Tine,

No plans for a BrainArray preprocessed barcode at the moment. If it is
something you're very interested in, I'd be happy to chat about options.

Best,
Matt



On Mon, Jul 28, 2014 at 10:30 AM, Tine Casneuf <tineke.casneuf@gmail.com>
wrote:

> Hi Matt,
>
> As I had expected :)
>
> Assuming this is not something I as a user can do, do you have plans to
> develop the barcode for the brainarray CDF parsed data? -I assume this
> would be quite an effort as it would require rerunning for every other
> Brainarray version? -
>
> thank you!
> tine
>
>
>
> On Mon, Jul 28, 2014 at 4:20 PM, Matthew McCall <mccallm@gmail.com> wrote:
>
>> The barcode function uses precomputed distributions that are based on
>> data preprocessed with the Affy CDF. Comparing values from data
>> preprocessed with an alternative CDF to these distributions doesn't make
>> any sense -- the probesets are fundamentally different.
>>
>> Matt
>>
>>
>> On Mon, Jul 28, 2014 at 10:14 AM, Tine Casneuf <tineke.casneuf@gmail.com>
>> wrote:
>>
>>> Hi Matt,
>>>
>>> that is correct, it indeed only works with the alternative CDF eset
>>> object if , platform = "GPL570" is added.
>>>
>>> Do you know why the number of genes expressed differs to such a great
>>> extent:
>>>
>>> 30.000 genes with Affy CDF  versus 110 with the alternative (after
>>> adding , platform = "GPL570")  ?
>>>
>>> thanks,
>>>
>>> tine
>>>
>>>
>>>
>>>
>>> On Mon, Jul 28, 2014 at 4:09 PM, Matthew McCall <mccallm@gmail.com>
>>> wrote:
>>>
>>>> Happy to help. The Gene Expression Barcode (barcode function in the
>>>> frma package) is only implemented for the Affy CDF. It should produce an
>>>> error when you try to barcode the output from frma using an alternative
>>>> CDF, but I believe you overrode the error by supplying the argument --
>>>> platform = "GPL570".
>>>>
>>>> Best,
>>>> Matt
>>>>
>>>>
>>>>
>>>> On Mon, Jul 28, 2014 at 9:58 AM, Tine Casneuf <tineke.casneuf@gmail.com
>>>> > wrote:
>>>>
>>>>> Hi Matt,
>>>>>
>>>>> thanks in advance. Not a problem, it works with the previous version.
>>>>>
>>>>> Can i bother you with another question? With an example dataset, I
>>>>> tried to estimate which genes are expressed, but found an substantial
>>>>> difference between using the Affy CDF versus the alternative one:
>>>>>
>>>>> library(frma)
>>>>>
>>>>> library(affy)
>>>>>
>>>>> library(GEOquery)
>>>>>
>>>>> getGEOSuppFiles("GSE20986")
>>>>>
>>>>> dir("GSE20986/")
>>>>>
>>>>> untar("GSE20986/GSE20986_RAW.tar", exdir="data")
>>>>>
>>>>> cels <- list.files("data/", pattern = "[gz]")
>>>>>
>>>>> sapply(paste("data", cels, sep="/"), gunzip)
>>>>>
>>>>> myCELs <- paste("data/", dir("data/", pattern = ".CEL$"), sep = "")
>>>>>
>>>>>
>>>>> ## affy CDF
>>>>>
>>>>> batch <- ReadAffy(filenames = myCELs)
>>>>>
>>>>> eset <- frma(batch, summarize = "random_effect")
>>>>>
>>>>> apc <- barcode(eset, cutoff = (-log10(0.05)), output = "binary")
>>>>>
>>>>> selPbs <- sum(rowSums(apc) > 1)
>>>>>
>>>>> selPbs
>>>>>
>>>>>
>>>>> ## alternative CDF
>>>>>
>>>>> batchBA <- ReadAffy(filenames = myCELs, cdfname =
>>>>> "hgu133plus2hsentrezg")
>>>>>
>>>>> esetBA <- frma(batchBA, summarize = "random_effect")
>>>>>
>>>>> apcBA <- barcode(esetBA, cutoff = (-log10(0.05)), output = "binary",
>>>>> platform = "GPL570")
>>>>>
>>>>> selPbsBA <- sum(rowSums(apcBA) > 1)
>>>>>
>>>>> selPbsBA
>>>>>
>>>>> > selPbs  ## the Affy CDF
>>>>>
>>>>> [1] 30117
>>>>> > selPbsBA  ## the brain array CDF
>>>>>
>>>>> [1] 117
>>>>>
>>>>> Would you happen to know why with the Affy CDF the number of expressed
>>>>> genes is ~30.000 and with the alternative only ~100 genes, 300 times lower?
>>>>>
>>>>> Thanks a lot,
>>>>> Best,
>>>>>
>>>>> Tine
>>>>>
>>>>>
>>>>> As before, > sessionInfo()
>>>>>
>>>>> R version 3.0.3 (2014-03-06)
>>>>>
>>>>> Platform: x86_64-apple-darwin10.8.0 (64-bit)
>>>>>
>>>>>
>>>>> locale:
>>>>>
>>>>> [1] C
>>>>>
>>>>>
>>>>> attached base packages:
>>>>>
>>>>> [1] parallel  stats     graphics  grDevices utils     datasets
>>>>> methods
>>>>>
>>>>> [8] base
>>>>>
>>>>>
>>>>> other attached packages:
>>>>>
>>>>>  [1] hgu133plus2hsentrezgcdf_16.0.0 hgu133plus2frmavecs_1.3.0
>>>>>
>>>>>  [3] hgu133plus2cdf_2.12.0          AnnotationDbi_1.22.6
>>>>>
>>>>>  [5] frma_1.12.0                    affy_1.38.1
>>>>>
>>>>>  [7] GEOquery_2.26.2                Biobase_2.20.1
>>>>>
>>>>>  [9] BiocGenerics_0.6.0             plyr_1.8.1
>>>>>
>>>>> [11] rj_1.1.3-1
>>>>>
>>>>>
>>>>> loaded via a namespace (and not attached):
>>>>>
>>>>>  [1] BiocInstaller_1.12.1  Biostrings_2.28.0     DBI_0.2-7
>>>>>
>>>>>  [4] GenomicRanges_1.12.5  IRanges_1.18.4        MASS_7.3-33
>>>>>
>>>>>  [7] RCurl_1.95-4.1        RSQLite_0.11.4        Rcpp_0.11.2
>>>>>
>>>>> [10] XML_3.95-0.2          affxparser_1.32.3     affyio_1.28.0
>>>>>
>>>>> [13] bit_1.1-12            codetools_0.2-8       ff_2.2-13
>>>>>
>>>>> [16] foreach_1.4.2         iterators_1.0.7       oligo_1.24.2
>>>>>
>>>>> [19] oligoClasses_1.22.0   preprocessCore_1.22.0 rj.gd_1.1.3-1
>>>>>
>>>>> [22] splines_3.0.3         stats4_3.0.3          tools_3.0.3
>>>>>
>>>>> [25] zlibbioc_1.6.0
>>>>>
>>>>>
>>>>>
>>>>> On Mon, Jul 28, 2014 at 1:44 PM, Matthew McCall <mccallm@gmail.com>
>>>>> wrote:
>>>>>
>>>>>> Yes, the intention is to be one version behind the latest Brainarray
>>>>>> version. So hgu133plus2frmavecs_1.3.0 should really go with
>>>>>> hgu133plus2hsentrezgcdf_17.0.0, but this year has been very hectic, so I
>>>>>> missed an update.
>>>>>>
>>>>>> Best,
>>>>>> Matt
>>>>>>
>>>>>>
>>>>>> On Mon, Jul 28, 2014 at 3:55 AM, Tine Casneuf <
>>>>>> tineke.casneuf@gmail.com> wrote:
>>>>>>
>>>>>>> Hi Matt,
>>>>>>>
>>>>>>> thanks a lot, this works indeed (hgu133plus2frmavecs_1.3.0 with
>>>>>>> hgu133plus2hsentrezgcdf_16.0.0). Is your intention to keep updating
>>>>>>> these to be able to work with the more recent versions of Brainarray?
>>>>>>>
>>>>>>> thanks again,
>>>>>>>
>>>>>>> tine
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> On Sun, Jul 27, 2014 at 11:26 PM, Matthew McCall <mccallm@gmail.com>
>>>>>>> wrote:
>>>>>>>
>>>>>>>> Tine,
>>>>>>>>
>>>>>>>> I'm a bit behind on updating the frmavecs alternative CDFs. Try
>>>>>>>> using:
>>>>>>>> hgu133plus2frmavecs_1.3.0 with hgu133plus2hsentrezgcdf_16.0.0
>>>>>>>>
>>>>>>>> A couple other things to try:
>>>>>>>> -- update to the latest version of preprocessCore (that's where
>>>>>>>> rcModelWPLM comes from).
>>>>>>>> -- not sure if this matters, but I always pass the cdfname to
>>>>>>>> ReadAffy() instead of changing it afterwards
>>>>>>>>
>>>>>>>> Best,
>>>>>>>> Matt
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> On Sun, Jul 27, 2014 at 3:37 PM, Tine Casneuf [guest] <
>>>>>>>> guest@bioconductor.org> wrote:
>>>>>>>>
>>>>>>>>> Hi all,
>>>>>>>>>
>>>>>>>>> I am trying to apply frma with an alternative Brainarray CDF to a
>>>>>>>>> microarray dataset. I cannot get this to work and found a relevant post on
>>>>>>>>> the bioC mailing list:
>>>>>>>>> http://article.gmane.org/gmane.science.biology.informatics.conductor/47887/match=frma+alternative+cdf
>>>>>>>>>
>>>>>>>>> I get the same error as mentioned on the post:
>>>>>>>>>
>>>>>>>>> > test <- ReadAffy()
>>>>>>>>> > test@cdfName <- "hgu133plus2hsentrezgcdf"
>>>>>>>>> > library(frma)
>>>>>>>>> >  test2 <- frma(test)
>>>>>>>>> Error in rcModelWPLM(y = x1, w = w.tmp, row.effects = pe.tmp,
>>>>>>>>> input.scale = x4) :
>>>>>>>>>   row.effects should sum to zero
>>>>>>>>> >  test2 <- frma(test, summarize = "random_effect")
>>>>>>>>> Error in if (convi < 1e-04) break : missing value where TRUE/FALSE
>>>>>>>>> needed
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> I get the same error with the most recent version of the brain
>>>>>>>>> array CDF (18.0.0). The suggested solution on the page mentioned above
>>>>>>>>> (brain array version 15 and hgu133afrmavecs version 1.2.0) dord not solve
>>>>>>>>> the problem for me.
>>>>>>>>>
>>>>>>>>> Does anyone know which versions of the brainarray CDFs, and
>>>>>>>>> hgu133afrmavecs go together?
>>>>>>>>>
>>>>>>>>> thanks a lot,
>>>>>>>>>
>>>>>>>>> Tine
>>>>>>>>>
>>>>>>>>>  -- output of sessionInfo():
>>>>>>>>>
>>>>>>>>> > sessionInfo()
>>>>>>>>> R version 3.0.3 (2014-03-06)
>>>>>>>>> Platform: x86_64-apple-darwin10.8.0 (64-bit)
>>>>>>>>>
>>>>>>>>> locale:
>>>>>>>>> [1] C/UTF-8/C/C/C/C
>>>>>>>>>
>>>>>>>>> attached base packages:
>>>>>>>>> [1] parallel  stats     graphics  grDevices utils     datasets
>>>>>>>>>  methods
>>>>>>>>> [8] base
>>>>>>>>>
>>>>>>>>> other attached packages:
>>>>>>>>> [1] hgu133plus2frmavecs_1.2.0      frma_1.12.0
>>>>>>>>> [3] hgu133plus2hsentrezgcdf_15.0.0 AnnotationDbi_1.22.6
>>>>>>>>> [5] affy_1.38.1                    Biobase_2.20.1
>>>>>>>>> [7] BiocGenerics_0.6.0
>>>>>>>>>
>>>>>>>>> loaded via a namespace (and not attached):
>>>>>>>>>  [1] BiocInstaller_1.12.1  Biostrings_2.28.0     DBI_0.2-7
>>>>>>>>>  [4] GenomicRanges_1.12.5  IRanges_1.18.4        MASS_7.3-33
>>>>>>>>>  [7] RSQLite_0.11.4        affxparser_1.32.3     affyio_1.28.0
>>>>>>>>> [10] bit_1.1-12            codetools_0.2-8       ff_2.2-13
>>>>>>>>> [13] foreach_1.4.2         iterators_1.0.7       oligo_1.24.2
>>>>>>>>> [16] oligoClasses_1.22.0   preprocessCore_1.22.0 splines_3.0.3
>>>>>>>>> [19] stats4_3.0.3          tools_3.0.3           zlibbioc_1.6.0
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> --
>>>>>>>>> Sent via the guest posting facility at bioconductor.org.
>>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> --
>>>>>>>> Matthew N McCall, PhD
>>>>>>>> 112 Arvine Heights
>>>>>>>> Rochester, NY 14611
>>>>>>>> Cell: 202-222-5880
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>>>
>>>>>> --
>>>>>> Matthew N McCall, PhD
>>>>>> 112 Arvine Heights
>>>>>> Rochester, NY 14611
>>>>>> Cell: 202-222-5880
>>>>>>
>>>>>>
>>>>>
>>>>
>>>>
>>>> --
>>>> Matthew N McCall, PhD
>>>> 112 Arvine Heights
>>>> Rochester, NY 14611
>>>> Cell: 202-222-5880
>>>>
>>>>
>>>
>>
>>
>> --
>> Matthew N McCall, PhD
>> 112 Arvine Heights
>> Rochester, NY 14611
>> Cell: 202-222-5880
>>
>>
>


-- 
Matthew N McCall, PhD
112 Arvine Heights
Rochester, NY 14611
Cell: 202-222-5880

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