[BioC] Parsing Illumina Golden Gate idat files

Matthew Ritchie mritchie at wehi.EDU.AU
Fri Oct 22 05:08:16 CEST 2010


Dear Mike,

It is my understanding that idats from Illumina's GoldenGate arrays and
expression BeadChips are encrypted.  The code to read in idat files in
crlmm does not deal with encrypted data.

To use beadarraySNP, you will need BeadStudio/GenomeStudio output from
your experiment (typically one file which contains the intensities and
genotype calls from all the samples you are interested in).

Best wishes,

Matt

> Dear List,
>
> I have a series of golden gate cancer panel SNP data and wanted to use the
> beadarraySNP package to analyse the data. Unfortunately, I only have the
> idat files and not the csv files. Thus I tried 'crlmm' package to parse
> the idats for the red and green channel to create the csv tables. I get
> some error message which is most likely related to the format of the
> files.
>
> library(ff)
> library(crlmm)
>
> f.GG = list.files()
>
> x = crlmm:::readIDAT(f.GG)
> Error in matrix(0, nFields, 3) : too many elements specified
>
>
> x = crlmm:::readIdatFiles(path=getwd()) #I know that this is for Infinium
> data, I tried anyway
> reading 4075501002_R001_C001    _Grn.idat      Error in matrix(0, nFields,
> 3) : too many elements specified
>
> Does someone has an idea how to read in the files? Any hint is welcome.
>
> Thanks and kind regards,
>
> Mike
>
>
>> sessionInfo()
> R version 2.11.1 (2010-05-31)
> i386-pc-mingw32
>
> locale:
> [1] LC_COLLATE=German_Germany.1252  LC_CTYPE=German_Germany.1252
> [3] LC_MONETARY=German_Germany.1252 LC_NUMERIC=C
> [5] LC_TIME=German_Germany.1252
>
> attached base packages:
> [1] tools     stats     graphics  grDevices utils     datasets  methods
> [8] base
>
> other attached packages:
> [1] crlmm_1.6.5         oligoClasses_1.10.0 Biobase_2.8.0
> [4] ff_2.1-2            bit_1.1-4
>
> loaded via a namespace (and not attached):
>  [1] affyio_1.16.0         annotate_1.26.1       AnnotationDbi_1.10.2
>  [4] Biostrings_2.16.9     DBI_0.2-5             ellipse_0.3-5
>  [7] genefilter_1.30.0     IRanges_1.6.16        mvtnorm_0.9-92
> [10] preprocessCore_1.10.0 RSQLite_0.9-2         splines_2.11.1
> [13] survival_2.35-8       xtable_1.5-6


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