Taken in the abstract, the tidy data argument is one for consistent data
structures that enable interoperability, which is what we have with
SummarizedExperiment. The long form or tidy data frame is an effective
general representation, but if there is additional structure in your data,
why not
Hi Michael
where would you put the “colData”-style metadata for the 3rd, 4th, … dimensions?
As an (ex-)physicists of course I like arrays, and the more dimensions the
better, but in practical work I’ve consistently been bitten by the rigidity of
such a design choice too early in a process.
One would need a long-form colData that aligns with the array.
But now I realize that's not what Jesper wants to do here, and is not how
SE is currently designed. Jesper is using the third (and now fourth)
dimension to store an additional dimension of information about the same
sample. We already
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
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
