Hi Henrik, Thank you very much for the information and it has clarified lot of my doubts.
Best, Sam. On Thursday, January 22, 2015 at 8:36:59 PM UTC+1, Henrik Bengtsson wrote: > > Hi guys, > > here are some late feedback on this discussion: > > * When talking about copy numbers, it is important to always be very > clear and distinguish between whether we talk about normal/germline > CNs or tumor CNs. The former take integer CN levels (0, 1, 2, 3, > ...), whereas for tumors we very rarely observe pure homogeneous tumor > cells, which is why we only measure and observe non-integer CN levels. > Hopefully, we observe at least discrete CN levels in tumors, but one > should never expect integer levels. > > * aCGH: a historical term often used as a synonym for total copy > numbers. For example, some say "aCGH analysis" when they really mean > "total copy-number analysis". aCGH stands for array-CGH, or in full > 'array comparative genomic hybridization'. This refers to the older > generation two-color/two-channel arrays where a test and a reference > sample where labelled with two different dyes and "competitively" > hybridized to the same array and the same probes. I recommend to stop > using this term and instead use "total copy number", total CN, or > "TCN" (when it's clear). By being explicit about "total", you're > also explicitly contrasting it to "parent-specific" CNs (which you can > do if you have SNP data). > > * CNA: Copy-Number Aberration. This term can be applied to both tumor > and germline samples. In tumors you expect non-integer CN levels. In > germline/normals you expect integer CN levels (0, 1, 2, 3, ...). > > * CNP: Copy-Number Polymorphism. This term applies to copy-number > differences in relationship to a population. This also implies we're > talking about germline genomes. In other words, CNPs are also integer > CN levels (0, 1, 2, 3, ...). CNPs are used to specify, say, "2% of > the Europeans have a 1 copy deletion of length 1.0-1.5 Mb on Chr 3 at > 124.5Mb". CNPs is for segment deletions and gains what SNPs are for > nucleotide polymorphisms. The term CNP is rare. It is much more > common to hear/see "CNV". > > * CNV: Copy-Number Variation. Ideally the word "variation" refers to > "polymorphism" and therefore the term CNV should be used only to refer > to CNPs. I don't know if there is a formal definitions, but I find it > unfortunate to see CNV being used when CNA should be used. By my > books, CNV only takes integer CN levels (0, 1, 2, 3, ...). The term > CNV should never be used to refer to CN levels in tumors. > > * Calling total CN levels is very hard in tumors, and as the first > above point alludes to, it may not even be a well defined problem. > For instance, imagine you have a tumor sample with 5% tumor cells and > 95% normal cells, and that the those tumors cells all have a deletion > on Chr 2. Then, at what point to you consider that sample itself to > have a deletion on Chr 2? Are you after he sample/tissue itself, or > are you after those 5% tumors cells? What if you have a heterogeneous > mix of tumor cells? The more precise you can specify your question > the more easy it is for you to decided what approach forward (may) > work and what doesn't work. Here "work" can also be read as "make > sense". > > * The first and most important task for almost all segmentation > methods is to *segment* the genome, that is, identify at what genomic > locations the observed DNA (tumor, normal or a mix) changes in CN > level. Together, these location, aka "change points", defines how the > genome can be "partitioned" into segments with equal CN levels, such > that when we look at a particular segment, we can assume that all > genomic locations within that segment has the same underlying genomic > composition (e.g. gain, loss, loss in 5% of the cells, etc.). CBS, > GLAD, and many other methods, segment the genome this way as a first > step. > > * A common task after having decided on the segments (partitioning of > the genome), is to decide on what is going on within each segment. > Not all methods does this. For instance, CBS "only" provides you with > the change points. GLAD on the other hand does both the segmentation > and then also provides a method for calling. Theoretically, there is > nothing preventing you from using the GLAD *calling* algorithm using > the segmentation found by CBS. Unfortunately, I don't think it is > straightforward to do that in practice; at least you have to coerce > one data format into one that GLAD understands. > > * GLAD does not scale well with the number of loci, because it's > computational complexity is ~O(n^2), unless things have changed since. > In 2007, I tried to predict GLAD's processing time when we were using > the Affymetrix 500K chips and the GenomeWideSNP_5 and GenomeWideSNP_6 > were starting to come out. A GWS6 chip would basically take days to > segment. See attached PNG for a table. > > * CBS is much faster as an algorithm. Also, the implementation in the > DNAcopy package has been made even faster over time. There was a > major speedup back in 2009, cf. > http://aroma-project.org/benchmarks/DNAcopy_v1.19.2-speedup/ > <http://www.google.com/url?q=http%3A%2F%2Faroma-project.org%2Fbenchmarks%2FDNAcopy_v1.19.2-speedup%2F&sa=D&sntz=1&usg=AFQjCNHhIzh1bfbX0gRJh4BpTlp8oMj8UQ> > > > Over and for now > > Henrik > > On Thu, Jan 22, 2015 at 12:42 AM, Chengyu Liu <chengyu...@gmail.com > <javascript:>> wrote: > > Hi, > > > >> > >> I have tried this and works good but at the end I need the information > >> whether there is a gain or loss at the segment. I will use GLAD model > to get > >> gain or loss at a segment. My samples and controls are completely > unrelated > >> so I am little bit doubtful whether I am doing right or not. I also > found > >> some other algorithms that can work on segments produced by CBS model > still > >> looking into them. > >>> > >>> > > I think you can use GLAD to call gain and loss. But CBS does not return > gain > > or loss, only segments. If you use CBS you should call gain or loss > yourself > > (or use other tools such as GISTIC). > > > >> > >> Then I am also looking for CNA. What other softwares have you tried on > >> data from CytoScan HD array? > > > > Like you I used aroma to preprocess, segmented using CBS and manually > call > > gain or loss. The simplest way is using a threshold to define gain or > loss. > > If I remember correctly, one of TCGA papers in Nature, there a fixed > > threshold was used to define gain and loss. Maybe you can check that. > > > > Br, > > > >>> > >>>> > >>>> > >>>> > >>>>> > >>>>> Br, > >>>>> C.Y > >>>>> > >>>>> > >>>>>> > >>>>>> > >>>>>> Thanks, > >>>>>> > >>>>>> Best Regards, > >>>>>> Sam. > >>>>>> > >>>>>> On Tuesday, January 20, 2015 at 10:38:27 AM UTC+1, Chengyu Liu > wrote: > >>>>>>> > >>>>>>> Hi, > >>>>>>> > >>>>>>> On Monday, January 19, 2015 at 3:42:59 PM UTC+2, Sam Padmanabhuni > >>>>>>> wrote: > >>>>>>>> > >>>>>>>> Dear AromaAffymetrix Team, > >>>>>>>> > >>>>>>>> First of all, thank you very much for such a detailed vignette on > >>>>>>>> how to perform the CNV analysis. > >>>>>>>> > >>>>>>>> I am Sam, a PhD student in genetics, working on CNV analysis on > data > >>>>>>>> from CytoScan HD Array. I have read the vignette to do CRMAv2 and > non-paired > >>>>>>>> CBS. I have copied the commands and ran in R. > >>>>>>>> > >>>>>>>> But, I have few questions regarding CbsModel and GladModel in > >>>>>>>> segmentation algorithm: > >>>>>>>> > >>>>>>>> 1. It is mentioned that, copy number states is not calculated in > >>>>>>>> CbsModel segmentation. How do I get information of whether the > segment is a > >>>>>>>> loss or gain from output of CbsModel? I mean can this information > be passed > >>>>>>>> to other algorithms to estimate copy number state. > >>>>>>> > >>>>>>> As far as I know, the out put of CBS is the relative copy number. > It > >>>>>>> does not directly tell you the copy number states. > >>>>>>>> > >>>>>>>> > >>>>>>>> 2. I have looked in to GLAD model and it is mentioned that it is > >>>>>>>> developed for aCGH but my data is not from aCGH. Can it be still > used to > >>>>>>>> calculate copy number states for the data I am working on? > >>>>>>> > >>>>>>> GLAD can calculate copy number states for affy-array, although I > have > >>>>>>> not used it before. > >>>>>>>> > >>>>>>>> > >>>>>>>> 3. Also, do you have a vignette on how to run CRMAv2 and CBS on > >>>>>>>> CytoScan HD array? This would be really helpful. > >>>>>>> > >>>>>>> It is the same with other chiptype, prepare input as required > (there > >>>>>>> is vignette). > >>>>>>> > >>>>>>> > >>>>>>> BTW, I am also working on CytoScan HD. What kind of analysis are > you > >>>>>>> going to do? Do you have paired samples or non-paired? Maybe we > have > >>>>>>> something common and we can discuss. > >>>>>>> > >>>>>>> Br, > >>>>>>> C.Y > >>>>>>> > >>>>>>> > >>>>>>>> > >>>>>>>> Thank you, > >>>>>>>> > >>>>>>>> Best, > >>>>>>>> Sam. > >>>>>>>> > >>>>>>>> > >>>> > >>>> Best Regards, > >>>> Sam. > >> > >> > >> > >> Best, > >> Sam. > > > > -- > > -- > > 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/d/optout. > -- -- 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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