Option (2) sounds nice. Even if you used (3), I would end up naming most
of my columns by seq_len anyway. I usually don't have very good
candidates for column names for my counting functions; the inputs to the
functions are BAM/other file paths that can get quite long, and I don't
like having spaced-out columns when I look at my assays.
I concede that the example of se[,2] <- se[,1] wasn't the most
realistic; it came about from some unit tests I was using to check
subset replacement behaviour, and it was failing once I threw in column
names.
On 05/12/15 18:35, Morgan, Martin wrote:
The philosophy motivating the check is that names make the relationship between
samples and data explicit, rather than relying on fragile positional
information. With this in mind, I wonder why your upstream work flow does not
include dimnames on the matrix?
That said, the check was introduced in
------------------------------------------------------------------------
r68053 | [email protected] | 2012-07-27 03:35:55 -0400 (Fri, 27 Jul 2012) | 2
lines
SummarizedExperiment uses rowData=GRangesList() as defult
------------------------------------------------------------------------
To the observations you mention below one could also add that the rownames()
can be NULL, so there is an uncomfortable asymmetry.
I could (1) remove the check (but use the DataFrame() constructor in an
admittedly hackish way, not wanting to rely on the internal new() function). I
could also (2) construct row / column names as seq_len(nrow()) /
seq_len(ncol()).
Or (3) the code could be tightened to more closely adhere to the philosophy
above (for instance, I think duplication of columns implied by se[,2] = se[,1]
is worth stop()ing over, and allowing colnames(se) = NULL only enables bad
practice). Likely this would be disruptive.
For what it's worth, we have
library(Biobase)
eset = ExpressionSet(matrix(0, 1, 2))
dimnames(eset)
[[1]]
[1] "1"
[[2]]
[1] "1" "2"
colnames(eset) = NULL
Error in `sampleNames<-`(`*tmp*`, value = NULL) :
'value' length (0) must equal sample number in AssayData (2)
so dimnames are being imposed.
(2) would be my current compromise preference.
Martin
________________________________________
From: Bioc-devel [[email protected]] on behalf of Aaron Lun
[[email protected]]
Sent: Saturday, December 05, 2015 7:36 AM
To: bioc-devel
Subject: Re: [Bioc-devel] do SummarizedExperiments really need colnames?
Hello all,
At the start of the SummarizedExperiment constructor, there's a code
block that throws an error if 'colData' is not specified and the assay
matrices don't have column names.
Is this really necessary? In many cases, I just want to get a matrix
into the SE0 object without having to worry about column names. It
doesn't seem like there's a requirement for this in the SE0 class,
either; it seems happy with 'colnames(se0) <- NULL', and setting
'colData' to a 'DataFrame' with 'NULL' row names doesn't break the
constructor.
The requirement for column names causes issues for some manipulations -
for example:
out <- SummarizedExperiment(matrix(0, 10, 5),
colData=DataFrame(row.names=1:5))
out[,1] <- out[,2]
## Error in `rownames<-`(`*tmp*`, value = c("2", "2", "3", "4", "5")) :
## duplicate rownames not allowed
While this is fair enough, it's a bit annoying if I didn't want or need
the names in the first place.
The error mentioned above precedes the construction of the missing
'colData', so if column names are missing, then a more general way to
construct the 'colData' would to do 'new("DataFrame", nrows=ncol(assays))'.
Cheers,
Aaron
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