[BioC] beadarray package: problem with object made by createBeadSummaryData
Krys Kelly
kak28 at cam.ac.uk
Mon Nov 12 16:56:02 CET 2007
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
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