[BioC] Delta CT data distribution and cluster analyses; machine learning or other

[Richard Friedman]

Dear John,

	Is the Delta CT data from PCR or from some other method?
If it is from PCR in my experience Delta Delta CT is usually normally  
distributed.
were the first delta references to the difference between the  
experiment and internal reference
(e.g. GAPDH) and the second delta refers to 2 experimental conditions.

With hopes that the above helps,
Rich
------------------------------------------------------------
Richard A. Friedman, PhD
Associate Research Scientist,
Biomedical Informatics Shared Resource
Herbert Irving Comprehensive Cancer Center (HICCC)
Lecturer,
Department of Biomedical Informatics (DBMI)
Educational Coordinator,
Center for Computational Biology and Bioinformatics (C2B2)/
National Center for Multiscale Analysis of Genomic Networks (MAGNet)
Room 824
Irving Cancer Research Center
Columbia University
1130 St. Nicholas Ave
New York, NY 10032
(212)851-4765 (voice)
friedman at cancercenter.columbia.edu
http://cancercenter.columbia.edu/~friedman/

I am a Bayesian. When I see a multiple-choice question on a test and I  
don't
know the answer I say "eeney-meaney-miney-moe".

Rose Friedman, Age 14







On May 13, 2011, at 10:46 AM, john herbert wrote:

> Dear Bioconductors,
> I have a bunch of DeltaCT values for several tissues. If I boxplot  
> the data,
> it looks very similar to microarray data, a lot of congestion around  
> zero.
>
> Likewise, if I log2 the data, as in microarray, the distributions  
> looks
> close to normal and like microarray data.
>
> Please see the image here for different plots;
> https://docs.google.com/leaf?id=0B9IUGsKecS4GNDc0OWVlNzEtZjE5Yi00Y2Q4LWI0M2MtMGFiNzZhMDU0YTFm&hl=en
>
> My question is data manipulation in this manner OK for this type of  
> data and
> will it effect/invalidate any unsupervised machine learning/ 
> clustering?
>
> Can I quantile normalise the data and still do valid clustering?
>
> 	[[alternative HTML version deleted]]
>
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