Hallo everybody,

I am running a microarray analysis using the miRNA2.0 arrays from
affymetrix.
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,
"rma")

> eset.rma_miRNA= call.exprs(data, "rma")

or

> normData<-rma(data)

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

Assa

> sessionInfo()
R version 2.13.0 (2011-04-13)
Platform: i386-pc-mingw32/i386 (32-bit)

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United
States.1252    LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                           LC_TIME=English_United
States.1252

attached base packages:
 [1] tools     tcltk     splines   stats     graphics  grDevices datasets
utils     methods   base

other attached packages:
 [1] mirna20cdf_2.8.0       mirna102xgaincdf_2.8.0 tkWidgets_1.30.0
DynDoc_1.30.0          widgetTools_1.30.0
 [6] limma_3.8.2            siggenes_1.26.0        multtest_2.8.0
simpleaffy_2.28.0      gcrma_2.24.1
[11] 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):
 [1] affyio_1.20.0         annotate_1.30.0       AnnotationDbi_1.14.1
Biostrings_2.20.1     DBI_0.2-5
 [6] IRanges_1.10.4        MASS_7.3-12           preprocessCore_1.14.0
RSQLite_0.9-4         survival_2.36-5
[11] xtable_1.5-6

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