[BioC] rma vs. call.exprs
beniltoncarvalho at gmail.com
Thu Jun 16 12:56:08 CEST 2011
are you really sure that you're getting different results?
all that call.exprs(obj, 'rma') does is to call rma(obj)... nothing else.
make sure you don't have any pre-existing object on your R session.
i'd be really surprised if both strategies give you discordant results...
here's a reproducible example of what i mean:
y1 = exprs(rma(Dilution))
y2 = exprs(call.exprs(Dilution, 'rma'))
all.equal(y1, y2) ## i get TRUE, as expected
On 16 June 2011 11:41, Assa Yeroslaviz <frymor at gmail.com> wrote:
> Hallo everybody,
> I am running a microarray analysis using the miRNA2.0 arrays from
> I ran it a few times with different parameters and was wondering why I am
> getting different results in some cases but not in other.
> I than accidentally fond out that there is a strong different in the results
> I get when I am normalizing my data with RMA or with call.exprs( data,
>> eset.rma_miRNA= call.exprs(data, "rma")
> Can anyone explain to me what is the difference between the two methods. In
> the help file from call.exprs they only say that it works with the rma
> algorithm, but no more.
> Should there be a difference in the results?
> Thanks a lot for the help
> R version 2.13.0 (2011-04-13)
> Platform: i386-pc-mingw32/i386 (32-bit)
>  LC_COLLATE=English_United States.1252 LC_CTYPE=English_United
> States.1252 LC_MONETARY=English_United States.1252
>  LC_NUMERIC=C LC_TIME=English_United
> attached base packages:
>  tools tcltk splines stats graphics grDevices datasets
> utils methods base
> other attached packages:
>  mirna20cdf_2.8.0 mirna102xgaincdf_2.8.0 tkWidgets_1.30.0
> DynDoc_1.30.0 widgetTools_1.30.0
>  limma_3.8.2 siggenes_1.26.0 multtest_2.8.0
> simpleaffy_2.28.0 gcrma_2.24.1
>  genefilter_1.34.0 affy_1.30.0 Biobase_2.12.1
> rcom_2.2-3.1 rscproxy_1.3-1
> loaded via a namespace (and not attached):
>  affyio_1.20.0 annotate_1.30.0 AnnotationDbi_1.14.1
> Biostrings_2.20.1 DBI_0.2-5
>  IRanges_1.10.4 MASS_7.3-12 preprocessCore_1.14.0
> RSQLite_0.9-4 survival_2.36-5
>  xtable_1.5-6
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