Thanks a lot! (It has finally landed!) I plan to coerce my methyLumiM
object to RGChannel, normalise together with the sorted cell data and use
getBloodCellCounts.

Cheers

Marco


2014-02-22 19:33 GMT+01:00 Tim Triche, Jr. <tim.triche@gmail.com>:

> Yeah it's the devel version you want. I'll see about back porting
> everything to 2.13 but I can't promise it will be super fast... You might
> be better off installing the devel package from the BioC site (am I going
> to get stoned to death for saying this?).
>
> Please note that you're still going to be hosed if you try to use
> preprocessQuantile or estimateCellCounts on the coerced object. That's not
> something I can fix; it's intrinsic to how minfi does these steps. You may
> have to choose which steps are most important to you, since I don't think
> lumi was ever modified to retain opposite-channel intensities of infinium I
> probes
>
> Ymmv,
>
> --t
>
> On Feb 22, 2014, at 10:11 AM, Marco Boks <marcoboks@gmail.com> wrote:
>
> Dear All,
>
> Pardon my ignorance, but I am getting slightly desperate to coerce my
> methyLumi object to RGChannelSet.
>
> I tried all combinations of
> require(devtools)
> datrcg<-as(sampsM,'RGChannelSet')
>
> Error in methylumiToMinfi(from) :
>   Cannot construct an RGChannelSet without full (OOB) intensities
>
> Any pointer would be very much appreciated. (I wonder if my inability to
> use the 'devel' is to blame...)
>
> Kind regards from the Netherlands
>
> Marco
>
> Marco PM Boks,
>
> Brain Center Rudolf Magnus,
>
> University Medical Centre Utrecht, HP. A.01.489,
>
> PO Box 85500, 3508 GA Utrecht,
>
> The Netherlands,
>
> Phone: +31 88 7556370
>
> Fax: +31 88 7555509
>
> E-mail: mboks@umcutrecht.nl <c.schubart@umcutrecht.nl>
>
>
>
>
> sessionInfo()
> R version 3.0.2 (2013-09-25)
> Platform: x86_64-unknown-linux-gnu (64-bit)
>
> locale:
>  [1] LC_CTYPE=en_US.iso885915       LC_NUMERIC=C
>  [3] LC_TIME=en_US.iso885915        LC_COLLATE=en_US.iso885915
>  [5] LC_MONETARY=en_US.iso885915    LC_MESSAGES=en_US.iso885915
>  [7] LC_PAPER=en_US.iso885915       LC_NAME=C
>  [9] LC_ADDRESS=C                   LC_TELEPHONE=C
> [11] LC_MEASUREMENT=en_US.iso885915 LC_IDENTIFICATION=C
>
> attached base packages:
> [1] parallel  stats     graphics  grDevices utils     datasets  methods
> [8] base
>
> other attached packages:
>  [1] minfi_1.8.9          bumphunter_1.2.0     locfit_1.5-9.1
>  [4] iterators_1.0.6      foreach_1.4.1        Biostrings_2.30.1
>  [7] GenomicRanges_1.14.4 XVector_0.2.0        IRanges_1.20.6
> [10] reshape_0.8.4        plyr_1.8             lattice_0.20-24
> [13] methylumi_2.8.0      matrixStats_0.8.14   ggplot2_0.9.3.1
> [16] reshape2_1.2.2       scales_0.2.3         Biobase_2.22.0
> [19] BiocGenerics_0.8.0   devtools_1.4.1       BiocInstaller_1.12.0
>
> loaded via a namespace (and not attached):
>  [1] annotate_1.40.0       AnnotationDbi_1.24.0  base64_1.1
>  [4] beanplot_1.1          codetools_0.2-8       colorspace_1.2-4
>  [7] DBI_0.2-7             dichromat_2.0-0       digest_0.6.4
> [10] doRNG_1.5.5           evaluate_0.5.1        genefilter_1.44.0
> [13] grid_3.0.2            gtable_0.1.2          httr_0.2
> [16] illuminaio_0.4.0      itertools_0.1-1       labeling_0.2
> [19] limma_3.18.10         MASS_7.3-29           mclust_4.2
> [22] memoise_0.1           multtest_2.18.0       munsell_0.4.2
> [25] nlme_3.1-113          nor1mix_1.1-4         pkgmaker_0.17.4
> [28] preprocessCore_1.24.0 proto_0.3-10          RColorBrewer_1.0-5
> [31] RCurl_1.95-4.1        registry_0.2          R.methodsS3_1.6.1
> [34] rngtools_1.2.3        RSQLite_0.11.4        siggenes_1.36.0
> [37] splines_3.0.2         stats4_3.0.2          stringr_0.6.2
> [40] survival_2.37-7       tools_3.0.2           whisker_0.3-2
> [43] XML_3.98-1.1          xtable_1.7-1
>
>
>
> 2014-02-13 18:23 GMT+01:00 Tim Triche, Jr. <tim.triche@gmail.com>:
>
>> (cc:'ing the epigenomicsforum list due to a similar request there)
>>
>> You can now coerce (at least in devel) without the OOB probes (I checked
>> in an additional fix Monday morning, which was also needed to correct a
>> build issue), but you will still run into issues with minfi's approach.
>>  There are at least two possibilities to get around this and still get
>> estimated cell counts.  Note that I'd choose #2 (or a reasonable semblance
>> of it, i.e. quantile normalizing your data together with Reinius & Kere's
>> sorted leukocyte fractions) whenever feasible, but sometimes it isn't
>> feasible. Here's one way to deal with a lack of raw binary files (#1), and
>> some notes about Jaffe's approach (#2).
>>
>> 1) Use the modified version of the modified version of Houseman's code
>> (yes, that's in there twice!)
>>
>> require(devtools)
>> install_github('chromophobe','ttriche')
>>
>> ?composition  ## I don't write man pages just for fun...
>> require(FlowSorted.Blood.450k)
>> counts <- getBloodCellCounts(your.GenomicRatioSet.coerced.from.lumi)
>> plotCellCounts(counts)
>>
>>
>> 2) Start from the IDATs, if you have them, in which case you can just run
>> the whole thing in minfi.  Sometimes this is impossible (original authors
>> blithely ignore you, otherwise-extremely-helpful program officer for their
>> grant gets buried by a snowstorm, etc.) so I yanked out the essential bits
>> and stuffed them into a convenience function above.  One of these days I'll
>> tidy up chromophobe enough to push it into BioC.  But, if you have raw data
>> (and technical or biological replicates), it would be worth comparing the
>> two approaches to see whether your additional processing steps are helping
>> enough to keep them around.  I may end up doing so (and perhaps comparing
>> both with EWASher).
>>
>>
>> Hope this helps,
>>
>> --t
>>
>>
>> On Sat, Feb 8, 2014 at 10:15 AM, Aileen Bahl <aileen.bahl@helsinki.fi>wrote:
>>
>>> Dear all,
>>>
>>> I used lumi to analyze my 450k data. Now, I want to use the Houseman
>>> algorithm to correct for the cell composition. As far as I read, the
>>> implementation in minfi covers several changes of the algorithm for the
>>> 450k platform. Therefore, I would like to use this package instead of
>>> changing the original code by hand. However, while trying to use minfi, I
>>> faced the problem of transforming my MethylumiM object to the required
>>> RGChannel object. I already found the coercions.R from Bioconductor but
>>> this gives me an error because the full OOB intensities are missing. Could
>>> you please provide some help on how to make this transformation in both
>>> directions (MethylumiM to RGchannel and the other way around)?
>>>
>>> Thanks in advance,
>>> Aileen
>>>
>>> _______________________________________________
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>>> Bioconductor@r-project.org
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>>>
>>
>>
>

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