[Bioc-devel] New SE or new assay in SE?

[Pages, Herve]

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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>>
> 

-- 
Hervé Pagès

Program in Computational Biology
Division of Public Health Sciences
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