[BioC] gains and losses via mode shifting

[Oscar Rueda]

Well, smoothed means are difficult to translate to alterations, such as  
'loss' or 'gain'. They are on the scale of the log-ratios, so they depend  
a lot on the variability of each array. I wouldn't expect the same levels  
for a set of arrays, even if they are normalized. The main problem with  
methods as DNACopy is that you only have a smoothed mean, but not a  
measure of the precision of that mean. You can use the MergeLevels  
algorithm (Willenbrock and Fridlyand 2005) to reduce the number of  
possible smoothed means in a hypothesis test fashion until you only have  
levels for 'loss', 'normal' and 'gain', but this approach does not always  
produce good results.
Methods based on Hidden Markov models, such as aCGH package, BIOHMM or our  
package RJaCGH use hidden states and gaussian distributions to represent  
copy numbers. Even in this case, every state does not have to correspond  
to a different biological copy number, because we are fitting a mixture of  
normal distributions and if the normal probes have a skewed distribution  
we will need several components to model that distribution. But in this  
case we can use the means and the variances of these states to infere if  
they are well above zero (in that case we could classify them as gains) or  
well below zero (in that case we could classify them as losses). This is  
what our algorithm relabelStates() in RJCGH package does.

Hope this helps,

Oscar M. Rueda
Structural Computational Biology Group
Spanish National Cancer Centre (CNIO)
Madrid, SPAIN.



On Tue, 01 Jul 2008 12:54:59 +0200, Benjamin Otto  
<b.otto at uke.uni-hamburg.de> wrote:

> The logratios are loess normalized with limma and the  
> smoothing/segmentation
> is done with DNAcopy.
>
>
> The problem is that some of the samples seem to belong to maniac tumors.  
> The
> intriguing point for some samples is not really chromosomes 1-3, I only  
> use
> them as a kind of clue, but more that I do observe two possible base  
> lines
> which exhibit nearly comparable peaks in my density function. Each of  
> them
> look as if it could be the real zero line, but I don't know which one.  
> If I
> used some criterion like 2*SD(50% quantile) for detection of gains or  
> losses
> then the shift direction would make a difference.
>
>
> Benjamin
>
>
>
> -----Ursprüngliche Nachricht-----
> Von: Oscar Rueda [mailto:omrueda at cnio.es]
> Gesendet: Tuesday, July 01, 2008 11:46 AM
> An: Benjamin Otto; bioconductor at stat.math.ethz.ch
> Betreff: Re: [BioC] gains and losses via mode shifting
>
> Dear Benjamin,
>
> I'm not sure if I understand correctly your problem, but are your samples
> normalized to have the same median?
>
> Oscar M. Rueda
> Structural Computational Biology Group
> Spanish National Cancer Centre (CNIO)
> Madrid, SPAIN.
>
> On Mon, 30 Jun 2008 13:02:46 +0200, Benjamin Otto
> <b.otto at uke.uni-hamburg.de> wrote:
>
>> Hi,
>>
>> After the segmentation of CGH data in some papers the results are
>> frequently
>> shifted by the density mode. To be more precise the mode of the highest
>> peak
>> is used. However this procedure depends on the condition that there is
>> clearly one prominent peak dominating the density function.
>>
>> Currently, in some of my samples, I do have the problem of two prominent
>> peaks flanking the y-axis which make the decision about the correct  
>> shift
>> direction a difficult one. Moreover in some of the cases a shift in one
>> direction seems to be obvious, in some other cases a shift in the other
>> direction seems more preferable and in a third group the preference is
>> not
>> quite clear. But in all groups a segmentation profile in chromosomes 1-3
>> is
>> nearly identical which suggests that I do observe the same gain or loss
>> (depending on the shift direction) in all these samples.
>>
>> Does anyone have an idea how to assess this problem and how to solve it?
>> Is
>> there another frequently used procedure aside the density mode shifting
>> used
>> for such data?
>>
>> I do have pictures of some samples displaying the problem but they are
>> too
>> big for the mailing list. Is there an official repository I can upload
>> them
>> to?
>>
>> Thanks in advance, best regards,
>>
>> Benjamin
>>
>> ======================================
>> Benjamin Otto
>> University Hospital Hamburg-Eppendorf
>> Institute For Clinical Chemistry
>> Martinistr. 52
>> D-20246 Hamburg
>>
>> Tel.: +49 40 42803 1908
>> Fax.: +49 40 42803 4971
>> ======================================
>>
>>
>>
>
>
>
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