[BioC] Problem with Beadarray package for beadchipHT-12

[Mark Dunning]

Hi Leon,

What error message are you getting? The HumanHT-12 data should be in
the exact same format as for earlier arrays. However, the bead-level
intensities are probably found in the .txt files in your directory,
unlike the example script where the bead-level intensities were in
.csv files.

Try the following.


BLData <- readIllumina(backgroundMethod = "none", targets = targets,
arrayNames = targets$ArrayName, metrics = TRUE, annoPkg="Humanv3")

Best,

Mark



On Fri, Jul 3, 2009 at 1:08 PM, Perry Moerland<p.d.moerland at amc.uva.nl> wrote:
> Hi Leon,
> Could you tell us where your code stops working, include the error message,
> and also include a sessionInfo(), otherwise it will be hard to give you any
> input.
> best
> Perry
>
> Leo Nitsche wrote:
>>
>> Hi all,
>>
>>
>> I have already obtained a data set from Illumina Beadchip-HT12 experience
>> and I would like to analyse them in R with Beadarray package. I have files
>> with the following extensions (.txt, .csv, .idat, .xml, .locs, .tiff) with
>> a
>> text file called Metrics. I guess that only two files are required (.txt
>> and
>> .tiff), right ?
>> Now, I try to use the following script, wrote by Mark Dunning (thanks for
>> him!) but I don't get what I should to get! Surely because the formats are
>> not the same between the new HumanV3 beadchip I use and the previous one
>> (HumanV2 for which the script was written) !
>> Here is the program and I will be grateful if somebody could tell me where
>> in the script and what I have to change to adapt it my HumanHT12 beadchip?
>>
>> targets = read.table("targets.txt", sep = "\t", header = TRUE,
>> as.is = TRUE)
>> dir()
>> targets = read.table("targets.txt", sep = "\t", header = TRUE,
>> as.is = TRUE)
>> Metrics = read.table("targets.txt", sep = "\t", header = TRUE,
>> as.is=TRUE)
>> Metrics = read.table("Metrics.txt", sep = "\t", header = TRUE,
>> as.is=TRUE)
>> Metrics
>> BLData <- readIllumina(textType = ".csv", backgroundMethod = "none",
>> targets = targets, arrayNames = targets$ArrayName, metrics = TRUE)
>>  BLData <- readIllumina(textType = ".csv", backgroundMethod = "none",
>> Matrics = Matrics, arrayNames = Metrics$ArrayName, metrics = TRUE)
>> is(BLData)
>> class(BLData)
>> slotNames(BLData)
>> an = arrayNames(BLData)
>> an
>> names(BLData at beadData[[an[1]]])
>> BLData[[an[1]]]$G[1:10]
>> BLData[[an[2]]]$Gb[1:10]
>> pData(BLData)
>> getArrayData(BLData, array = 1, what = "G", log = FALSE)[1:10]
>> getArrayData(BLData, array = 2, what = "Gb", log = FALSE)[1:10]
>> par(mfrow = c(1, 3))
>> boxplotBeads(BLData, las = 2, outline = FALSE, ylim = c(4, 12),
>> main = "Foreground")
>> boxplotBeads(BLData, las = 2, whatToPlot = "Gb", outline = FALSE,
>> ylim = c(4, 12), main = "Background")
>> BLData.bc = backgroundCorrect(BLData, method = "subtract")
>> boxplotBeads(BLData.bc, las = 2, outline = FALSE, ylim = c(4,
>> 12), main = "Background Corrected")
>> ids = unique(BLData[[an[1]]]$ProbeID)[1:10]
>> ids
>> ProbeCols = rainbow(10)
>> plotBeadIntensities(BLData, arrays = c(1, 3), ProbeIDs = ids,
>> ProbeCols = ProbeCols, log = TRUE, ylim = c(8, 15))
>> ProbeCols = rainbow(10)
>>>
>>> plotBeadIntensities(BLData, arrays = c(1, 3), ProbeIDs = ids,
>>
>> + ProbeCols = ProbeCols, log = TRUE, ylim = c(8, 15))ProbeCols =
>> rainbow(10)
>> plotBeadIntensities(BLData, arrays = c(1, 3), ProbeIDs = ids,
>> ProbeCols = ProbeCols, log = TRUE, ylim = c(8, 15))
>> o = findAllOutliers(BLData, array = 1)
>> o[1:10]
>> length(o)/numBeads(BLData)[1]
>> par(mfrow = c(2, 1))
>> par(mar = c(1, 1, 3, 1))
>> for (i in 1:2) {
>> o = findAllOutliers(BLData, array = i)
>> plotBeadLocations(BLData, BeadIDs = o[1:1000], array = i,
>> SAM = FALSE, cex = 0.5, col = "red", pch = 16)
>> }
>> par(mfrow = c(2, 1))
>> for (i in 1:2) {
>> imageplot(BLData, array = i, nrow = 20, ncol = 200, zlim = range(9,
>> 10), low = "yellow", high = "red", what = "G")
>> }
>>
>>
>> Thank you very much
>>
>> Leon
>>
>>        [[alternative HTML version deleted]]
>>
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>
>
> --
> Perry Moerland, PhD
> Room J1B-206, Bioinformatics Laboratory
> Department of Clinical Epidemiology, Biostatistics and Bioinformatics
> Academic Medical Centre, University of Amsterdam
> Postbus 22660, 1100 DD Amsterdam, The Netherlands
> tel: +31 20 5664660
> p.d.moerland at amc.uva.nl, http://www.amc.uva.nl/
>
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