I agree that the profile or metagene plot is useful and widely applied. Creating such a plot consists of several steps, including: - quantifying and accumulating signal around sites of interest - normalization - visualization The qProfile() function in QuasR was designed to do the quantification/accumulation, which is not straightforward to implement efficiently and could use a lot of memory. This leaves it to the user to choose an appropriate approach for the normalization (if at all necessary) and gives full flexibility for plotting. qProfile returns a list of vectors, so normalization and plotting are not very complex (as shown in the example mentioned by Tim, in the QuasR vignette in section 6.1.6 "Create a genomic pro le for a set of regions using qProfile"). I would be interested to know your opinions - are these still too complex, so that a plot method would be of high value? Michael On 13.09.2013 07:21, bach le wrote: > Many thanks. I've checked BSmooth but it seems not to be what I mentioned. > As Tim said, this kind of figures are used quite often to illustrate the > difference between groups of objects. Yet till now it seems that there has > not been any offer from BioC (afa I may know). It would be great if someone > can help to implement it. > Cheers, > > > On Fri, Sep 13, 2013 at 3:56 AM, Tim Triche, Jr. <tim.triche at="" gmail.com="">wrote: > >> Bsmooth/bsseq (and QuasR, as well) are great for manipulating and analyzing >> BSseq data, but there's something in this email that I've never really >> found a great solution for, and that is so-called "profile" or "metagene" >> plots (the latter is a confusing bit of terminology, given that it is >> re-used for linear combinations of gene effects in expression studies). >> >> Suppose you wanted to look at the distribution of H3K4me3 or H3K27me3 >> ChIP-seq density relative to the start of (or exon/intron junctions within, >> or enhancers whose activity was linked to, ...) transcribed vs. silent >> genes across a genome. Suppose you also wanted to look at methylation >> proportions relative to the same positions (again, the idea here is to take >> a bunch of landmarks and plot a summary statistic describing the behavior >> of some measurement relative to those landmarks, across the genome). An >> example of such a plot is on page 23 of the QuasR user's manual. For >> clarity, here's a link: >> >> https://dl.dropboxusercontent.com/u/12962689/profile.png >> >> This seems like something that is so incredibly common it ought to be a >> generic function within BioC somewhere, but I've never found a really easy >> way to do it. If I want to plot a density matrix mat[x,y] for alhl x and >> all y, I can call image(mat) or persp(mat) and that's that. Is there >> something like this within biocGenerics of which I've remained completely >> ignorant, or... ? >> >> If it isn't a generic somewhere, I think I may have to implement one. >> >> >> >> >> On Thu, Sep 12, 2013 at 1:32 AM, Alex Gutteridge <alexg at="" ruggedtextile.com="">>> wrote: >> >>> On 12.09.2013 08:25, Gia [guest] wrote: >>> >>>> Hi, >>>> I would like to ask if anyone experienced with creating figures from >>>> BS-Seq methylation data for end analysis of genes (or any genomic >>>> features), like what was presented in the following link: >>>> http://www.nature.com/ng/**journal/v39/n1/fig_tab/ng1929_**F4.html< >> http://www.nature.com/ng/journal/v39/n1/fig_tab/ng1929_F4.html> >>>> It would be appreciate if you can show how to create this kind of >>>> figures using any Bioconductor packages. >>>> Cheers, >>>> >>>> -- output of sessionInfo(): >>>> >>>> None >>>> >>>> -- >>>> Sent via the guest posting facility at bioconductor.org. >>>> >>>> ______________________________**_________________ >>>> Bioconductor mailing list >>>> Bioconductor at r-project.org >>>> https://stat.ethz.ch/mailman/**listinfo/bioconductor< >> https://stat.ethz.ch/mailman/listinfo/bioconductor> >>>> Search the archives: >>>> http://news.gmane.org/gmane.**science.biology.informatics.**conductor< >> http://news.gmane.org/gmane.science.biology.informatics.conductor> >>>> >>> >>> I've only skimmed through that paper but that figure isn't showing BS-Seq >>> data as far as I can see - it's showing the results of an array / IP >> based >>> approach to methylation quantitation. BSmooth is one of the best packages >>> I've found for manipulating BS-Seq data. If you get your data in there >> you >>> could derive analogous statistics (i.e. methylation levels) pretty >> easily. >>> Then any of the base plotting functions will give you similar graphs. >>> >>> -- >>> Alex Gutteridge >>> >>> >>> ______________________________**_________________ >>> Bioconductor mailing list >>> Bioconductor at r-project.org >>> https://stat.ethz.ch/mailman/**listinfo/bioconductor< >> https://stat.ethz.ch/mailman/listinfo/bioconductor> >>> Search the archives: http://news.gmane.org/gmane.** >>> science.biology.informatics.**conductor< >> http://news.gmane.org/gmane.science.biology.informatics.conductor> >>> >> >> >> >> -- >> *He that would live in peace and at ease, * >> *Must not speak all he knows, nor judge all he sees.* >> * >> * >> Benjamin Franklin, Poor Richard's >> Almanack<http: archive.org="" details="" poorrichardsalma00franrich=""> >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor >> > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor >