Hi all,

We are interested in using VirtualArray while mining a few datasets into
order to ask more theoretical questions than the data was originally
intended for. However, to set the foundation I need to merge various
data-sets from very similar platforms.

I have just a couple questions regarding the application of VirtualArray.
To reduce complexity in our dialogue I will just refer to 2 GEO datasets
for the time being.

First, we have checked the expression summaries of each of the GeoSets. How
does your program infer which normalizing to perform on one data-set vs.
the other to make the distributions more similar to each other? I can make
assumptions with the below example, however do you have a test for this?

> summary(Eset1)[,1:3]
   Pat1            Pat2             Pat3
 "Min.   :-1.48434  " "Min.   :-1.628659  " "Min.   :-1.63216  "
 "1st Qu.:-0.05553  " "1st Qu.:-0.075109  " "1st Qu.:-0.08433  "
 "Median : 0.01388  " "Median :-0.001093  " "Median : 0.02052  "
 "Mean   : 0.01210  " "Mean   : 0.002367  " "Mean   : 0.02474  "
 "3rd Qu.: 0.10731  " "3rd Qu.: 0.075719  " "3rd Qu.: 0.16198  "
 "Max.   : 2.01628  " "Max.   : 2.439713  " "Max.   : 1.62180  "
> summary(Eset2)[,1:3]
   Pat1            Pat2             Pat3
 "Min.   : 0.8523  " "Min.   : 0.8373  " "Min.   : 0.6775  "
 "1st Qu.: 4.6027  " "1st Qu.: 4.4968  " "1st Qu.: 4.4723  "
 "Median : 6.0780  " "Median : 6.0009  " "Median : 5.9944  "
 "Mean   : 6.1098  " "Mean   : 6.0757  " "Mean   : 6.0891  "
 "3rd Qu.: 7.4339  " "3rd Qu.: 7.4802  " "3rd Qu.: 7.5196  "
 "Max.   :13.5664  " "Max.   :13.4372  " "Max.   :13.3803  "

Second, when compiling the new expression set with:

> my_virtualArrays$iPSC_hESC_noBatchEffect <- virtualArrayExpressionSets()

While this runs we have run into 2 problems. The first being that our
annotation type is GPL5175 for both Esets in this example. And we will
receive the following error:      Error in eval(expr, envir, enclos) :
object 'GPL5175SYMBOL' not found.

The second is that this step also relies upon the BiocParallel bioconductor
source package which does not seem to be installing for R v. 3.0.2. I have
attempted bioconductor download, install.packages command, reinstallation
of R etc... with no advances.

Any insight to the above questions would be great.

Yours,

Michael

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