Thanks very much Pierre.

Apologies for my confusing use of terminology. I do indeed mean that I 
applied ASCRMA(v2) to each batch separately.

Regards,
Peter



On Tuesday, January 5, 2016 at 9:22:06 PM UTC+11, Pierre Neuvial wrote:
>
> Dear Peter, 
>
> First, just to make sure we are talking about the same things, when 
> you write "I have applied ASCRMA to each array separately.", you mean 
> that you applied ASCRMA(v2) to each of the two *batches* separately, 
> right ?  In the aroma-project world, we usually reserve the word 
> 'array' for what you called a 'sample'. 
>
> Then, let me recall or clarify that ASCRMA(v2) processes each or the 
> 28 samples separately.  Therefore, it would make no difference you 
> applied ASCRMAv2 on a single data set of 28 samples, or to two 
> separate data sets, ...or to 28 separate data sets.  This is why 
> ASCRMA(v2) is called a "single-array" method. 
>
> From the density plots, it seems to me that the normalization was able 
> to make the intensity distributions more similar, which is a good sign 
> that part of the experimental variability has been removed.  However, 
> I would like to emphasize that we do not expect these distributions to 
> be strictly identical after normalization (as would be the case if we 
> were performing quantile normalization).  In fact, some of the 
> differences we see after normalization may correspond to true 
> biological signal. 
>
> At first sight it seems to me that it is safe to use your normalized 
> data for downstream analysis. 
>
> If you want to dig further, one thing you could do is to plot these 
> densities for the normal samples only.  There, we do not expect much 
> biological variation in the densities.  If there is still clear 
> variation between the two batches, then one possibility to reduce it 
> could be to force the "average" density of the normal samples of the 
> two batches to be identical.  The transformation used for the normal 
> samples of each batch could then be used to normalize the other 
> samples of that batch. 
>
> I hope this will help you. 
>
> Best, 
>
> Pierre 
>
>
>
> On Tue, Jan 5, 2016 at 7:32 AM, Peter Savas <psa...@gmail.com 
> <javascript:>> wrote: 
> > Dear Group, 
> > 
> > I have 28 samples of tumour normal pairs, run on 2 GenomeWideSNP6.0 
> arrays 
> > several months apart. Some of the pairs have members on different chips 
> (ie 
> > tumor on one, normal on the other). I am not sure about the best way to 
> > normalise the data such that these split pairs can be used for 
> downstream 
> > analysis. The plan is for ASCRMA, TumorBoost and then PSCBS. 
> > 
> > I have applied ASCRMA to each array separately. Probe density plots pre 
> and 
> > post this normalisation are attached. It seems that there is still some 
> room 
> > for improvement. 
> > 
> > Thank you and all the best for the new year. 
> > 
> > Regards, 
> > Peter 
> > 
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