039_A_1 1863191039_B_1 10243 NA NA 10280 NA NA 10575 NA NA 20048 NA NA 20296 NA NA 20343 NA NA 20373 NA NA 20431 NA NA 50008 NA NA 50014 NA NA > pData(BSData)[,1] 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 1863191039_F_1 1863191046_A_1 1863191046_B_1 1863191046_C_1 1863191046_D_1 1863191039_F_1 1863191046_A_1 1863191046_B_1 1863191046_C_1 1863191046_D_1 1863191046_E_1 1863191046_F_1 1863191049_A_1 1863191049_B_1 1863191049_C_1 1863191046_E_1 1863191046_F_1 1863191049_A_1 1863191049_B_1 1863191049_C_1 1863191049_D_1 1863191049_E_1 1863191049_F_1 1863191050_A_1 1863191050_B_1 1863191049_D_1 1863191049_E_1 1863191049_F_1 1863191050_A_1 1863191050_B_1 1863191050_C_1 1863191050_D_1 1863191050_E_1 1863191050_F_1 1863191052_A_1 1863191050_C_1 1863191050_D_1 1863191050_E_1 1863191050_F_1 1863191052_A_1 1863191052_B_1 1863191052_C_1 1863191052_D_1 1863191052_E_1 1863191052_F_1 1863191052_B_1 1863191052_C_1 1863191052_D_1 1863191052_E_1 1863191052_F_1 30 Levels: 1863191039_A_1 1863191039_B_1 1863191039_C_1 ... 1863191052_F_1 > pData(BSData)[,2] NULL > pData(BSData)[,2] NULL > pData(BSData)[,1] 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 1863191039_F_1 1863191046_A_1 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 1863191039_F_1 1863191046_A_1 1863191046_B_1 1863191046_C_1 1863191046_D_1 1863191046_E_1 1863191046_F_1 1863191049_A_1 1863191049_B_1 1863191046_B_1 1863191046_C_1 1863191046_D_1 1863191046_E_1 1863191046_F_1 1863191049_A_1 1863191049_B_1 1863191049_C_1 1863191049_D_1 1863191049_E_1 1863191049_F_1 1863191050_A_1 1863191050_B_1 1863191050_C_1 1863191049_C_1 1863191049_D_1 1863191049_E_1 1863191049_F_1 1863191050_A_1 1863191050_B_1 1863191050_C_1 1863191050_D_1 1863191050_E_1 1863191050_F_1 1863191052_A_1 1863191052_B_1 1863191052_C_1 1863191052_D_1 1863191050_D_1 1863191050_E_1 1863191050_F_1 1863191052_A_1 1863191052_B_1 1863191052_C_1 1863191052_D_1 1863191052_E_1 1863191052_F_1 1863191052_E_1 1863191052_F_1 30 Levels: 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 ... 1863191052_F_1 > pData(BSData)[,1] 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 1863191039_F_1 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 1863191039_F_1 1863191046_A_1 1863191046_B_1 1863191046_C_1 1863191046_D_1 1863191046_E_1 1863191046_F_1 1863191046_A_1 1863191046_B_1 1863191046_C_1 1863191046_D_1 1863191046_E_1 1863191046_F_1 1863191049_A_1 1863191049_B_1 1863191049_C_1 1863191049_D_1 1863191049_E_1 1863191049_F_1 1863191049_A_1 1863191049_B_1 1863191049_C_1 1863191049_D_1 1863191049_E_1 1863191049_F_1 1863191050_A_1 1863191050_B_1 1863191050_C_1 1863191050_D_1 1863191050_E_1 1863191050_F_1 1863191050_A_1 1863191050_B_1 1863191050_C_1 1863191050_D_1 1863191050_E_1 1863191050_F_1 1863191052_A_1 1863191052_B_1 1863191052_C_1 1863191052_D_1 1863191052_E_1 1863191052_F_1 1863191052_A_1 1863191052_B_1 1863191052_C_1 1863191052_D_1 1863191052_E_1 1863191052_F_1 30 Levels: 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 ... 1863191052_F_1 > > SESSION INFO ------------ > sessionInfo() R version 2.6.0 (2007-10-03) i386-pc-mingw32 locale: LC_COLLATE=English_United Kingdom.1252;LC_CTYPE=English_United Kingdom.1252;LC_MONETARY=English_United Kingdom.1252;LC_NUMERIC=C;LC_TIME=English_United Kingdom.1252 attached base packages: [1] tools stats graphics grDevices utils datasets methods base other attached packages: [1] beadarray_1.6.0 affy_1.16.0 preprocessCore_1.0.0 affyio_1.6.1 [5] geneplotter_1.16.0 lattice_0.16-5 annotate_1.16.1 xtable_1.5-2 [9] AnnotationDbi_1.0.6 RSQLite_0.6-4 DBI_0.2-4 Biobase_1.16.1 [13] limma_2.12.0 loaded via a namespace (and not attached): [1] grid_2.6.0 KernSmooth_2.22-21 RColorBrewer_1.0-2 > > > > pData(BSData)[1,1] 1863191039_A_1 1863191039_A_1 30 Levels: 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 ... 1863191052_F_1 > Dr Krystyna A Kelly (Krys) Department of Pathology University of Cambridge, Tennis Court Road, Cambridge CB2 1QP Tel: 01223 333331 and MRC Biostatistics Unit Institute of Public Health, Robinson Way, Cambridge CB2 0SR Tel: 01223 767408 Email: kak28 at cam.ac.uk
beadarray beadarray • 1.3k views
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Matt Ritchie ▴ 460
@matt-ritchie-2048
Last seen 10.2 years ago
Hi Krys, This is a bug, which has been fixed in beadarray 1.7.2. Thanks for pointing it out! Best wishes, Matt > Hello > > Using R 2.5.1, I have read in and explored the bead level data from 5 > Illumina mouse-6 slides which have 6 arrays per slide and 2 images per > array. > > I have also created and saved bead summary data trying out a few options for > the background correction. > > When I was using R 2.5.1 and the corresponding versions of bioconductor and > beadarray and everything worked fine. > > But I want to upgrade to R 2.6.0. I have installed R 2.6.0 and the > corresponding versions of bioconductor and beadarray. I now find that > se.exprs is completely filled with NAs. > > I have compared the documentation from the two versions of beadarray > expecting that there was a new option that I needed to specify, but I can't > find anything that would account for the NAs > > Please can you suggest what the problem is. > > My program code, output from the BSData object and sessionInfo() are pasted > below. > > Thanks > > Krys > > > PROGRAM CODE > ------------ > # Read the bead level data > BLData39A <- readIllumina(arrayNames=c("1863191039_A_1", "1863191039_A_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData39B <- readIllumina(arrayNames=c("1863191039_B_1", "1863191039_B_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData39C <- readIllumina(arrayNames=c("1863191039_C_1", "1863191039_C_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData39D <- readIllumina(arrayNames=c("1863191039_D_1", "1863191039_D_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData39E <- readIllumina(arrayNames=c("1863191039_E_1", "1863191039_E_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData39F <- readIllumina(arrayNames=c("1863191039_F_1", "1863191039_F_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > > BLData46A <- readIllumina(arrayNames=c("1863191046_A_1", "1863191046_A_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData46B <- readIllumina(arrayNames=c("1863191046_B_1", "1863191046_B_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData46C <- readIllumina(arrayNames=c("1863191046_C_1", "1863191046_C_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData46D <- readIllumina(arrayNames=c("1863191046_D_1", "1863191046_D_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData46E <- readIllumina(arrayNames=c("1863191046_E_1", "1863191046_E_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData46F <- readIllumina(arrayNames=c("1863191046_F_1", "1863191046_F_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > > BLData49A <- readIllumina(arrayNames=c("1863191049_A_1", "1863191049_A_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData49B <- readIllumina(arrayNames=c("1863191049_B_1", "1863191049_B_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData49C <- readIllumina(arrayNames=c("1863191049_C_1", "1863191049_C_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData49D <- readIllumina(arrayNames=c("1863191049_D_1", "1863191049_D_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData49E <- readIllumina(arrayNames=c("1863191049_E_1", "1863191049_E_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData49F <- readIllumina(arrayNames=c("1863191049_F_1", "1863191049_F_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > > BLData50A <- readIllumina(arrayNames=c("1863191050_A_1", "1863191050_A_2"), > textType=".txt", backgroundMethod="none", rmoffset=0,normalizeMethod="none", > metrics=FALSE) > BLData50B <- readIllumina(arrayNames=c("1863191050_B_1", "1863191050_B_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData50C <- readIllumina(arrayNames=c("1863191050_C_1", "1863191050_C_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData50D <- readIllumina(arrayNames=c("1863191050_D_1", "1863191050_D_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData50E <- readIllumina(arrayNames=c("1863191050_E_1", "1863191050_E_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData50F <- readIllumina(arrayNames=c("1863191050_F_1", "1863191050_F_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > > BLData52A <- readIllumina(arrayNames=c("1863191052_A_1", "1863191052_A_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData52B <- readIllumina(arrayNames=c("1863191052_B_1", "1863191052_B_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData52C <- readIllumina(arrayNames=c("1863191052_C_1", "1863191052_C_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData52D <- readIllumina(arrayNames=c("1863191052_D_1", "1863191052_D_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData52E <- readIllumina(arrayNames=c("1863191052_E_1", "1863191052_E_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData52F <- readIllumina(arrayNames=c("1863191052_F_1", "1863191052_F_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > > # Creation of summary data > BSData39A <- createBeadSummaryData(BLData39A, log=FALSE,n=3, > imagesPerArray=2) > BSData39B <- createBeadSummaryData(BLData39B, log=FALSE,n=3, > imagesPerArray=2) > BSData39C <- createBeadSummaryData(BLData39C, log=FALSE,n=3, > imagesPerArray=2) > BSData39D <- createBeadSummaryData(BLData39D, log=FALSE,n=3, > imagesPerArray=2) > BSData39E <- createBeadSummaryData(BLData39E, log=FALSE,n=3, > imagesPerArray=2) > BSData39F <- createBeadSummaryData(BLData39F, log=FALSE,n=3, > imagesPerArray=2) > > BSData46A <- createBeadSummaryData(BLData46A, log=FALSE,n=3, > imagesPerArray=2) > BSData46B <- createBeadSummaryData(BLData46B, log=FALSE,n=3, > imagesPerArray=2) > BSData46C <- createBeadSummaryData(BLData46C, log=FALSE,n=3, > imagesPerArray=2) > BSData46D <- createBeadSummaryData(BLData46D, log=FALSE,n=3, > imagesPerArray=2) > BSData46E <- createBeadSummaryData(BLData46E, log=FALSE,n=3, > imagesPerArray=2) > BSData46F <- createBeadSummaryData(BLData46F, log=FALSE,n=3, > imagesPerArray=2) > > BSData49A <- createBeadSummaryData(BLData49A, log=FALSE,n=3, > imagesPerArray=2) > BSData49B <- createBeadSummaryData(BLData49B, log=FALSE,n=3, > imagesPerArray=2) > BSData49C <- createBeadSummaryData(BLData49C, log=FALSE,n=3, > imagesPerArray=2) > BSData49D <- createBeadSummaryData(BLData49D, log=FALSE,n=3, > imagesPerArray=2) > BSData49E <- createBeadSummaryData(BLData49E, log=FALSE,n=3, > imagesPerArray=2) > BSData49F <- createBeadSummaryData(BLData49F, log=FALSE,n=3, > imagesPerArray=2) > > BSData50A <- createBeadSummaryData(BLData50A, log=FALSE,n=3, > imagesPerArray=2) > BSData50B <- createBeadSummaryData(BLData50B, log=FALSE,n=3, > imagesPerArray=2) > BSData50C <- createBeadSummaryData(BLData50C, log=FALSE,n=3, > imagesPerArray=2) > BSData50D <- createBeadSummaryData(BLData50D, log=FALSE,n=3, > imagesPerArray=2) > BSData50E <- createBeadSummaryData(BLData50E, log=FALSE,n=3, > imagesPerArray=2) > BSData50F <- createBeadSummaryData(BLData50F, log=FALSE,n=3, > imagesPerArray=2) > > BSData52A <- createBeadSummaryData(BLData52A, log=FALSE,n=3, > imagesPerArray=2) > BSData52B <- createBeadSummaryData(BLData52B, log=FALSE,n=3, > imagesPerArray=2) > BSData52C <- createBeadSummaryData(BLData52C, log=FALSE,n=3, > imagesPerArray=2) > BSData52D <- createBeadSummaryData(BLData52D, log=FALSE,n=3, > imagesPerArray=2) > BSData52E <- createBeadSummaryData(BLData52E, log=FALSE,n=3, > imagesPerArray=2) > BSData52F <- createBeadSummaryData(BLData52F, log=FALSE,n=3, > imagesPerArray=2) > > BSData <- combine( > BSData39A, BSData39B, BSData39C, BSData39D, BSData39E, BSData39F, > BSData46A, BSData46B, BSData46C, BSData46D, BSData46E, BSData46F, > BSData49A, BSData49B, BSData49C, BSData49D, BSData49E, BSData49F, > BSData50A, BSData50B, BSData50C, BSData50D, BSData50E, BSData50F, > BSData52A, BSData52B, BSData52C, BSData52D, BSData52E, BSData52F) > > > OUTPUT FROM SESSSION USING BSData > --------------------------------- > >> BSData > ExpressionSetIllumina (storageMode: list) > assayData: 48358 features, 30 samples > element names: exprs, se.exprs, NoBeads > phenoData > rowNames: 1863191039_A_1, 1863191039_B_1, ..., 1863191052_F_1 (30 total) > varLabels and varMetadata description: > arrayName: NA > featureData > featureNames: > fvarLabels and fvarMetadata description: none > experimentData: use 'experimentData(object)' > Annotation: illuminaProbeIDs >> slotNames(BSData) > [1] "QC" "assayData" "phenoData" > [4] "featureData" "experimentData" "annotation" > [7] ".__classVersion__" >> names(assayData(BSData)) > [1] "exprs" "se.exprs" "NoBeads" >> dim(assayData(BSData)$exprs) > [1] 48358 30 >> dim(assayData(BSData)$se.exprs) > [1] 48358 30 >> exprs(BSData)[1:10,1:2] > 1863191039_A_1 1863191039_B_1 > 10243 84.31794 90.07728 > 10280 77.86524 78.17629 > 10575 148.53714 154.93587 > 20048 74.88917 71.63645 > 20296 18520.55707 20620.06535 > 20343 60.40684 61.49921 > 20373 64.48009 63.93970 > 20431 26997.07647 29130.48258 > 50008 114.36110 267.88378 > 50014 47.48685 43.68849 >> se.exprs(BSData)[1:10,1:2] > 1863191039_A_1 1863191039_B_1 > 10243 NA NA > 10280 NA NA > 10575 NA NA > 20048 NA NA > 20296 NA NA > 20343 NA NA > 20373 NA NA > 20431 NA NA > 50008 NA NA > 50014 NA NA >> pData(BSData)[,1] > 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 > 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 > 1863191039_F_1 1863191046_A_1 1863191046_B_1 1863191046_C_1 1863191046_D_1 > 1863191039_F_1 1863191046_A_1 1863191046_B_1 1863191046_C_1 1863191046_D_1 > 1863191046_E_1 1863191046_F_1 1863191049_A_1 1863191049_B_1 1863191049_C_1 > 1863191046_E_1 1863191046_F_1 1863191049_A_1 1863191049_B_1 1863191049_C_1 > 1863191049_D_1 1863191049_E_1 1863191049_F_1 1863191050_A_1 1863191050_B_1 > 1863191049_D_1 1863191049_E_1 1863191049_F_1 1863191050_A_1 1863191050_B_1 > 1863191050_C_1 1863191050_D_1 1863191050_E_1 1863191050_F_1 1863191052_A_1 > 1863191050_C_1 1863191050_D_1 1863191050_E_1 1863191050_F_1 1863191052_A_1 > 1863191052_B_1 1863191052_C_1 1863191052_D_1 1863191052_E_1 1863191052_F_1 > 1863191052_B_1 1863191052_C_1 1863191052_D_1 1863191052_E_1 1863191052_F_1 > 30 Levels: 1863191039_A_1 1863191039_B_1 1863191039_C_1 ... 1863191052_F_1 >> pData(BSData)[,2] > NULL >> pData(BSData)[,2] > NULL >> pData(BSData)[,1] > 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 > 1863191039_F_1 1863191046_A_1 > 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 > 1863191039_F_1 1863191046_A_1 > 1863191046_B_1 1863191046_C_1 1863191046_D_1 1863191046_E_1 1863191046_F_1 > 1863191049_A_1 1863191049_B_1 > 1863191046_B_1 1863191046_C_1 1863191046_D_1 1863191046_E_1 1863191046_F_1 > 1863191049_A_1 1863191049_B_1 > 1863191049_C_1 1863191049_D_1 1863191049_E_1 1863191049_F_1 1863191050_A_1 > 1863191050_B_1 1863191050_C_1 > 1863191049_C_1 1863191049_D_1 1863191049_E_1 1863191049_F_1 1863191050_A_1 > 1863191050_B_1 1863191050_C_1 > 1863191050_D_1 1863191050_E_1 1863191050_F_1 1863191052_A_1 1863191052_B_1 > 1863191052_C_1 1863191052_D_1 > 1863191050_D_1 1863191050_E_1 1863191050_F_1 1863191052_A_1 1863191052_B_1 > 1863191052_C_1 1863191052_D_1 > 1863191052_E_1 1863191052_F_1 > 1863191052_E_1 1863191052_F_1 > 30 Levels: 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 > 1863191039_E_1 ... 1863191052_F_1 >> pData(BSData)[,1] > 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 > 1863191039_F_1 > 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 > 1863191039_F_1 > 1863191046_A_1 1863191046_B_1 1863191046_C_1 1863191046_D_1 1863191046_E_1 > 1863191046_F_1 > 1863191046_A_1 1863191046_B_1 1863191046_C_1 1863191046_D_1 1863191046_E_1 > 1863191046_F_1 > 1863191049_A_1 1863191049_B_1 1863191049_C_1 1863191049_D_1 1863191049_E_1 > 1863191049_F_1 > 1863191049_A_1 1863191049_B_1 1863191049_C_1 1863191049_D_1 1863191049_E_1 > 1863191049_F_1 > 1863191050_A_1 1863191050_B_1 1863191050_C_1 1863191050_D_1 1863191050_E_1 > 1863191050_F_1 > 1863191050_A_1 1863191050_B_1 1863191050_C_1 1863191050_D_1 1863191050_E_1 > 1863191050_F_1 > 1863191052_A_1 1863191052_B_1 1863191052_C_1 1863191052_D_1 1863191052_E_1 > 1863191052_F_1 > 1863191052_A_1 1863191052_B_1 1863191052_C_1 1863191052_D_1 1863191052_E_1 > 1863191052_F_1 > 30 Levels: 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 ... > 1863191052_F_1 >> >> > > SESSION INFO > ------------ >> sessionInfo() > R version 2.6.0 (2007-10-03) > i386-pc-mingw32 > > locale: > LC_COLLATE=English_United Kingdom.1252;LC_CTYPE=English_United > Kingdom.1252;LC_MONETARY=English_United > Kingdom.1252;LC_NUMERIC=C;LC_TIME=English_United Kingdom.1252 > > attached base packages: > [1] tools stats graphics grDevices utils datasets methods > base > > other attached packages: > [1] beadarray_1.6.0 affy_1.16.0 preprocessCore_1.0.0 > affyio_1.6.1 > [5] geneplotter_1.16.0 lattice_0.16-5 annotate_1.16.1 > xtable_1.5-2 > [9] AnnotationDbi_1.0.6 RSQLite_0.6-4 DBI_0.2-4 > Biobase_1.16.1 > [13] limma_2.12.0 > > loaded via a namespace (and not attached): > [1] grid_2.6.0 KernSmooth_2.22-21 RColorBrewer_1.0-2 >> >> >> >> pData(BSData)[1,1] > 1863191039_A_1 > 1863191039_A_1 > 30 Levels: 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 ... > 1863191052_F_1
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Hi Matt So should I revert to R 2.5.1 or is there a way to access beadarray 1.7.2? Thanks Krys -----Original Message----- From: Matt Ritchie [mailto:Matt.Ritchie@cancer.org.uk] Sent: 12 November 2007 19:01 To: Krys Kelly; bioconductor at stat.math.ethz.ch Subject: Re: [BioC] beadarray package: problem with object made by createBeadSummaryData Hi Krys, This is a bug, which has been fixed in beadarray 1.7.2. Thanks for pointing it out! Best wishes, Matt > Hello > > Using R 2.5.1, I have read in and explored the bead level data from 5 > Illumina mouse-6 slides which have 6 arrays per slide and 2 images per > array. > > I have also created and saved bead summary data trying out a few options for > the background correction. > > When I was using R 2.5.1 and the corresponding versions of bioconductor and > beadarray and everything worked fine. > > But I want to upgrade to R 2.6.0. I have installed R 2.6.0 and the > corresponding versions of bioconductor and beadarray. I now find that > se.exprs is completely filled with NAs. > > I have compared the documentation from the two versions of beadarray > expecting that there was a new option that I needed to specify, but I can't > find anything that would account for the NAs > > Please can you suggest what the problem is. > > My program code, output from the BSData object and sessionInfo() are pasted > below. > > Thanks > > Krys > > > PROGRAM CODE > ------------ > # Read the bead level data > BLData39A <- readIllumina(arrayNames=c("1863191039_A_1", "1863191039_A_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData39B <- readIllumina(arrayNames=c("1863191039_B_1", "1863191039_B_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData39C <- readIllumina(arrayNames=c("1863191039_C_1", "1863191039_C_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData39D <- readIllumina(arrayNames=c("1863191039_D_1", "1863191039_D_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData39E <- readIllumina(arrayNames=c("1863191039_E_1", "1863191039_E_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData39F <- readIllumina(arrayNames=c("1863191039_F_1", "1863191039_F_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > > BLData46A <- readIllumina(arrayNames=c("1863191046_A_1", "1863191046_A_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData46B <- readIllumina(arrayNames=c("1863191046_B_1", "1863191046_B_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData46C <- readIllumina(arrayNames=c("1863191046_C_1", "1863191046_C_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData46D <- readIllumina(arrayNames=c("1863191046_D_1", "1863191046_D_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData46E <- readIllumina(arrayNames=c("1863191046_E_1", "1863191046_E_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData46F <- readIllumina(arrayNames=c("1863191046_F_1", "1863191046_F_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > > BLData49A <- readIllumina(arrayNames=c("1863191049_A_1", "1863191049_A_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData49B <- readIllumina(arrayNames=c("1863191049_B_1", "1863191049_B_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData49C <- readIllumina(arrayNames=c("1863191049_C_1", "1863191049_C_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData49D <- readIllumina(arrayNames=c("1863191049_D_1", "1863191049_D_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData49E <- readIllumina(arrayNames=c("1863191049_E_1", "1863191049_E_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData49F <- readIllumina(arrayNames=c("1863191049_F_1", "1863191049_F_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > > BLData50A <- readIllumina(arrayNames=c("1863191050_A_1", "1863191050_A_2"), > textType=".txt", backgroundMethod="none", rmoffset=0,normalizeMethod="none", > metrics=FALSE) > BLData50B <- readIllumina(arrayNames=c("1863191050_B_1", "1863191050_B_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData50C <- readIllumina(arrayNames=c("1863191050_C_1", "1863191050_C_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData50D <- readIllumina(arrayNames=c("1863191050_D_1", "1863191050_D_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData50E <- readIllumina(arrayNames=c("1863191050_E_1", "1863191050_E_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData50F <- readIllumina(arrayNames=c("1863191050_F_1", "1863191050_F_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > > BLData52A <- readIllumina(arrayNames=c("1863191052_A_1", "1863191052_A_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData52B <- readIllumina(arrayNames=c("1863191052_B_1", "1863191052_B_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData52C <- readIllumina(arrayNames=c("1863191052_C_1", "1863191052_C_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData52D <- readIllumina(arrayNames=c("1863191052_D_1", "1863191052_D_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData52E <- readIllumina(arrayNames=c("1863191052_E_1", "1863191052_E_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > BLData52F <- readIllumina(arrayNames=c("1863191052_F_1", "1863191052_F_2"), > textType=".txt", backgroundMethod="none", offset=0,normalizeMethod="none", > metrics=FALSE) > > # Creation of summary data > BSData39A <- createBeadSummaryData(BLData39A, log=FALSE,n=3, > imagesPerArray=2) > BSData39B <- createBeadSummaryData(BLData39B, log=FALSE,n=3, > imagesPerArray=2) > BSData39C <- createBeadSummaryData(BLData39C, log=FALSE,n=3, > imagesPerArray=2) > BSData39D <- createBeadSummaryData(BLData39D, log=FALSE,n=3, > imagesPerArray=2) > BSData39E <- createBeadSummaryData(BLData39E, log=FALSE,n=3, > imagesPerArray=2) > BSData39F <- createBeadSummaryData(BLData39F, log=FALSE,n=3, > imagesPerArray=2) > > BSData46A <- createBeadSummaryData(BLData46A, log=FALSE,n=3, > imagesPerArray=2) > BSData46B <- createBeadSummaryData(BLData46B, log=FALSE,n=3, > imagesPerArray=2) > BSData46C <- createBeadSummaryData(BLData46C, log=FALSE,n=3, > imagesPerArray=2) > BSData46D <- createBeadSummaryData(BLData46D, log=FALSE,n=3, > imagesPerArray=2) > BSData46E <- createBeadSummaryData(BLData46E, log=FALSE,n=3, > imagesPerArray=2) > BSData46F <- createBeadSummaryData(BLData46F, log=FALSE,n=3, > imagesPerArray=2) > > BSData49A <- createBeadSummaryData(BLData49A, log=FALSE,n=3, > imagesPerArray=2) > BSData49B <- createBeadSummaryData(BLData49B, log=FALSE,n=3, > imagesPerArray=2) > BSData49C <- createBeadSummaryData(BLData49C, log=FALSE,n=3, > imagesPerArray=2) > BSData49D <- createBeadSummaryData(BLData49D, log=FALSE,n=3, > imagesPerArray=2) > BSData49E <- createBeadSummaryData(BLData49E, log=FALSE,n=3, > imagesPerArray=2) > BSData49F <- createBeadSummaryData(BLData49F, log=FALSE,n=3, > imagesPerArray=2) > > BSData50A <- createBeadSummaryData(BLData50A, log=FALSE,n=3, > imagesPerArray=2) > BSData50B <- createBeadSummaryData(BLData50B, log=FALSE,n=3, > imagesPerArray=2) > BSData50C <- createBeadSummaryData(BLData50C, log=FALSE,n=3, > imagesPerArray=2) > BSData50D <- createBeadSummaryData(BLData50D, log=FALSE,n=3, > imagesPerArray=2) > BSData50E <- createBeadSummaryData(BLData50E, log=FALSE,n=3, > imagesPerArray=2) > BSData50F <- createBeadSummaryData(BLData50F, log=FALSE,n=3, > imagesPerArray=2) > > BSData52A <- createBeadSummaryData(BLData52A, log=FALSE,n=3, > imagesPerArray=2) > BSData52B <- createBeadSummaryData(BLData52B, log=FALSE,n=3, > imagesPerArray=2) > BSData52C <- createBeadSummaryData(BLData52C, log=FALSE,n=3, > imagesPerArray=2) > BSData52D <- createBeadSummaryData(BLData52D, log=FALSE,n=3, > imagesPerArray=2) > BSData52E <- createBeadSummaryData(BLData52E, log=FALSE,n=3, > imagesPerArray=2) > BSData52F <- createBeadSummaryData(BLData52F, log=FALSE,n=3, > imagesPerArray=2) > > BSData <- combine( > BSData39A, BSData39B, BSData39C, BSData39D, BSData39E, BSData39F, > BSData46A, BSData46B, BSData46C, BSData46D, BSData46E, BSData46F, > BSData49A, BSData49B, BSData49C, BSData49D, BSData49E, BSData49F, > BSData50A, BSData50B, BSData50C, BSData50D, BSData50E, BSData50F, > BSData52A, BSData52B, BSData52C, BSData52D, BSData52E, BSData52F) > > > OUTPUT FROM SESSSION USING BSData > --------------------------------- > >> BSData > ExpressionSetIllumina (storageMode: list) > assayData: 48358 features, 30 samples > element names: exprs, se.exprs, NoBeads > phenoData > rowNames: 1863191039_A_1, 1863191039_B_1, ..., 1863191052_F_1 (30 total) > varLabels and varMetadata description: > arrayName: NA > featureData > featureNames: > fvarLabels and fvarMetadata description: none > experimentData: use 'experimentData(object)' > Annotation: illuminaProbeIDs >> slotNames(BSData) > [1] "QC" "assayData" "phenoData" > [4] "featureData" "experimentData" "annotation" > [7] ".__classVersion__" >> names(assayData(BSData)) > [1] "exprs" "se.exprs" "NoBeads" >> dim(assayData(BSData)$exprs) > [1] 48358 30 >> dim(assayData(BSData)$se.exprs) > [1] 48358 30 >> exprs(BSData)[1:10,1:2] > 1863191039_A_1 1863191039_B_1 > 10243 84.31794 90.07728 > 10280 77.86524 78.17629 > 10575 148.53714 154.93587 > 20048 74.88917 71.63645 > 20296 18520.55707 20620.06535 > 20343 60.40684 61.49921 > 20373 64.48009 63.93970 > 20431 26997.07647 29130.48258 > 50008 114.36110 267.88378 > 50014 47.48685 43.68849 >> se.exprs(BSData)[1:10,1:2] > 1863191039_A_1 1863191039_B_1 > 10243 NA NA > 10280 NA NA > 10575 NA NA > 20048 NA NA > 20296 NA NA > 20343 NA NA > 20373 NA NA > 20431 NA NA > 50008 NA NA > 50014 NA NA >> pData(BSData)[,1] > 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 > 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 > 1863191039_F_1 1863191046_A_1 1863191046_B_1 1863191046_C_1 1863191046_D_1 > 1863191039_F_1 1863191046_A_1 1863191046_B_1 1863191046_C_1 1863191046_D_1 > 1863191046_E_1 1863191046_F_1 1863191049_A_1 1863191049_B_1 1863191049_C_1 > 1863191046_E_1 1863191046_F_1 1863191049_A_1 1863191049_B_1 1863191049_C_1 > 1863191049_D_1 1863191049_E_1 1863191049_F_1 1863191050_A_1 1863191050_B_1 > 1863191049_D_1 1863191049_E_1 1863191049_F_1 1863191050_A_1 1863191050_B_1 > 1863191050_C_1 1863191050_D_1 1863191050_E_1 1863191050_F_1 1863191052_A_1 > 1863191050_C_1 1863191050_D_1 1863191050_E_1 1863191050_F_1 1863191052_A_1 > 1863191052_B_1 1863191052_C_1 1863191052_D_1 1863191052_E_1 1863191052_F_1 > 1863191052_B_1 1863191052_C_1 1863191052_D_1 1863191052_E_1 1863191052_F_1 > 30 Levels: 1863191039_A_1 1863191039_B_1 1863191039_C_1 ... 1863191052_F_1 >> pData(BSData)[,2] > NULL >> pData(BSData)[,2] > NULL >> pData(BSData)[,1] > 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 > 1863191039_F_1 1863191046_A_1 > 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 > 1863191039_F_1 1863191046_A_1 > 1863191046_B_1 1863191046_C_1 1863191046_D_1 1863191046_E_1 1863191046_F_1 > 1863191049_A_1 1863191049_B_1 > 1863191046_B_1 1863191046_C_1 1863191046_D_1 1863191046_E_1 1863191046_F_1 > 1863191049_A_1 1863191049_B_1 > 1863191049_C_1 1863191049_D_1 1863191049_E_1 1863191049_F_1 1863191050_A_1 > 1863191050_B_1 1863191050_C_1 > 1863191049_C_1 1863191049_D_1 1863191049_E_1 1863191049_F_1 1863191050_A_1 > 1863191050_B_1 1863191050_C_1 > 1863191050_D_1 1863191050_E_1 1863191050_F_1 1863191052_A_1 1863191052_B_1 > 1863191052_C_1 1863191052_D_1 > 1863191050_D_1 1863191050_E_1 1863191050_F_1 1863191052_A_1 1863191052_B_1 > 1863191052_C_1 1863191052_D_1 > 1863191052_E_1 1863191052_F_1 > 1863191052_E_1 1863191052_F_1 > 30 Levels: 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 > 1863191039_E_1 ... 1863191052_F_1 >> pData(BSData)[,1] > 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 > 1863191039_F_1 > 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 1863191039_E_1 > 1863191039_F_1 > 1863191046_A_1 1863191046_B_1 1863191046_C_1 1863191046_D_1 1863191046_E_1 > 1863191046_F_1 > 1863191046_A_1 1863191046_B_1 1863191046_C_1 1863191046_D_1 1863191046_E_1 > 1863191046_F_1 > 1863191049_A_1 1863191049_B_1 1863191049_C_1 1863191049_D_1 1863191049_E_1 > 1863191049_F_1 > 1863191049_A_1 1863191049_B_1 1863191049_C_1 1863191049_D_1 1863191049_E_1 > 1863191049_F_1 > 1863191050_A_1 1863191050_B_1 1863191050_C_1 1863191050_D_1 1863191050_E_1 > 1863191050_F_1 > 1863191050_A_1 1863191050_B_1 1863191050_C_1 1863191050_D_1 1863191050_E_1 > 1863191050_F_1 > 1863191052_A_1 1863191052_B_1 1863191052_C_1 1863191052_D_1 1863191052_E_1 > 1863191052_F_1 > 1863191052_A_1 1863191052_B_1 1863191052_C_1 1863191052_D_1 1863191052_E_1 > 1863191052_F_1 > 30 Levels: 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 ... > 1863191052_F_1 >> >> > > SESSION INFO > ------------ >> sessionInfo() > R version 2.6.0 (2007-10-03) > i386-pc-mingw32 > > locale: > LC_COLLATE=English_United Kingdom.1252;LC_CTYPE=English_United > Kingdom.1252;LC_MONETARY=English_United > Kingdom.1252;LC_NUMERIC=C;LC_TIME=English_United Kingdom.1252 > > attached base packages: > [1] tools stats graphics grDevices utils datasets methods > base > > other attached packages: > [1] beadarray_1.6.0 affy_1.16.0 preprocessCore_1.0.0 > affyio_1.6.1 > [5] geneplotter_1.16.0 lattice_0.16-5 annotate_1.16.1 > xtable_1.5-2 > [9] AnnotationDbi_1.0.6 RSQLite_0.6-4 DBI_0.2-4 > Biobase_1.16.1 > [13] limma_2.12.0 > > loaded via a namespace (and not attached): > [1] grid_2.6.0 KernSmooth_2.22-21 RColorBrewer_1.0-2 >> >> >> >> pData(BSData)[1,1] > 1863191039_A_1 > 1863191039_A_1 > 30 Levels: 1863191039_A_1 1863191039_B_1 1863191039_C_1 1863191039_D_1 ... > 1863191052_F_1
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Hi Krys, You can checkout beadarray 1.7.2 from the BioC developmental svn repository (see http://wiki.fhcrc.org/bioc/SvnHowTo for instructions) and install it from source, or use the older version for R 2.5.1 - up to you! Best wishes, Matt > Hi Matt > > So should I revert to R 2.5.1 or is there a way to access beadarray 1.7.2? > > Thanks > > Krys > > > -----Original Message----- > From: Matt Ritchie [mailto:Matt.Ritchie at cancer.org.uk] > Sent: 12 November 2007 19:01 > To: Krys Kelly; bioconductor at stat.math.ethz.ch > Subject: Re: [BioC] beadarray package: problem with object made by > createBeadSummaryData > > Hi Krys, > > This is a bug, which has been fixed in beadarray 1.7.2. Thanks for pointing > it out! Best wishes, > > Matt > >> Hello >> >> Using R 2.5.1, I have read in and explored the bead level data from 5 >> Illumina mouse-6 slides which have 6 arrays per slide and 2 images per >> array. >> >> I have also created and saved bead summary data trying out a few options > for >> the background correction. >> >> When I was using R 2.5.1 and the corresponding versions of bioconductor > and >> beadarray and everything worked fine. >> >> But I want to upgrade to R 2.6.0. I have installed R 2.6.0 and the >> corresponding versions of bioconductor and beadarray. I now find that >> se.exprs is completely filled with NAs. >> >> I have compared the documentation from the two versions of beadarray >> expecting that there was a new option that I needed to specify, but I > can't >> find anything that would account for the NAs >> >> Please can you suggest what the problem is. >> >> My program code, output from the BSData object and sessionInfo() are > pasted >> below. >> >> Thanks >> >> Krys
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