In the PSCBS package, we provide the `estimateKappa()` function for
estimating kappa, which we refer to as "background signal", cf.
https://cran.r-project.org/web/packages/PSCBS/vignettes/PairedPSCBS.pdf.
The kappa parameter is strongly correlated with the amount of normal
contamination.  We're very conservative in claiming it equals the
normal contamination, because in order for that to be an accurate
estimator we need to assume strong linearity in signals, which we
don't want to claim.  This is also why we keep 'kappa' somewhat under
the radar. However, if you ignore this, you can treat kappa as an
estimator for amount of normal contamination (others do that in other
methods).  In addition, it's pretty safe to say that kappa preserves
the rank of the true normal contamination, that is, you can fairly
safely compare kappa between samples and conclude that one sample has
more normal contamination that another.  What you cannot say for sure
is the exact amount, which might be important when your trying to use
it to control mutation rates etc.

Hope this helps

Henrik


On Fri, Apr 22, 2016 at 11:47 AM, Kevin McCormick
<kevin.patrick.mccorm...@gmail.com> wrote:
> Is there a way to incorporate tumor purity estimates (e.g. from ASCAT) into
> the Aroma pipeline for segmenting copy number changes between parent and
> tumor?  We are looking at cell lines derived from tumors to compare
> consistency between copy number variations.  The tumor purity in the
> parental cells has moderate variation, and the lines with lower purity in
> the parental are getting called to have more copy number changes than those
> with higher purity, even though a manual inspection suggests the differences
> are merely due to change in purity.
>
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