Hi Henrik,
Thanks a lot for the help.
For sm <- CbsModel(dsTR, ref=dfR, tags="HapMapRef"), you mean sm <-
CbsModel(dsT, ref=dfR, tags="HapMapRef"), right?
Thanks,
Sean
On Thu, Aug 1, 2013 at 6:00 PM, Henrik Bengtsson <
henrik.bengts...@aroma-project.org> wrote:
> On Mon, Jul 29, 2013 at 7:45 PM, ying chen <njs...@gmail.com> wrote:
> > Hi Henrik,
> > Thanks a lot for the help!
> > Sorry I have more questions. I am following "How to: Calculate total copy
> > number ratios from total (non-polymorphic) signals" and "Vignette: Total
> > copy-number segmentation (non-paired CBS)", but I am not sure if I do it
> > correctly.
> > I have two SNP6 datasets Tumor and HapMap270 and I want to use HpaMap270
> as
> > reference to go all the way to CBS step. So I do the following steps
> > respectively.
> > > ds1 <- doCRMAv2("HapMap270", chipType="GenomeWideSNP_6,Full")
> > > ds2 <- doCRMAv2("Tumor", chipType="GenomeWideSNP_6,Full")
> > After that, I do
> > > dataSet <- "HapMap270"
> > > tags <- "ACC,ra,-XY,BPN,-XY,AVG,A+B,FLN,-XY"
> > > chipType <- "GenomeWideSNP_6"
> > > dsN <- AromaUnitTotalCnBinarySet$byName(dataSet, tags=tags,
> > chipType=chipType)
> > > dataSet <- "Tumor"
> > > tags <- "ACC,ra,-XY,BPN,-XY,AVG,A+B,FLN,-XY"
> > > chipType <- "GenomeWideSNP_6"
> > > dsT <- AromaUnitTotalCnBinarySet$byName(dataSet, tags=tags,
> > chipType=chipType)
> > > dfR <- getAverageFile(dsN) # ?
> > > dsTR <- exportTotalCnRatioSet(dsT, ref=dfR) # ?
> > Would the above two steps work? My question is how to go ahead from here
> to
> > do CBS and will sm <- CbsModel(dsTR) work?
>
> Skip the exportTotalCnRatioSet() call, and instead use:
>
> sm <- CbsModel(dsTR, ref=dfR, tags="HapMapRef");
>
> The 'tags' is just to add an informative tag to the output data set.
>
> /Henrik
>
> > Thanks again for your help!
> > Sean
> >
> >
> >
> >
> > On Sun, Jul 28, 2013 at 4:28 PM, Henrik Bengtsson
> > <henrik.bengts...@aroma-project.org> wrote:
> >>
> >> Hi.
> >>
> >> On Fri, Jul 26, 2013 at 8:02 AM, sean nj <njs...@gmail.com> wrote:
> >> > Hi guys,
> >> >
> >> > I have a question regarding how to calculate raw copy numbers using
> >> > common
> >> > reference instead of average of all samples of the study. Basically I
> >> > want
> >> > to use average of HapMap270 samples as reference for all further copy
> >> > number
> >> > calculations.
> >> >
> >> > I have a bunch HapMap270 snp6 cel files and I followed Vignette:
> >> > Estimation
> >> > of total copy numbers using the CRMA v2 method (10K-CytoScanHD) to
> Step
> >> > 5 -
> >> > Calculation of raw copy numbers, and generated ceR and saved it as a
> >> > RData
> >> > file ceR.Rdata.
> >>
> >> It's important to understand that almost all objects in the Aroma
> >> framework are basically "pointers" to external files. For instance,
> >> your 'ceR', which I assume you've got from something like ceR <-
> >> getAverageFile(ces), is referring to the file with pathname
> >> getPathname(ceR). More below...
> >>
> >> >
> >> > My first question is, how to use this data for any future copy number
> >> > analysis? My guess is that instead of calculating the ceR from the
> >> > sample
> >> > set I can just load the ceR.RData file I saved and use it. Right?
> >>
> >> First of all, please note that when do ceR <- getAverageFile(ces) on
> >> the same data set 'ces', the result is already available on file and
> >> it will be quickly found and returned. In other words, it will not
> >> recalcuate the averages again [unless you do ceR <-
> >> getAverageFile(ces, force=TRUE)].
> >>
> >> However, I do understand that you may not want to have to keep a large
> >> 'ces' data set around, when you're only interested in the pooled
> >> average. In that case, I would copy the file containing the "average"
> >> to a new data set. Currently, this is not straightforward in Aroma
> >> (I'll think about something), but you can do the following:
> >>
> >> # Calculate the pooled average
> >> > ceR <- getAverageFile(cesN);
> >>
> >> # Copy this file to plmData/HapMap270,pooled/GenomeWideSNP_6/, e.g.
> >> > filename <- getFilename(ceR);
> >> > filename
> >> [1]
> ".average-intensities-median-mad,d03faaf8b707a97c4e43381b1a5d1ef2.CEL"
> >> > rootPath <- getParent(getPath(cesN), depth=2L);
> >> > dataSet <- "HapMap270,pooled";
> >> > chipType <- getChipType(ceR, fullname=FALSE);
> >> > path <- file.path(rootPath, dataSet, chipType);
> >> > path
> >> [1] "plmData/HapMap270,pooled/GenomeWideSNP_6"
> >> > mkdirs(path);
> >> > copyFile(getPathname(ceR), file.path(path, filename));
> >>
> >> With this done, you can then grab this pooled reference as:
> >>
> >> > library("aroma.affymetrix")
> >> > path <- "plmData/HapMap270,pooled/GenomeWideSNP_6";
> >> > filename <-
> >> >
> ".average-intensities-median-mad,d03faaf8b707a97c4e43381b1a5d1ef2.CEL";
> >> > ceR <- CnChipEffectFile(filename, path=path);
> >>
> >> Note, when you save 'ceR', you are basically saving the reference to
> >> the file. Yes, you can load it later, but make sure not to move it,
> >> otherwise you'll get some type of "file not found" error.
> >>
> >> > saveObject(ceR, "HapMap270,GenomeWideSNP_6,reference.Rdata");
> >>
> >> If already saved, and file not moved, you can then do:
> >>
> >> > library("aroma.affymetrix");
> >> > ceR <- loadObject("HapMap270,GenomeWideSNP_6,reference.Rdata");
> >>
> >> All this is very ad hoc (=non-aroma style), and as I said, I'll see if
> >> I can come up with a cleaner solution for storing and retrieving
> >> pooled averages.
> >>
> >> >
> >> > My second question is, how to go ahead from there to calculate the
> >> > relative
> >> > copy numbers for all unit from all samples? The two examples given in
> >> > the
> >> > Vignette are for one unit from one sample and for a few unit on
> >> > chromosome 2
> >> > for one sample. What is the function to retrieve all units on all
> >> > chromosomes instead of units <- getUnitsOnChromosome(gi, chromosome=2,
> >> > region=c(81,86)*1e6)?
> >>
> >> You can set 'units' to NULL to retrieve all loci, i.e. no need to use
> >> getUnitsOnChromosome(). FYI, units <- NULL will give the same data as
> >> with units <- 1:nbrOfUnits(gi).
> >>
> >> > And what is the function to retrieve all samples
> >> > instead of ce <- getFile(cesN, indexOf(cesN, "NA06985"))?
> >>
> >> Hmm... not clear what you mean. All samples are in 'cesN', and you do
> >> need to iterate over them somehow. Is this what you're looking for?
> >>
> >> for (ii in seq_along(cesN)) {
> >> ce <- getFile(cesN, ii)
> >> ...
> >> }
> >>
> >> Or are you asking how to extract the data from all samples? Then you
> can
> >> do:
> >>
> >> theta <- extractTheta(cesN, units=units)
> >>
> >> but be careful because that loads a lot of data into memory.
> >>
> >> Hope this helps,
> >>
> >> Henrik
> >>
> >> >
> >> > Thanks a lot for the help,
> >> >
> >> > Sean
> >> >
> >> > --
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