On Fri, Dec 13, 2013 at 11:15 AM, Emilie <emilie.lalo...@gmail.com> wrote:
> Thanks again Henrick. I do see 3 bands, but not sure they are necessarily > clean/distinct. > > > <https://lh5.googleusercontent.com/-yPngBXg2loA/Uqtcqi2z4YI/AAAAAAAAKWI/mcUOS0DWiyQ/s1600/2013-12-13_KB170B_BAF.png> > These normal BAFs look ok to me. > <https://lh5.googleusercontent.com/-yPngBXg2loA/Uqtcqi2z4YI/AAAAAAAAKWI/mcUOS0DWiyQ/s1600/2013-12-13_KB170B_BAF.png> > A similar but slightly noisier pattern is observed in the tumour sample. I > also down-sampled the data 50x to be able to see the patterns (vs a black > blob). Would you consider this as noise/a bad run? > Down-sampling is alright when plotting whole-genome data. If the tumor BAFs ('betaT') are not much noisier than the normal BAFs ('betaN'), I suspect a mismatched pair. Next, look at tumor vs normal BAFs, e.g. plot(betaN, betaT, xlim=c(0,1), ylim=c(0,1)) What do you get? You should see most data points scattered along the diagonal line, similar to the ones in Figure 4 of the online CalMaTe vignette [ http://aroma-project.org/vignettes/CalMaTe ]. If you see data points all over the place, particularly in upper-left and the lower-right corners, your tumor normal pair is not from the same patient. /Henrik > Emilie > > > > On Thursday, December 12, 2013 6:01:48 PM UTC-5, Henrik Bengtsson wrote: > >> The tumor DH panel makes me believe that either your tumor or your normal >> chip data is bad, or alternatively that the tumor and normal are not >> matched. >> >> Check the allele B fraction of your normal. It should show three distinct >> bands. Do the same for the tumor. It should also show distinct bands with >> varying of bands depending on aberrations. If both look clean, then it's >> likely they're not matched. If one is very noisy, then that one is simply >> a bad run/sample. >> >> Henrik >> On Dec 12, 2013 12:42 PM, "Emilie" <emilie....@gmail.com> wrote: >> >>> Thank you both very much! I was indeed referring to smooth.cna, sorry >>> about that confusion. >>> >>> I've switched over to PSCBS and used the dropSegmentationOutliers- it >>> seems to be running well. I've noticed that some of my samples have very >>> fragmented profiles (see attached). Does this suggest poor quality data, or >>> maybe an error in my normalization/plotting? Not all samples are like this, >>> but it almost seems like the order of the of the probes is scrambled? >>> >>> >>> Emilie >>> >>> >>> On Thursday, December 5, 2013 1:08:46 PM UTC-5, Henrik Bengtsson wrote: >>>> >>>> Pierre beat me to this one. Comments below... >>>> >>>> On Thu, Dec 5, 2013 at 9:20 AM, Pierre Neuvial >>>> <pierre....@genopole.cnrs.fr> wrote: >>>> > Hi Emilie, >>>> > >>>> > OK, so you are referring to the “smooth.CNA" function in the DNAcopy >>>> > package, cf >>>> > http://www.bioconductor.org/packages/2.13/bioc/vignettes/DNA >>>> copy/inst/doc/DNAcopy.pdf >>>> > >>>> > What this function is doing is detecting outliers (based on how far >>>> their >>>> > signal value is from their neighbors) and shrink their signal values >>>> toward >>>> > those of their neighbors. >>>> > >>>> > This is indeed appropriate and recommended. I thought that by >>>> "smoothing" >>>> > you meant performing some kind of local averaging of the original >>>> signal >>>> > (e.g. using a mobile median or by binning): this I don't recommend. >>>> Sorry >>>> > for the confusion. >>>> > >>>> > >>>> > To drop outliers, one possibility is to use the >>>> "dropSegmentationOutliers" >>>> > function from the PSCBS package. See the vignettes at >>>> > http://cran.fhcrc.org/web/packages/PSCBS/index.html >>>> > >>>> > Another comment: since you are following the vignette for paired CNA >>>> > analysis, I am guessing that you are working with tumor/normal pairs. >>>> If >>>> > so, then you should use PSCBS rather than CBS for segmentation. >>>> PSCBS is an >>>> > extension of CBS to segment not only total copy numbers but also >>>> allelic >>>> > ratios. See the PSCBS vignette in the above URL. >>>> >>>> To balance this a little bit, I would say there may exist outliers in >>>> the total copy number (TCN) signals that are so sever that they bias >>>> the estimators/test statistic of CBS (which assumes Gaussian signals). >>>> If one believes there are such outliers and worries that they are so >>>> extreme that they would affect the segmentation severely, one could >>>> either (i) drop or (ii) shrink ("smooth") them. In the vignettes of >>>> the PSCBS package, I've last night [PSCBS (>= 0.39.8)] >>>> corrected/clarified Section 'Dropping TCN outliers' to say the >>>> following: >>>> >>>> "There may be some outliers among the TCNs. In >>>> CBS~\citep{OlshenA_etal_2004,VenkatramanOlshen_2007}, the authors >>>> propose a method for identifying outliers and then to shrink such >>>> values toward their neighbors ("smooth") before performing >>>> segmentation. At the time CBS was developed it made sense to not just >>>> to drop outliers because the resolution was low and every datapoint >>>> was valuable. With modern technologies the resolution is much higher >>>> and we can afford dropping such outliers, which can be done by: >>>> >>>> > data <- dropSegmentationOutliers(data) >>>> >>>> Dropping TCN outliers is optional." >>>> >>>> Hope this clarifies. >>>> >>>> Back to the original question: It is not possible to drop (or smooth) >>>> outliers using the CbsModel() pipeline [I'll add that to the todo >>>> list]. The easiest is to turn use the PSCBS package, where you can do >>>> plain old single-track CBS segmentation, paired PSCBS segmentation and >>>> also non-paired PSCBS segmentation. As Pierre says, if you have tumor >>>> SNP data, you should look into doing parent-specific CN analysis, >>>> which you can do either via paired or non-paired PSCBS depending on >>>> whether you have match normals or not. >>>> >>>> To take your allele-specific CRMAv2 and bring it into a format >>>> recognized by the PSCBS package, see >>>> http://aroma-project.org/vignettes/PairedPSCBS-lowlevel >>>> >>>> /Henrik >>>> >>>> > >>>> > Best, >>>> > >>>> > Pierre >>>> > >>>> > >>>> > On Wed, Dec 4, 2013 at 5:29 PM, Emilie <emilie....@gmail.com> wrote: >>>> >> >>>> >> Hi Pierre, >>>> >> >>>> >> Thanks for your answer. I may be wrong but I thought smoothing prior >>>> to >>>> >> segmentation was somewhat common. It is shown in the vignettes for >>>> DNACopy >>>> >> and seems to be fairly common in the literature (this approach was >>>> used in >>>> >> the Metabric paper for example, >>>> >> http://www.ncbi.nlm.nih.gov/pubmed/22522925). >>>> >> >>>> >> I'd be interested in hearing more of your thoughts against this. Do >>>> you >>>> >> have an idea of how much resolution is lost by smoothing? >>>> >> >>>> >> Emilie >>>> >> >>>> >> >>>> >> >>>> >> On Tuesday, December 3, 2013 5:26:38 PM UTC-5, Pierre Neuvial wrote: >>>> >>> >>>> >>> Hi Emilie, >>>> >>> >>>> >>> It's certainly possible to do this within the Aroma framework (e.g. >>>> using >>>> >>> the function "binnedSmoothing"). It's probably not as >>>> straightforward as >>>> >>> running the segmentation directly, though, because this is not a >>>> typical use >>>> >>> case. >>>> >>> >>>> >>> In fact, I'm not sure why you want to perform smoothing before >>>> >>> segmentation ? Smoothing is definitely not required before >>>> segmentation, >>>> >>> and I would actually discourage to go this path because it will end >>>> up in a >>>> >>> loss of resolution along the genome at the smoothing step. >>>> >>> >>>> >>> Best, >>>> >>> >>>> >>> Pierre >>>> >>> >>>> >>> >>>> >>> On Tue, Dec 3, 2013 at 8:53 PM, Emilie <emilie....@gmail.com> >>>> wrote: >>>> >>>> >>>> >>>> Hi there, >>>> >>>> >>>> >>>> I'm new to processing Affy SNP6 chips and so am mainly >>>> experimenting >>>> >>>> with different methods to date. I ran CRMAv2 and followed steps >>>> 1-4 from the >>>> >>>> vignette (http://aroma-project.org/vignettes/CRMAv2). For step 5, >>>> I want to >>>> >>>> do a paired analysis. >>>> >>>> >>>> >>>> Previously I've used DNAcopy to perform CBS for other array types, >>>> and >>>> >>>> would like to follow a similar procedure, which includes smoothing >>>> prior to >>>> >>>> segmentation. Is this possible using the aroma.affymetrix package? >>>> So far >>>> >>>> I've followed the vignette for paired CNA analysis >>>> >>>> (http://aroma-project.org/vignettes/pairedTotalCopyNumberAnalysis) >>>> but >>>> >>>> haven't seen any options for smoothing. >>>> >>>> >>>> >>>> thank you very much, >>>> >>>> >>>> >>>> emilie >>>> >>>> >>>> >>>> -- >>>> >>>> -- >>>> >>>> When reporting problems on aroma.affymetrix, make sure 1) to run >>>> the >>>> >>>> latest version of the package, 2) to report the output of >>>> sessionInfo() and >>>> >>>> traceback(), and 3) to post a complete code example. >>>> >>>> >>>> >>>> >>>> >>>> You received this message because you are subscribed to the Google >>>> >>>> Groups "aroma.affymetrix" group with website >>>> http://www.aroma-project.org/. >>>> >>>> To post to this group, send email to aroma-af...@googlegroups.com >>>> >>>> >>>> >>>> To unsubscribe and other options, go to >>>> >>>> http://www.aroma-project.org/forum/ >>>> >>>> >>>> >>>> --- 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