They are the mean levels on the log2 ratio scale. /Henrik
On Wed, Aug 18, 2010 at 11:50 AM, Ajanthah Sangaralingam <a.sangaralin...@qmul.ac.uk> wrote: > Thank you very much for the information it was very helpful. > I have now made a comparison of tumor sample with a normal sample and fitted > a segmentation model, I have used CBS and GLAD. > > The output of these models gives me the mean raw CN level for the region and > the number of loci in the region. > Is the "mean" value given by the model the mean log2ratio of the copy number > estimate? > > Many thanks for your help > > Ajanthah > > > > > > > > > On 04/08/2010 19:05, "Pierre Neuvial" <pie...@stat.berkeley.edu> wrote: > >> Hi, >> >> On Tue, Aug 3, 2010 at 8:12 AM, Ajanthah Sangaralingam >> <a.sangaralin...@qmul.ac.uk> wrote: >>> Thank you for the reply. I actually need to get the log2 copy number >>> ratios >>> form the raw .cel files of a GenomeWideSNP6.0 array - I was using CRMA1 >>> but >>> am now repeating the analysis using CRMA v2. >>> I am putting all of the different tumour types either matched or >>> unmatched >>> with a germline sample in the same directory and all the normal samples >>> in >>> another directory. >> >> This is fine, but note that did not need to put them in separate >> directories. >> >>> I will then go through the processes of qulaity assesment, calibration >>> crosstalk, normalization for probe sequence effect, probe summarization, >>> and >>> normalization of PCR fragment length effects. >>> >>> Do I need to calculate the raw copy numbers and turn these into log2 copy >>> numbers? >> >> I don't understand your question. >> >>> How would I then calculate the copy numbers for >>> 1. Unpaired tumour samples - will need to be compared to a pooled >>> reference >>> from a particular tumpur type >>> 2. Paired samples? >> >> >> It's hard to be more specific than what Henrik already said without >> more details on your sample names and tumor types, and most >> importantly on the design of your study. >> >> I'll try for the unpaired analysis (your 1.) >> >> I am assuming that you have two data sets: >> - 'dsT' for the tumor samples, >> - 'dsN' for the normal samples. >> >> It seems that your concern is to use *tumor-type specific* sets of >> normal samples. Is that correct ? See my remark below on the fact >> that I'm not sure it's what you should do. >> >> If so, then assuming that 'idxT1' contains the indices of all tumor >> samples from a particular tumor type in dsT, and 'idxN1' contains the >> indices of normal samples from the same tumor type in dsN, you can do >> >> dsN1 <- extract(dsN, idxN1); ## normal samples of tumor type 1 >> dsT1 <- extract(dsT, idxT1); ## tumor samples of tumor type 1 >> >> dfR1 <- getAverageFile(dsN1); ## pool of normal samples of tumor type 1 >> sm1 <- CbsModel(dsT1, dfR1); >> >> Then you can do >> >> fit(sm1, chromosome=1, array=1, verbose=log); >> >> to perform CBS segmentation and/or >> >> rawCNs1 <- extractRawCopyNumbers(sm1, array=1, chromosome=1) >> plot(rawCns1) >> >> to extract and plot raw copy numbers (independently of CBS). >> >> And so on for each tumor type. >> >> This should answer your 1. However, I'm not sure that using >> tumor-type specific sets of normal samples will give you better >> results. This depends in particular on the following specific points >> in your design: >> - Are you "normals" normal tissue samples blood samples ? >> - Were all the tumor and normal microarrays done in the same lab, and >> approximately at the same time ? If so, combining all the normals >> could be better. >> One way to know which option is best (tumor-specific reference or >> global reference) is to try both and compare the segmentation results >> (e.g. using ChromosomeExplorer). >> >> For your 2 (paired tumor/normal analysis), I think Henrik gave all the >> necessary information already, but >> >> assuming that 'idxT2' contains the indices of all tumor samples from a >> particular tumor type in dsT that have a paired normal, and 'idxN2' >> contains the indices of these paired normal samples from the same >> tumor type in dsN, further assuming that *the samples are in the same >> order in the two sets of indices*, you can do >> >> dsN2 <- extract(dsN, idxN2); >> dsT2 <- extract(dsT, idxT2); >> >> sm2 <- CbsModel(dsT2, dsN2); >> >> fit(sm2, chromosome=1, array=1, verbose=log); >> rawCNs2 <- extractRawCopyNumbers(sm2, array=1, chromosome=1) >> plot(rawCNs2); >> >> I hope this helps, >> >> Pierre. >> >>> >>> Many thanks for your help >>> >>> On 18/07/2010 12:01, "Ajanthah Sangaralingam" >>> <a.sangaralin...@qmul.ac.uk> >>> wrote: >>> >>>> Hi, >>>> >>>> Yes this is correct. >>>> >>>> Many thanks >>>> >>>> Ajanthah >>>> ________________________________________ >>>> From: aroma-affymetrix@googlegroups.com >>>> [aroma-affymet...@googlegroups.com] >>>> On >>>> Behalf Of Henrik Bengtsson [...@stat.berkeley.edu] >>>> Sent: Sunday, July 18, 2010 11:28 AM >>>> To: aroma-affymetrix >>>> Subject: Re: [aroma.affymetrix] Analysis of GenomeWideSNP6.0 data >>>> >>>> Hi. >>>> >>>> On Fri, Jul 16, 2010 at 11:13 AM, Ajanthah Sangaralingam >>>> <a.sangaralin...@qmul.ac.uk> wrote: >>>>> Hi, >>>>> >>>>> I have been doing some paired total copy number analysis in aroma >>>>> afyymetrix. >>>>> The dataset I have is complicated for haf the dataset I have reference >>>>> samples, for the other half I will do an unpiared analysis. >>>> >>>> So, to make sure I don't misunderstand, you have an Affymetrix >>>> GenomeWideSNP_6 (GWS6) data set that contains tumors and for some, but >>>> not all of the you have matched normal samples, where "matched normal" >>>> mean a normal tissue or normal blood extract from the same patient as >>>> the tumor was taken. Is this correct? >>>> >>>>> I alos have data from many different tomor types not just one - I do >>>>> not >>>>> have >>>>> the sample number of samples from each type of tumor. >>>>> >>>>> My questions are: >>>>> >>>>> When doing a paired analysis - the normal and tumour data have there >>>>> own >>>>> directories and allelic cross talk calibration, summarization and PCR >>>>> fragment length normlization is all done separately. >>>> >>>> It is important to know which preprocessing method you are following. >>>> Since you are working with GWS6 arrays, I recommend that you use the >>>> CRMAv2 preprocessing method as described in vignette 'Estimation of >>>> total copy numbers using the CRMA v2 method (10K-GWS6)': >>>> >>>> http://aroma-project.org/vignettes/CRMAv2 >>>> >>>> Note the function doCRMAv2() which is convenient when you do not want >>>> to dig into the details. >>>> >>>> Since you are not mentioning probe-sequence normalization, it looks >>>> like you are indeed using CRMA v1. If so, I recommend that you use >>>> CRMA v2 instead. Using CRMA v2 will be really useful for you, as >>>> explained below. >>>> >>>>> Is this tue for the different tumor types as well - should they be >>>>> treated >>>>> separately for all of tehse stages or can all the tumor types be put >>>>> into >>>>> one >>>>> tumour directory. >>>> >>>> This is perfectly fine if you are using CRMA v2 (but not CRMA v1). >>>> As now clarified in the vignette, in addition to the CRMAv2 paper, you >>>> will get identical results with CRMAv2 regardless what other samples >>>> you put in your data set; the CRMAv2 method is truly a single-array >>>> method. It is only when you get to the step where calculate copy >>>> numbers relative to a pool of references you have to make a decision >>>> on what pool of reference samples you'll use. >>>> >>>>> Also, I am unable to extarct the reference samples that I want after >>>>> normaization to compare to the matching sanmples say in another tumor >>>>> type. >>>>> Segmentation models cannot be fit unless the number of samples match >>>>> exactly. >>>> >>>> It actually can, as explained below. >>>> >>>>> >>>>> Does this mean that I need to do all the stages again for the subsets >>>>> of >>>>> reference samples that have matching pairs in the other tumor types? >>>> >>>> The segmentation models, for instance CbsModel, segments each tumor >>>> either (a) to a matched normal, or (b) to a global reference. When >>>> you do (a), by definition there has to be an equal number of tumors as >>>> matched normals, whereas when you do (b), there can only be one >>>> reference sample specified. >>>> >>>> Example of paired tumor-normal segmentation: >>>> >>>> # A set of tumor samples >>>> dsT <- ... >>>> # A set of matched normal samples ordered such that they >>>> # match the ordering in the tumor data set 'dsT'. >>>> dsN <- ... >>>> sm <- CbsModel(dsT, dsN); >>>> >>>> Example of tumor-global reference segmentation: >>>> >>>> # A set of tumor samples >>>> dsT <- ... >>>> # A set of reference samples (can be normals or everything) >>>> dsR <- ... >>>> # Use the pool of all reference samples as the reference >>>> dfR <- getAverageFile(dsR); >>>> sm <- CbsModel(dsT, dfR); >>>> >>>> Note that 'dfR' is a single "virtual" array, not a data set. >>>> >>>> Did that above make sense? >>>> >>>> /Henrik >>>> >>>>> >>>>> Many thanks >>>>> >>>>> Ajanthah >>>>> >>>>> >>>>> >>>>> >>>>> This email may contain information that is privileged, confidential or >>>>> otherwise protected from disclosure. >>>>> It must not be used by, or its contents copied or disclosed to, persons >>>>> other >>>>> than the addressee. >>>>> If you have received this email in error please notify the sender >>>>> immediately >>>>> and delete the email. >>>>> This message has been scanned for viruses. >>>>> >>>>> -- >>>>> 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-affymetrix@googlegroups.com >>>>> To unsubscribe and other options, go to >>>>> http://www.aroma-project.org/forum/ >>>>> >>>> >>>> -- >>>> 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-affymetrix@googlegroups.com >>>> To unsubscribe and other options, go to >>>> http://www.aroma-project.org/forum/ >>> >>> -- >>> 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-affymetrix@googlegroups.com >>> To unsubscribe and other options, go to >>> http://www.aroma-project.org/forum/ >>> >> >> -- >> 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-affymetrix@googlegroups.com >> To unsubscribe and other options, go to >> http://www.aroma-project.org/forum/ > > -- > 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-affymetrix@googlegroups.com > To unsubscribe and other options, go to http://www.aroma-project.org/forum/ > -- 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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