[BioC] gcrma - u133aaofav2probe error

[Henrik Bengtsson]

Hi.

On Mon, Mar 14, 2011 at 10:54 AM, James W. MacDonald
<jmacdon at med.umich.edu> wrote:
> Hi Myrto,
>
> On 3/14/2011 7:58 AM, Myrto Kostadima wrote:
>>
>> Hi,
>> I am currently trying to analyse microarray data from this publicly
>> available dataset:
>> GSE24759<http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24759>
>> Platform: [U133AAofAv2] Affymetrix GeneChip HT-HG_U133A Early Access Array
>>
>> When using gcrma on the data:
>>>
>>> marray.eset.gcrma<- gcrma(marray.data)
>>
>> I get the following error:
>>
>> [1] "Environment u133aaofav2probe was not found in the Bioconductor
>> repository."
>> Error in get(probepackagename) : object 'u133aaofav2probe' not found
>>
>> The only package that is available on Bioconducttor is: u133aaofav2cdf
>>
>> I have not been able to find a solution online. Anybody who could help
>> with
>> that?
>
> Unfortunately we have never been able to get hold of the probe file for this
> array, so have not been able to make the probe package. If anybody out there
> happens to have the probe file, I would appreciate an off-line response.

>From http://aroma-project.org/chipTypes/HT_HG-U133A_and_HT_HG-U133B

"Early access versions of the HT_HT-U133A chip type were labelled
U133AAofAv2(*) and HT_HT-U133A_EA.

Footnote: (*) The evidence for this comes from comparing spatial
images of a CEL file with U133AAofAv2 [link to PNG] in the header with
one with HT_HT-U133A [link to PNG].  Both have the same spatial
patterns, i.e. blocks of checkered blocks and control probes, "landing
lights", and positive controls spelling out 'Genechip' and 'HG-U133
AofAv2'."


For advanced users only: The convertCel() function of affxparser
allows you to *relabel* the chip type *label* that exists in the CEL
file header, e.g. convertCel("old.CEL", "new.CEL",
newChipType="HT_HT-U133A").  Warning: Only do this if you know what
you're doing.  Read help("convertCel", package="affxparser") in the
devel-version affxparser 1.23.3 contains more info.  Again, do not use
this if you are not fully understanding what you are doing.  If
misused, you're analysis will be completely garbage.  If I wasn't
clear enough, read this paragraph again.  If you still don't
understand it, pretend that you never heard about this new feature of
convertCel(), i.e. wipe it out of your memory.  I hope I made my
point.

/Henrik

>
>
> Best,
>
> Jim
>
>
>>
>> Thanks,
>> Myrto
>>
>
> --
> James W. MacDonald, M.S.
> Biostatistician
> Douglas Lab
> University of Michigan
> Department of Human Genetics
> 5912 Buhl
> 1241 E. Catherine St.
> Ann Arbor MI 48109-5618
> 734-615-7826
> **********************************************************
> Electronic Mail is not secure, may not be read every day, and should not be
> used for urgent or sensitive issues
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at r-project.org
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives:
> http://news.gmane.org/gmane.science.biology.informatics.conductor
>