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@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.
>>
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>>
>
> 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
>
>
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>



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*Must not speak all he knows, nor judge all he sees.*
*
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