Hi,

It took me some time (and finding a colaborator to help me) to write
an R package wrapping my copy number algorithm GADA since I have been
busy with so many other things.

I used the answer you kindly provided some time ago to add my
algorithm in aroma.affymetrix:
http://groups.google.com/group/aroma-affymetrix/browse_thread/thread/614c7cdc1cbb8cf5/655efedf35aa6a3c?lnk=gst&q=theta+copy+number#655efedf35aa6a3c
I think it was very detailed and I figured out the gaps by looking how
the CBS and GLAD cases
were handled. I really appreciate it.

I think we still have to do some more checks to make sure everything
is working well.
So far,  I'm quite happy that  it looks like it goes much faster than
CBS method.

While implementing, I noticed that when I extract the copy number
intensities, you also estimate
something that looks like the standard deviation sdM...

> data <- getRawCnData(gada, ceList=ceList, refList=refList, chromosome=22, 
> verbose=-10);
> str(data)
 num [1:74, 1:6] 15685581 16604328 16958128 17506879 18008688 ...
 - attr(*, "dimnames")=List of 2
  ..$ : NULL
  ..$ : chr [1:6] "x" "M" "sdTheta" "sdM" ...

Is this correct? If that is the case I would be interested in knowing
how are these
SD calculated... I may be able to use them in my algorithm.

Finally, one last question is that I get a few probes with the M value
NA. I guess it is fine,
but I just wonder how they arise.

I really appreciate your help,

Roger,

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