[BioC] Agilent single color array

[Sean Davis]

On Mon, Jun 30, 2008 at 1:54 PM, Kasper Daniel Hansen
<khansen at stat.berkeley.edu> wrote:
> Hi
>
> I have gotten my hands on data from the single color Agilent platform using
> a custom array design and I would like to hear what people are usually doing
> when it comes to preprocessing.
>
> I have previously analyzed some two color arrays from Agilent and found that
> the data I had was pretty standard when it comes to normalization. Even
> though I preferred doing my own preprocessing the Agilent supplied
> gProcessedSignal and rProcessedSignal columns were decent (this was from a
> much earlier version of their software - Feature Extractor).
>
> But for the one color arrays I find that gProcessedSignal performs horrible
> - flat out horrible, the raw data looks much better. Furthermore, when I
> normalize between I arrays I see relatively little effect of normalization,
> sometimes the normalization even increases the spread on MA plots where I
> would not expect it to do anything. Of course this may be related to the
> hybridizations done or the array design I have in hand, but I still find it
> somewhat surprising.
>
> I have tried vsn2 from vsn, quantile normalization and quantile
> normalization following normexp (offset 25 and 50) background correction
> from Limma. All 3 (4 if you count the 2 offsets) combinations have also been
> done with and without subtracting the local background estimate from Feature
> Extractor (the gBGMeanSignal column).
>
> Anyway, I am curious as to what other people's experience using this
> platform are.

What type of array is it?  In particular, is it miRNA?

Sean