Hi.

On Fri, Sep 3, 2010 at 10:38 AM, Kai <wangz...@gmail.com> wrote:
> Hi everyone,
>
> Does anyone know whether the results from "multi-source copy-number
> normalization" can be further processed by segmentation model such as
> CBS and visualized in ChromosomeExplorer?

First of all, if it is possible to pass a CN data set to CbsModel,
GladModel, HaarSegModel etc, then it is basically possible for
ChromosomeExplorer process it too.

>
> There is vignette on MSCN (http://www.aroma-project.org/node/88),
> which talks about how to create binary data files containing copy
> number estimates from multiple platforms, and smoothed CN estimates. I
> was wondering whether these copy number estimates can be used to
> generate segmentation by CBS and subsequently visualized by
> ChromosomeExplorer.

Yes, in the sense that you can process each platform separately, but
unfortunately still *no* in the sense that you cannot process them
jointly.  This is the case both before and after multi-source
copy-number normalization (MSCN).

A SINGEL PLATFORM:
For instance, if you set up a platform-independent data set (*.asb
files) as in the 'Multi-source copy-number normalization (MSCN)'
vignette [http://aroma-project.org/vignettes/MSCN], e.g.

ds <- AromaUnitTotalCnBinarySet$byName(dataSet, tags=tags, chipType="*");

Then you can pass this to CbsModel just as you pass an CnChipEffectSet
'ces' in one of the total CN vignettes, e.g.

cbs <- CbsModel(ds);
ce <- ChromosomeExplorer(cbs);


MULTIPLE PLATFORMS:
In case you want to segment MSCN normalized data across multiple
platforms, you have to turn to the low-level methods available in
aroma.  This means that you can not leverage the automatic pipelines
of the CbsModel and/or ChromosomeExplorer.  You have to do your
storing and plotting of results yourself.  Here is an outline:

Say you have a 'dsList' list object containing
AromaUnitTotalCnBinarySet from multiple platforms after MSCN
normalization as in http://aroma-project.org/vignettes/MSCN, e.g.

library("aroma.cn");
log <- Arguments$getVerbose(-8, timestamp=TRUE);
tagsList <- list("MSKCC", "Harvard", "Stanford", "Broad");
dataSet <- "TCGA,GBM,testSet,pairs";
dsList <- lapply(tagsList, FUN=function(tags) {
  AromaUnitTotalCnBinarySet$byName(dataSet, tags=tags, chipType="*");
});
ugp <- AromaUgpFile$byChipType("GenericHuman", tags="100kb");
mscn <- MultiSourceCopyNumberNormalization(dsList, fitUgp=ugp);
dsNList <- process(mscn, verbose=verbose);

The you can extract a list of data files for one particular sample
across platforms as:

dfList <- getFileList(dsList, sampleName);

>From this list of files (for the same sample), you can then extract a
RawCopyNumbers object contain all the CN data for a particular
chromosome as:

cn <- extractMergedRawCopyNumbers(dfList, chromosome=chromosome,
verbose=verbose);

Please note that extractMergedRawCopyNumbers() is a non-documented
alpha/beta function, so it may change in the future.

Now, with this RawCopyNumbers 'cn' object you can do neat things, e.g.

print(cn);
plot(cn, pch=".", cex=2, col=cn$id);
fit <- segmentByCBS(cn, verbose=verbose);
drawCnRegions(fit, lwd=3);
str(fit);

Feel free to give feedback so we can develop this use case further.

Hope this helps.

/Henrik

>
>
> Thank you very much.
>
> Best,
> Kai
>
> --
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version of the package, 2) to report the output of sessionInfo() and 
traceback(), and 3) to post a complete code example.


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