Hi,

This seems to be working well, although I'm concerned with the raw counts 
> distributions of some cell lines as they look skewed to negative values 
> (histogram attached, apologises for the poor quality). 
>
> Actually, I have seen this effect also using as reference the average of a 
> batch (~250 samples) of SNP6 normal samples. My end goal is to obtain 
> GISTIC scores and when I fed the CbsModel output to GISTIC I noticed that 
> there are more '-1's than '0's, again showing there is a skew to negative 
> ratios.
>
> Am I missing any preprocessing that is required besides the doCRMAv2?
>

Just to follow up, if I follow the vignette CRMAv2 with all the steps 
(http://aroma-project.org/vignettes/CRMAv2/) the histogram of the ratios is 
now centred on zero, attached. Is doing step-by-step slower than 
'doCRMAv2'? It seemed to be taking more time, but I haven't calculated the 
differences.

In the vignette code:

if (length(findUnitsTodo(plm1)) > 0) {
  # Fit CN probes quickly (~5-10s/array + some overhead)
  units1 <- fitCnProbes(plm1, verbose=verbose)
  str(units1)
  # int [1:945826] 935590 935591 935592 935593 935594 935595 ...
  # Fit remaining units, i.e. SNPs (~5-10min/array)
  units1 <- fit(plm1, verbose=verbose)
  str(units1)
}

Is not processing the SNPs an option if you are only interested in 
copy-number changes? That would be ideal :)

Thanks,

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