[Bioc-devel] Unexpected behaviour with Assays and Vector classes

Hi Herve,

I would have expected GRanges behaviour, where the metadata is affected
by the replacement. For example, with GRanges objects, I often use the
metadata to store statistics or descriptors relevant to each genomic
interval, e.g., peak scores, log-fold changes and so on. If I did a
replacement to change the genomic coordinates, I would expect that the
associated metadata would come along for the ride. The same argument
would be applied to other classes derived from Vector.

I should add that I encountered this problem in the context of doing
subset replacement for metadata. To re-use your IRanges example:

require(IRanges)
ir <- IRanges(11:14, 20, names=letters[1:4])
mcols(ir) <- DataFrame(stuff=1:4)
mcols(ir[1])$stuff <- 2
mcols(ir)$stuff

[1] 1 2 3 4

I would expect that the first entry of "stuff" would now be 2. But
because metadata doesn't get replaced during subset replacement, it
remains at 1. This is problematic, because if I wanted to update a
subset of entries in the metadata, I would use something similar to the
above replacement and expect it to change the existing object.

Cheers,

Aaron

Herv? Pag?s wrote:

Hi Aaron,

On 11/15/2015 10:59 AM, Aaron Lun wrote:

Hello all,

I've encountered some unexpected behaviour with some of the base classes
while developing stuff for genomic interactions. The first issue lies
with the subset replacement in the Vector class. Let's say I make a
derived class "foo" inheriting from Vector, as below:

  > require(S4Vectors)
  > setClass("foo", contains="Vector", slots=c(blah="integer"))
  > setMethod("parallelSlotNames", "foo", function(x) {
  >     c("blah", callNextMethod())
  > })

[1] "parallelSlotNames"

  > setMethod("c", "foo", function(x, ..., recursive=TRUE) {
  >    new.blah <- do.call(c, lapply(list(x, ...), FUN=slot,

name="blah"))

  >    new.mcols <- do.call(rbind, lapply(list(x, ...), FUN=mcols))
  >    new("foo", blah=new.blah, metadata=metadata(x),
  >        elementMetadata=new.mcols)
  > })

[1] "c"

Construction gives what you'd expect:

  > a <- new("foo", blah=1:5, elementMetadata=DataFrame(stuff=1:5))
  > a at blah

[1] 1 2 3 4 5

  > mcols(a)$stuff

[1] 1 2 3 4 5

However, if I try to do subset replacement, I get this:

  > a[1] <- a[2]
  > a at blah

[1] 2 2 3 4 5

  > mcols(a)$stuff

[1] 1 2 3 4 5

So, "blah" is replaced properly, but "elementMetadata" is not. This is
attributable to a line in "replaceROWS" which preserves the mcols of the
original object during replacement (also for "names"). Should this line
be removed to give expected behaviour for the elementMetadata?

For the treatment of the metadata columns we are usually mimicking
how names are treated in base R:

x <- c(a=1, b=2, c=3, d=4)
x[1] <- x[2]
x

a b c d
2 2 3 4

The names are not affected.

IRanges objects are following that model:

library(IRanges)
ir <- IRanges(11:14, 20, names=letters[1:4])
mcols(ir) <- DataFrame(stuff=1:4)
ir

IRanges of length 4
     start end width names
[1]    11  20    10     a
[2]    12  20     9     b
[3]    13  20     8     c
[4]    14  20     7     d

mcols(ir)

DataFrame with 4 rows and 1 column
       stuff
   <integer>
1         1
2         2
3         3
4         4

ir[1] <- ir[2]
ir

IRanges of length 4
     start end width names
[1]    12  20     9     a
[2]    12  20     9     b
[3]    13  20     8     c
[4]    14  20     7     d

mcols(ir)

DataFrame with 4 rows and 1 column
       stuff
   <integer>
1         1
2         2
3         3
4         4

However it seems that GRanges objects are not:

gr <- GRanges("chr1", ir)
gr

GRanges object with 4 ranges and 1 metadata column:
     seqnames    ranges strand |     stuff
        <Rle> <IRanges>  <Rle> | <integer>
   a     chr1  [12, 20]      * |         1
   b     chr1  [12, 20]      * |         2
   c     chr1  [13, 20]      * |         3
   d     chr1  [14, 20]      * |         4
   -------
   seqinfo: 1 sequence from an unspecified genome; no seqlengths

gr[1] <- gr[2]
gr

GRanges object with 4 ranges and 1 metadata column:
     seqnames    ranges strand |     stuff
        <Rle> <IRanges>  <Rle> | <integer>
   a     chr1  [12, 20]      * |         2
   b     chr1  [12, 20]      * |         2
   c     chr1  [13, 20]      * |         3
   d     chr1  [14, 20]      * |         4
   -------
   seqinfo: 1 sequence from an unspecified genome; no seqlengths

So we have an inconsistency within our Vector-based classes.
We need to fix that. It seems that you would have expected the
metadata columns to be altered by [<-. Is this what most people feel?

The other issue is that r/cbind'ing doesn't seem to work properly for
unnamed multi-matrix Assays objects. Consider:

  > require(SummarizedExperiment)
  > whee <- Assays(list(x1=matrix(1, 3, 4), x2=matrix(2, 3, 4)))
  > whee2 <- Assays(list(x1=matrix(3, 3, 4), x2=matrix(4, 3, 4)))
  > rbind(whee, whee2)

Reference class object of class "ShallowSimpleListAssays"
Field "data":
List of length 2
names(2): x1 x2

  >
  > names(whee) <- names(whee2) <- NULL
  > rbind(whee, whee2)

Reference class object of class "ShallowSimpleListAssays"
Field "data":
List of length 1

So, unnaming and rbind'ing results in the loss of a matrix. This is the
same issue I reported for unnamed multi-matrix assays when rbinding
multiple SummarizedExperiment objects; I recall that being resolved by
r/cbind'ing based on position. Should this be done here as well? If not,
perhaps we should force people to name their assays.

Maybe Martin or Val can chime in for this one.

Thanks,
H.

Cheers,

Aaron

  > sessionInfo()

R Under development (unstable) (2015-10-30 r69588)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS release 6.4 (Final)

locale:
   [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
   [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8
   [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8
   [7] LC_PAPER=en_US.UTF-8       LC_NAME=C
   [9] LC_ADDRESS=C               LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

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

other attached packages:
[1] SummarizedExperiment_1.1.2 Biobase_2.31.0
[3] GenomicRanges_1.23.3       GenomeInfoDb_1.7.3
[5] IRanges_2.5.5              S4Vectors_0.9.8
[7] BiocGenerics_0.17.1

loaded via a namespace (and not attached):
[1] zlibbioc_1.17.0 XVector_0.11.0