Hi Michael,

On 04/01/2015 07:17 AM, Michael Love wrote:
I'll retract those last two emails about empty GRanges. That's simply:

se <- SummarizedExperiment(assays, colData=colData)
mcols(se) <- myDataFrame

Glad you found a simple way to do what you wanted.

More below...


On Tue, Mar 31, 2015 at 4:40 PM, Michael Love
<michaelisaiahl...@gmail.com> wrote:
Would this code inspired by the release version of GenomicRanges work?
e.g. if I want to add a DataFrame with 10 rows:

names <- letters[1:10]
x <- relist(GRanges(), PartitioningByEnd(integer(10), names=names))
mcols(x) <- DataFrame(foo=1:10)

Then give x to the rowRanges argument of SummarizedExperiment?

On Tue, Mar 31, 2015 at 3:49 PM, Michael Love
<michaelisaiahl...@gmail.com> wrote:
I forgot to ask my other question. I had gone in early March and fixed
my code to eliminate rowData<-, but the argument to SummarizedExperiment
was still called rowData, and a DataFrame could be provided. Then I
didn't check for a few weeks, but the argument for the rowData slot is
now called rowRanges. What's the trick to putting a DataFrame on an
empty GRanges, so I can get the old behavior but now using the rowRanges
argument?

I'm not sure what you meant by "so I can get the old behavior but
now using the rowRanges argument".

Just to clarify: the renaming of rowData to rowRanges is a change
of name only, not a change of behavior. More precisely the new
rowRanges() accessor should behave exactly as the old rowData()
accessor. The same applies to the 'rowRanges' argument of the
SummarizedExperiment() constructor. So whatever you were passing
before to the 'rowData' argument, you should still be able to pass
it to the new 'rowRanges' argument. Please let us know if it's not
the case as this is certainly not intended.

Thanks,
H.


On Tue, Mar 31, 2015 at 3:40 PM, Michael Love
<michaelisaiahl...@gmail.com> wrote:
With GenomicRanges 1.19.48, I'm still having issues with re-naming the
first assay and duplication of memory from my March 9 email. I tried
assayNames<- as well. My use case is if I am given a
SummarizedExperiment where the first element is not named "counts"
(albeit the SE is most likely coming from summarizeOverlaps() and
already named "counts"...).

sessionInfo()
R Under development (unstable) (2015-03-31 r68129)
Platform: x86_64-apple-darwin12.5.0 (64-bit)
Running under: OS X 10.8.5 (Mountain Lion)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats4    parallel  stats     graphics  grDevices datasets  utils
    methods   base

other attached packages:
[1] GenomicRanges_1.19.48 GenomeInfoDb_1.3.16   IRanges_2.1.43
S4Vectors_0.5.22
[5] BiocGenerics_0.13.10  testthat_0.9.1        devtools_1.7.0        knitr_1.9
[9] BiocInstaller_1.17.6

loaded via a namespace (and not attached):
[1] formatR_1.1    XVector_0.7.4  tools_3.3.0    stringr_0.6.2  evaluate_0.5.5

On Mon, Mar 9, 2015 at 1:21 PM, Michael Love
<michaelisaiahl...@gmail.com> wrote:


On Mar 9, 2015 12:36 PM, "Martin Morgan" <mtmor...@fredhutch.org> wrote:

On 03/09/2015 08:07 AM, Michael Love wrote:

Some guidance on how to avoid duplication of the matrix for developers
would be greatly appreciated.


It's unsatisfactory, but using withDimnames=FALSE avoids duplication on 
extraction of assays (but obviously you don't have dimnames on the matrix). Row 
or column subsetting necessarily causes the subsetted assay data to be 
duplicated. There should not be any duplication when rowRanges() or colData() 
are changed without changing their dimension / ordering.


Thanks Martin for checking into the regression.

Sorry, I should have been more specific earlier, I meant more 
guidance/documentation in the man page for SE. I scanned the 'Extension' 
section but didn't find a note on withDimnames for extracting the matrix or 
this example of renaming the assays (it seems like this could easily be 
relevant for other package authors).

A prominent note there might help devs write more memory efficient packages.

The argument section mentions speed but I'd explicitly mention memory given 
that we're often storing big matrices:

"Setting withDimnames=FALSE  increases the speed with which assays are 
extracted."

(its entirely possible the info is there but i missed it)

Best,

Mike


Another example of a trouble point, is that if I am given an SE with
an unnamed assay and I need to give the assay a name, this also can
expand the memory used. I had found a solution (which works with
GenomicRanges 1.18 / current release) with:

names(assays(se, withDimnames=FALSE))[1] <- "foo"

But now I'm looking in devel and this appears to no longer work. The
memory used expands, equivalent to:

names(assays(se))[1] <- "foo"

Here's some code to try this:

m <- matrix(1:1e7,ncol=10,dimnames=list(1:1e6,1:10))
se <- SummarizedExperiment(m)
names(assays(se, withDimnames=FALSE))[1] <- "foo"
names(assays(se))[1] <- "foo"

while running gc() in between steps.


I think this is a regression of some sort, and I'll look into it. Thanks for 
the heads-up.

Martin




On Mon, Mar 9, 2015 at 10:36 AM, Kasper Daniel Hansen
<kasperdanielhan...@gmail.com> wrote:

On Mon, Mar 9, 2015 at 10:30 AM, Vincent Carey <st...@channing.harvard.edu>
wrote:

I am glad you are keeping this discussion alive Kasper.

On Mon, Mar 9, 2015 at 10:06 AM, Kasper Daniel Hansen <
kasperdanielhan...@gmail.com> wrote:

It sounds like the proposed changes are already made.  However (like
others) I am still a bit mystified why this was necessary.  The old
version
did allow for a GRanges inside the DataFrame of the rowData, as far as I
recall.  So I assume this is for efficiency.  But why?  What kind of
data/use cases is this for?

I am happy to hear that SummarizedExperiment is going to be spun out into
its own package.  When that happens, I have some comments, which I'll
include here in anticipation
    1) I now very strongly believe it was a design mistake to not have
colnames on the assays.  The advantage of this choice is that sampleNames
are only stored one place.  The extreme disadvantage is the high
ineffeciency when you want colnames on an extracted assay.


after example(SummarizedExperiment)

colnames(assays(se1)[[1]])

[1] "A" "B" "C" "D" "E" "F"

so this seems to be optional.  But attempts to set rownames will fail
silently

rownames(assays(se1)[[1]]) = as.character(1:200)


rownames(assays(se1)[[1]])


NULL
seems we could issue a warning there



Vince, you need to be careful here.

The assays are stored without colnames (unless something has recently
changed).  The default is to - upon extraction - set the colnames of the
matrix.  This however requires a copy of the entire matrix.  So
essentially, upon extraction, each assay is needlessly duplicated to add
the colnames.  This is what I mean by inefficient. I would prefer to store
the assays with colnames.  This means that changing sampleNames of the
object will be inefficient (as it is for eSets) since it would require a
complete copy of everything.  But I would rather - much rather - copy when
setting sampleNames than copy when extracting an assay.

Best,
Kasper

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