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> 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? 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 <javascript:>> > 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/ >>> DNAcopy/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/ >>> >>>> >>> >>>> --- >>> >>>> You received this message because you are subscribed to the Google >>> >>>> Groups "aroma.affymetrix" group. >>> >>>> To unsubscribe from this group and stop receiving emails from it, >>> send >>> >>>> an email to aroma-affymetr...@googlegroups.com. >>> >>>> >>> >>>> For more options, visit https://groups.google.com/groups/opt_out. >>> >>> >>> >>> >>> >> -- >>> >> -- >>> >> 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/ >>> >> >>> >> --- >>> >> You received this message because you are subscribed to the Google >>> Groups >>> >> "aroma.affymetrix" group. >>> >> To unsubscribe from this group and stop receiving emails from it, >>> send an >>> >> email to aroma-affymetr...@googlegroups.com. >>> >> For more options, visit https://groups.google.com/groups/opt_out. >>> > >>> > >>> > -- >>> > -- >>> > 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/ >>> > >>> > --- >>> > You received this message because you are subscribed to the Google >>> Groups >>> > "aroma.affymetrix" group. >>> > To unsubscribe from this group and stop receiving emails from it, send >>> an >>> > email to aroma-affymetr...@googlegroups.com. >>> > For more options, visit https://groups.google.com/groups/opt_out. >>> >> -- >> -- >> 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<javascript:> >> To unsubscribe and other options, go to >> http://www.aroma-project.org/forum/ >> >> --- >> You received this message because you are subscribed to the Google Groups >> "aroma.affymetrix" group. >> To unsubscribe from this group and stop receiving emails from it, send an >> email to aroma-affymetr...@googlegroups.com <javascript:>. >> For more options, visit https://groups.google.com/groups/opt_out. >> > -- -- 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. 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