[Bioc-devel] mapping between original and reduced ranges
Would such a solution also allow to keep the original elementMetadata in the respective list representation? I assume that creates about the same overhead as keeping the index? Florian Hahne Novartis Institute For Biomedical Research Translational Sciences / Preclinical Safety / PCS Informatics Expert Data Integration and Modeling Bioinformatics CHBS, WKL-135.2.26 Novartis Institute For Biomedical Research, Werk Klybeck Klybeckstrasse 141 CH-4057 Basel Switzerland Phone: +41 61 6967127 Email : florian.hahne at novartis.com
On 3/15/12 11:58 PM, "Michael Lawrence" <lawrence.michael at gene.com> wrote:
I would be in favor of either the attribute or metadata solution. I could see having an IntegerList element in the element metadata that indicates the original ranges that were reduced into the returned range, or a Hits object in the top-level metadata. A plus and minus of the metadata approach is that it is more familiar to the users than hiding stuff in attributes, which is pretty low-level. However, using the metadata will increase the probabilty of "getting in the way". The user does need to explicitly request it though. Michael On Thu, Mar 15, 2012 at 3:26 PM, Herv? Pag?s <hpages at fhcrc.org> wrote:
On 03/15/2012 02:40 PM, Kasper Daniel Hansen wrote:
I'll vote against the attribute solution and for a solution where the type of return object gets changed, for example into a list.
Thanks for voting!
Problem with this is how you handle 'with.mapping=TRUE' when the input
is GRangesList. Do you return
(1) a list of the same length as the input 'x', where the i-th
top-level element is itself the 2-element list returned
by reduce(x[[i]], with.mapping=TRUE)
(2) or a 2-element list where 1 element is the reduced GRangesList
and the other element is an IntegerList representing the
list of mappings?
(1) would be very inefficient because the returned object would need
to be populated with hundreds of thousands of S4 instances.
(2) disrupts too much how reduce() is expected to behave on a
GRangesList object i.e. it's expected to operate in a "vectorized"
fashion, that is, each top-level element in the input is reduced
independently of the others and all the results are stored in a
list-like object of the *same length* as the input. So we have nice
properties like
reduce(x, ...)[[i]] is identical to reduce(x[[i]], ...)
Here that would not be the case anymore :-/
More generally speaking, I would not give up on the "endomorphism"
nature of reduce() so easily. It gives us good things like for
example its behaviour on a GRangesList object can be explained
as easily as with
endoapply(x, reduce, ....)
*whatever* arguments/parameters/toggles are passed to it. This
makes the documentation *much* easier to write and also it makes
writing unit test much easier.
So if we really want to go for the list solution, I would suggest
that this is done outside reduce() e.g. in reduceAndMap() or
something like that.
Cheers,
H.
Kasper 2012/3/15 Herv? Pag?s<hpages at fhcrc.org>:
On 03/15/2012 12:45 PM, Cook, Malcolm wrote:
Hi Herve, I've not used attributes to return values before. I guess it would work, and I won't object further if you do it this way, but, since you asked Again, it "feels wrong" in violating functional I suspect there may be issues with memory management. When does the attribute get gc-ed? When the object does? If so, then, retaining the attribute in memory when not needed _could_ be a burden, no? Back in my lisp days, this is when I would use `values` and `multiple-value-bind` (and friends) when I wanted a function to (optionally) return multiple values. But this is R. Would you consider returning instead a list of values, keyed by `value` and `hits`, but only when with.hits BTW: with.inframe.attrib is documented as 'For internal use'. What does it return in the attr?
AFAIK, it's only supported by the "reduce" methods for IRanges objects. The "inframe" attribute contains an IRanges object of the same length as the input. For each range in the input it tells you the position of that range with respect to the "frame" i.e. the space obtained by pasting together the ranges in the reduce object:
> ir
IRanges of length 5
start end width
[1] 24 28 5
[2] 27 31 5
[3] 1 5 5
[4] 6 10 5
[5] 12 16 5
> ir2<- reduce(ir, with.inframe.attrib=TRUE) > ir2
IRanges of length 3
start end width
[1] 1 10 10
[2] 12 16 5
[3] 24 31 8
> attr(ir2, "inframe")
IRanges of length 5
start end width
[1] 16 20 5
[2] 19 23 5
[3] 1 5 5
[4] 6 10 5
[5] 11 15 5
1 1 2 2 3
1...5....0....5....0....5....**0.<- standard coordinate system
ir[1] xxxxx
ir[2] xxxxx
ir[3] xxxxx
ir[4] xxxxx
ir[5] xxxxx
ir2: xxxxxxxxxx xxxxx xxxxxxxx
1...5....1 ....1 ....2...<- "frame" coordinate system
0 5 0
I'll document this.
H.
Thanks for listening! ~Malcolm -----Original Message-----
From: bioc-devel-bounces at r-project.**org<bioc-devel-bounces at r-project.org>[ mailto: bioc-devel-bounces at r- project.org] On Behalf Of Herv? Pag?s Sent: Thursday, March 15, 2012 1:55 PM To: Kasper Daniel Hansen Cc: bioc-devel at r-project.org Subject: Re: [Bioc-devel] mapping between original and reduced ranges Hi reducers, I agree it "feels wrong" to use findOverlaps() to extract the mapping from original to reduced ranges. Even if it can be computed very easily with: findOverlaps(gr, reduce(gr), select="first") (Note that using 'queryHits(findOverlaps(**reduce(gr), gr))' only produces the correct result if 'gr' is already sorted by increasing order.) I think it would be easy for reduce() internal code to produce this mapping. The question is: how do we give it back to the user? Is it OK to use an attribute for this? reduce() already uses this for returning some extra information about the reduction:
> ir
IRanges of length 5
start end width
[1] 1 5 5
[2] 6 10 5
[3] 12 16 5
[4] 24 28 5
[5] 27 31 5
> ir2<- reduce(ir, with.inframe.attrib=TRUE) > ir2
IRanges of length 3
start end width
[1] 1 10 10
[2] 12 16 5
[3] 24 31 8
> attr(ir2, "inframe")
IRanges of length 5
start end width
[1] 1 5 5
[2] 6 10 5
[3] 11 15 5
[4] 16 20 5
[5] 19 23 5
We could to the same thing for the mapping from original to reduced
ranges with e.g. an argument called 'with.mapping.attrib'.
Would that work?
Cheers,
H.
On 03/15/2012 05:44 AM, Kasper Daniel Hansen wrote:
So the key question is to what extent keeping track of where the ranges comes from would slow down the reduce operation. I am not familiar enough with the algorithm to know this, but given how fast IRanges is in general, I am not one for guessing on this. I agree with Florian that this is a very typical use case. Kasper On Thu, Mar 15, 2012 at 5:02 AM, Hahne, Florian <florian.hahne at novartis.com> wrote:
Hi all, It is true that this is not terribly slow when you deal with fairly large range objects: foo<- GRanges(seqnames=sample(1:4, 1e6, TRUE), ranges=IRanges(start=as.**integer(runif(min=1, max=1e7, n=1e6)),
width=50))
system.time(bar<- reduce(foo)) user system elapsed 0.918 0.174 1.091 system.time(foobar<- findOverlaps(foo, bar)) user system elapsed 2.051 0.402 2.453 However the whole process does take about 3x the time of just the
reduce
operation, and in my use case I want this to happen interactively, where waiting 3 seconds compared to 1 makes a huge difference... I wouldn't push this high up on the development agenda, but it seems to
be
something that is already 95% existing and could easily be added. But maybe I am wrong... Florian Florian Hahne Novartis Institute For Biomedical Research Translational Sciences / Preclinical Safety / PCS Informatics Expert Data Integration and Modeling Bioinformatics CHBS, WKL-135.2.26 Novartis Institute For Biomedical Research, Werk Klybeck Klybeckstrasse 141 CH-4057 Basel Switzerland Phone: +41 61 6967127 Email : florian.hahne at novartis.com On 3/14/12 9:40 PM, "Kasper Daniel
Hansen"<kasperdanielhansen@**gmail.com <kasperdanielhansen at gmail.com>>
wrote: We have discussed this a couple of times. I routinely uses the
reduce followed by findOverlaps paradigm. As Malcolm says it feels wrong, but from a practical point of view it is pretty fast, so I stopped worrying about it. I only think there is a reason to do this, if it is substantially faster. Kasper On Wed, Mar 14, 2012 at 3:46 PM, Cook, Malcolm<MEC at stowers.org>
wrote:
Chiming in.... on a similar note.... A version of `disjoin` which returns a Hits/RangesMapping additional to the GRanges result would be most useful and probably not require
much
additional effort (assuming `disjoin` computes this internally) Of course, it is easy to live without since I can just perform the findOverlaps myself after the disjoin.... it just "feels wrong" (tm) Ahoy! ~Malcolm -----Original Message-----
From: bioc-devel-bounces at r-project.**org<bioc-devel-bounces at r-project. org>[mailto: bioc-devel-
bounces at r-
project.org] On Behalf Of Hahne, Florian Sent: Wednesday, March 14, 2012 2:22 PM To: bioc-devel at r-project.org Subject: [Bioc-devel] mapping between original and reduced ranges This bounced before, guess the mailing list does not like HTML mails. So one more try: I had the following offline discussion with Michael about how one
could
retain a mapping of the ranges in a GRanges object before and after reduce. He suggested to take it to the list. Is that something that could be added to GenomicRanges/IRanges? Florian I have a slightly tricky application for which I need to reduce a GRanges object, but I would like to be able to process some of the original elementMetadata of the merged ranges later. The only way I was
able to
figure out which of the original ranges correspond to the merged
ranges
was to perform a findOverlaps operation, but of course that is rather costly. Is there a way to get the merge information out of the original reduce call? Here is a brief example: gr<- GRanges(seqnames="chr1",
ranges=IRanges(start=c(1,6,12,**24,27),
width=5), foo=1:5, bar=letters[1:5]) gr2<- reduce(gr, min.gapwidth=1) ind<- queryHits(findOverlaps(gr2, gr)) split(values(gr), ind) Unfortunately, this is the idiom. I could see an improvement where reduce or a similarly named function would return a Hits object (in addition to the actual reduce result) that would indicate the mapping between
the
input and reduced ranges. The RangesMapping structure would be
really
close to what we would need. Michael
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-- Herv? Pag?s Program in Computational Biology Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N, M1-B514 P.O. Box 19024 Seattle, WA 98109-1024 E-mail: hpages at fhcrc.org Phone: (206) 667-5791 Fax: (206) 667-1319
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