[Bioc-devel] New SE or new assay in SE?
Just after I pressed the "Send" button I realized that by returning a
new SE object you probably meant returning an SE object with only the
new assay in it. I would favor the other option i.e. 'doProcess(se)'
adds a new assay to 'se'. I think that's what most workflows based on SE
objects do.
This doesn't mean that you can't provide a lower-level function that
returns the transformed data in a "naked" matrix (i.e. not wrapped
inside an SE). This let's the (more advanced) user decide what they want
to do with it e.g. they can add it to the original SE:
assay(se, "normalized") <- normalized_data
or wrap it in its own new SE:
normalized <- SummarizedExperiment(list(normalized=normalized_data))
H.
On 1/29/20 08:29, Pages, Herve wrote:
On 1/28/20 01:37, Laurent Gatto wrote:
Dear all, Assume we have a SummarizedExperiment object `se` that contains raw count data, and a method `doProcess` that processes the data to produce a matrix of identical dimensions (for example log-transformation, normalisation, imputation, ...). What are the opinions in favour or against the following two options - `doProcess(se)` returns a new SE object - `doProcess(se)` adds a new assay to se
Aren't these are the same?
SE objects are not reference objects i.e. they follow R standard
copy-on-change semantic. This means that they never get modified **in
place** (aka they're not "mutable"). So 'doProcess(se)' will always
return a new object, whatever you do inside the function, that is, even
if the function modifies 'se' internally e.g. with something like:
assay(se, "new_assay") <- new_assay
Note that the assay() setter itself like all setters also produces a new
object. The parser actually replaces the following code
assay(se, "new_assay") <- new_assay
with
se <- `assay<-`(se, "new_assay", value=new_assay)
As you can see the previous `se` is replaced with the new one which
gives the **illusion** of in-place replacement but it's not.
Hope this helps,
H.
If you are interested about the broader context about this question, see https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_waldronlab_MultiAssayExperiment_issues_266&d=DwICAg&c=eRAMFD45gAfqt84VtBcfhQ&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=Of3qgEC1ElS9Ji3Iu2vNk93_Fj3m50sTV2zT0dyAKvA&s=qimtz2YygmTlAiYZOWZJrwPMo6eMKy5E5Rew60452TQ&e= Thank you in advance for your input. Laurent
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Herv? Pag?s Program in Computational Biology Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N, M1-B514 P.O. Box 19024 Seattle, WA 98109-1024 E-mail: hpages at fredhutch.org Phone: (206) 667-5791 Fax: (206) 667-1319