Thanks very much Henrik
On Dec 8, 1:36 pm, Henrik Bengtsson <henrik.bengts...@aroma-
project.org> wrote:
> Hi.
>
> On Thu, Dec 8, 2011 at 7:01 AM, Les Ander <lesa...@gmail.com> wrote:
> > Dear Henrik,
> > I have a really quick question. I have obtained regions of cnv using
> > cbs and
> > I am unclear regarding the interpretation of the data, in particular,
> > what does
> > "mean" and the "count" mean? Is count the number of probes?
>
> > Is mean the log2 ratio?
>
> Except for the added 'url' field, those are basically renamed versions
> of what is returned by segment() of the DNAcopy package. See output
> value 'out' in help("segment", package="DNAcopy"). So, 'mean' is mean
> of the locus-level (log2) CN estimates, 'count' is the number of data
> points in that segment.
>
> > Are numbers greater than 0 amplification and
> > less than
> > 0 deletions? If yes, how do I know if it is significant (are only the
> > significant regions
> > of non-neutrality listed?). It appears that the first region is almost
> > a 150 Mb region of change
> > which is not possible for my data (as it is karyotipically normal
> > without such large
> > changes), that is why I am slightly confused.
>
> The CBS algorithm does not do *calling* of CN states; it only
> identifies change points where it believes there the mean levels to
> the left and the right are not equal, cf.
>
> * Olshen, A. B., Venkatraman, E. S., Lucito, R., Wigler, M. (2004).
> Circular binary segmentation for the analysis of array-based DNA copy
> number data. Biostatistics 5: 557-572.
> * Venkatraman, E. S., Olshen, A. B. (2007) A faster circular binary
> segmentation algorithm for the analysis of array CGH data.
> Bioinformatics 23: 657-63.
>
> FYI, the GLAD algorithm (GladModel) does calling of CN states, but
> uses a different method for identifying change points. It is also
> much slower than CBS, especially for high-density arrays.
>
> /Henrik
>
>
>
>
>
>
>
>
>
> > sample chromosome start stop mean count url
> > mysample 1 61736 152555528 0.105 79069
> >http://genome.ucsc.edu/cgi-bin/hgTracks?clade=
> > mysample 1 152555707 152586239 1.182
> > 31 http://genome.ucsc.edu/cgi-bin/hgTrack
>
> > Can you please recommend how do I go about finding a threshold (for
> > mean) such that the rate of false positive and false negatives is not
> > great
>
> > thanks
>
> > --
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--
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