[Bioc-devel] SummarizedExperiment subset of 4 dimensions

[Wolfgang Huber]

Dear Jesper

this is maybe not the answer you want to hear, but stuffing in 4, 5, … dimensions may not be all that useful, as you can always roll out these higher dimensions into the existing third (or even into the second, the SummarizedExperiment columns). There is Hadley’s concept of “tidy data” (see e.g. http://www.jstatsoft.org/v59/i10 ) — a paper that is really worthwhile to read — which implies that the tidy way forward is to stay with 2 (or maybe 3) dimensions in SummarizedExperiment, and to record the information that you’d otherwise stuff into the higher dimensions in the colData covariates.

Wolfgang

Wolfgang Huber
Principal Investigator, EMBL Senior Scientist
Genome Biology Unit
European Molecular Biology Laboratory (EMBL)
Heidelberg, Germany

T +49-6221-3878823
wolfgang.huber at embl.de
http://www.huber.embl.de





> On 30 Mar 2015, at 12:38, Jesper Gådin <jesper.gadin at gmail.com> wrote:
> 
> Hi!
> 
> The SummarizedExperiment class is an extremely powerful container for
> biological data(thank you!), and all my thinking nowadays is just circling
> around how to stuff it as effectively as possible.
> 
> Have been using 3 dimension for a long time, which has been very
> successful. Now I also have a case for using 4 dimensions. Everything
> seemed to work as expected until I tried to subset my object, see example.
> 
> library(GenomicRanges)
> 
> rowRanges <- GRanges(
>                seqnames="chrx",
>                ranges=IRanges(start=1:3,end=4:6),
>                strand="*"
>                )
> 
> coldata <- DataFrame(row.names=paste("s",1:3, sep=""))
> 
> assays <- SimpleList()
> 
> #two dim
> assays[["dim2"]] <- array(0,dim=c(3,3))
> se <- SummarizedExperiment(assays, rowRanges = rowRanges, colData=coldata)
> se[1]
> #works
> 
> #three dim
> assays[["dim3"]] <- array(0,dim=c(3,3,3))
> se <- SummarizedExperiment(assays, rowRanges = rowRanges, colData=coldata)
> se[1]
> #works
> 
> #four dim
> assays[["dim4"]] <- array(0,dim=c(3,3,3,3))
> se <- SummarizedExperiment(assays, rowRanges = rowRanges, colData=coldata)
> se[1]
> #does not work
> #Error in x[i, , , drop = FALSE] : incorrect number of dimensions
> 
> This is also the case for rbind and cbind. Would it be appropriate to ask
> you to update the SE functions to handle subset, rbind, cbind also for 4
> dimensions? I know the time for next release is very soon, so maybe it is
> better to wait until after April 16. Just let me know your thoughts about
> it.
> 
> Jesper
> 
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> 
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