GRangesFrame is an interesting idea and I gave it some thoughts.
There is this nice symmetry between GRanges and GRangesFrame:
- GRanges = a naked GRanges + a DataFrame accessible via mcols()
- GRangesFrame = a DataFrame + a naked GRanges accessible via
some accessor (e.g. rowRanges())
So GRanges and GRangesFrame are equivalent in terms of what they
can hold, but different in terms of API: the former has the ranges
API as primary API and the DataFrame API on its mcols() component,
and the latter has the DataFrame API as primary API and the ranges
API on its rowRanges() component. Nice switch!
What does this API switch bring us? A GRangesFrame object is now
an object that fully behaves like a DataFrame and people can also
perform range-based operations on its rowRanges() component.
Here is what I'm afraid is going to happen: people will also want
to be able to perform range-based operations *directly* on
these objects, i.e. without having to call rowRanges() first.
So for example when they do subsetByOverlaps(), subsetting
happens vertically. Also the Hits object returned by findOverlaps()
would contain row indices. Problem with this is that these objects
now start to suffer from the "dual personality syndrome". For
example, it's not clear anymore what their length should be.
Strictly speaking it should be their number of columns (that's
what the length of a DataFrame is), but the ranges API that
we're trying to put on them also makes them feel like vectors
along the vertical dimension so it also feels that their length
should be their number of rows. Same thing with 1D subsetting.
Why does it subset the columns and not the rows? Most people
are now confused.
It's interesting to note that the same thing happens with GRanges
objects, but in the opposite direction: people wish they could
do DataFrame operations directly on them without calling mcols()
first. But in order to preserve the good health of GRanges objects,
we've not done that (except for $, a shortcut for mcols(x)$,
the pressure was just too strong).
H.
On 03/03/2015 04:35 PM, Michael Lawrence wrote:
Should be possible for the annotations to be of any type, as long as they
satisfy a simple contract of NROW() and 2D "[". Then, you could have a
DataFrame, GRanges, or whatever in there. But it would be nice to have a
special class for the container with range information. The contract for
the range annotation would be to have a granges() method.
I agree it would be nice if there was a way with the methods package to
easily assert such contracts. For example, one could define an interface
with a set of generics (and optionally the relevant position in the generic
signature). Then, once all of the methods have been assigned for a
particular class, it is made to inherit from that contract class. There are
lots of gotchas though. Not sure how useful it would be in practice.
On Tue, Mar 3, 2015 at 4:07 PM, Peter Haverty <haverty.pe...@gene.com>
wrote:
There are some nice similarities in these new imaginary types. A
"GRangesFrame" is a list of dimensionally identical things (columns) and
some row meta-data (the GRanges). The SE-like object is similarly a list
of dimensionally like things (matrices, RleDataFrames, BigMatrix objects,
HDF5-backed things) with some row meta-data (a DataFrame or GRangesFrame).
Elegant? Maybe they would actually be relatives in the class tree.
I wonder if this kind of thing would be easier if we had Java-style
Interfaces or duck-typing. The "x" slot of "y" holds something that
implements this set of methods ...
Oh, and kinda apropos, the genoset class will probably go away or become
an extension to this new SE-like thing. The extra stuff that comes along
with genoset will still be available.
Pete
____________________
Peter M. Haverty, Ph.D.
Genentech, Inc.
phave...@gene.com
On Tue, Mar 3, 2015 at 3:42 PM, Tim Triche, Jr. <tim.tri...@gmail.com>
wrote:
This.
It would be damned near perfect as a return value for assays coming out of
an object that held several such assays at several time points in a
population, where there are both assay-wise and covariate-wise "holes"
that
could nonetheless be usefully imputed across assays.
Statistics is the grammar of science.
Karl Pearson <http://en.wikipedia.org/wiki/The_Grammar_of_Science>
On Tue, Mar 3, 2015 at 3:25 PM, Peter Haverty <haverty.pe...@gene.com>
wrote:
I still think GRanges should be a subclass of DataFrame,
which would make this easy, but I don't seem to be winning that
argument.
Just impossible. As Michael mentioned back in November, they have
conflicting APIs.
Maybe a new "GRangesFrame" that is a DataFrame and holds a GRanges
(without mcols) as an index?
[[alternative HTML version deleted]]
_______________________________________________
Bioc-devel@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/bioc-devel
[[alternative HTML version deleted]]
_______________________________________________
Bioc-devel@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/bioc-devel
[[alternative HTML version deleted]]
_______________________________________________
Bioc-devel@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/bioc-devel
--
Hervé Pagès
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: hpa...@fredhutch.org
Phone: (206) 667-5791
Fax: (206) 667-1319
_______________________________________________
Bioc-devel@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/bioc-devel
