[Bioc-devel] Request to add 'normalize' to BiocGenerics
Robert Gentleman
rgentlem at gmail.com
Wed Feb 20 20:52:27 CET 2013
my 2c worth
On Wed, Feb 20, 2013 at 10:45 AM, Hervé Pagès <hpages at fhcrc.org> wrote:
> Hi,
>
> I agree with Laurent that we can't really play the semantic and concept
> police. It's the responsibility of package authors to decide whether
> it's appropriate or not to call "normalization" that particular
> transformation they're implementing.
>
> However I hope that we all agree on the following rule regarding the
> generics that make it into BiocGenerics:
>
> If foo() is a generic function defined in BiocGenerics, no
> BioC package should redefine the function (either as a generic
> or an ordinary function). It can only define methods for it,
> or move away and use a different name for this functionality.
but really the point of namespaces is that you don't need to do that.
And we really don't want to be the naming police.
The sole advantage of BiocGenerics, I think, is that there is a common
and standard location for a set of generic functions that get used in different
packages. This allows package authors to add methods that specialize the
behavior of a generic function. They have some confidence that the
generic will always exist and hence can plan accordingly. It
hopefully reduces dependencies between packages.
I don't think it should define a set of reserved words, that seems counter
productive.
There are often good reasons why the same name is used for different
concepts (normalize being one of them). And in some cases a single
generic suffices, but in others it will not. Places where a single generic
fall apart are when there are really different argument lists, and
where inheritance (and hence things like NextMethod) are going to get
messed
up if the disparate methods are all linked to a single generic. Generics
are really concepts - and the methods are realizations of those concepts.
Of course, packages that define functions whose names clash with
BiocGenerics will cause problems, and they would generally be best
to avoid that, but really I don't think I would advocate any sort of
prohibition.
>
> Does that sound reasonable? Otherwise that would kind of defeat the
> purpose of having the BiocGenerics package in the 1st place.
>
> To me, having 10 BioC packages defining a normalize() function is far
> from being ideal. I think having it defined in BiocGenerics would
> improve things a little bit. Also one potential positive side effect
> I see is that it would give an opportunity to the authors of those
> 10 packages to reconsider if they still want to ride the normalize()
> poney or not. Maybe some of them won't and they'll pick up another
> name. Not something we can really decide for them...
>
> H.
>
>
>
> On 02/20/2013 09:47 AM, Laurent Gautier wrote:
>>
>> On 2013-02-20 17:32, Schalkwyk, Leonard wrote:
>>>
>>>
>>> Is this not just an indication that normalize is now a poor choice of
>>> a function name?
>>
>>
>> If the package authors called the functions "normalize", this means
>> either:
>> 1- at least some of the package authors have named a function performing
>> an action that is inappropriately described as "normalize"
>> 2- all functions "normalize" do perform an action that can be described
>> with that verb
>>
>> Without more details, I'd vote for 2.
>>
>> (more below)
>>
>>>
>>> LEo
>>>
>>> On 20 Feb 2013, at 16:14, Wolfgang Huber wrote:
>>>
>>>> Hi
>>>>
>>>> is it clear that all these different functions (methods) share
>>>> similar semantics and enough (conceptually) of their interface?
>>
>>
>> Playing the semantic and concept police would come after defining things
>> like ontologies of data processing; I am not sure this should be a
>> priority.
>> I'd see working out a minimal common signature that keeps everyone going
>> with a minimal fuss come first.
>>
>>>>
>>>> Wouldn't the implication be that preemptively every possible string
>>>> of characters should already be defined as a generic function in
>>>> BiocGenerics?
>>
>>
>> No. Otherwise this would probably also mean that R's S4 system should in
>> fact define all possible strings as generics, which by extension would
>> also mean that generic functions do not need to be explicitly declared:
>> since all possible generics would be declared, it is more practical to
>> implicitly assume any given function has already generic declared. S4
>> has notions about implicit generic functions; a starting point is the
>> man page for setGeneric().
>>
>>
>>
>>>>
>>>> Best wishes
>>>> Wolfgang
>>>>
>>>> Il giorno Feb 20, 2013, alle ore 11:04 AM, Laurent Gatto
>>>> <lg390 at cam.ac.uk> ha scritto:
>>>>
>>>>> On 19 February 2013 22:44, Hervé Pagès <hpages at fhcrc.org> wrote:
>>>>>>
>>>>>> Hi Laurent, and maintainers of packages with a normalize() function,
>>>>>>
>>>>>>
>>>>>> On 02/15/2013 04:28 AM, Laurent Gatto wrote:
>>>>>>>
>>>>>>> A quick (and incomplete) manual search using
>>>>>>> http://search.bioconductor.jp/ suggest the following usage of
>>>>>>> normalize:
>>>>>>>
>>>>>>> As a function:
>>>>>>> xps::normalize
>>>>>>> codelink::normalize
>>>>>>> EBImage::normalize
>>>>>>> diffGeneAnalysis::normalize
>>>>>>>
>>>>>>> Defining a generic and methods:
>>>>>>> oligo::normalize
>>>>>>> flowCore::normalize
>>>>>>> MSnbase::normalize
>>>>>>> isobar::normalize
>>>>>>>
>>>>>>> and
>>>>>>>
>>>>>>> several normalize\.[*+] functions
>>>>>>>
>>>>>>> Would it be reasonable to add a normalize generic definition to
>>>>>>> BiocGenerics? The generic definitions in the above packages differ,
>>>>>>> however.
>>>>>>
>>>>>>
>>>>>> Sounds good to me.
>>>>>>
>>>>>> However, since the various normalize() functions have different
>>>>>> signatures, we need to agree on what the signature of the generic
>>>>>> in BiocGenerics should be.
>>>>>>
>>>>>> Here is a summary of the situation:
>>>>>>
>>>>>> ** xps package: normalize() is an ordinary function with the
>>>>>> following arg list:
>>>>>>
>>>>>> normalize(xps.data, filename=character(0), filedir=getwd(),
>>>>>> tmpdir="", update=FALSE, select="all", method="mean",
>>>>>> option="transcript:all", logbase="0", exonlevel="",
>>>>>> refindex=0, refmethod="mean", params=list(0.02, 0),
>>>>>> add.data=TRUE, verbose=TRUE)
>>>>>>
>>>>>> The package also defines normalize.constant(), normalize.lowess(),
>>>>>> normalize.quantiles(), normalize.supsmu(), which are also ordinary
>>>>>> functions (not S3 methods), and have similar but slightly
>>>>>> different arg lists.
>>>>>>
>>>>>> ** codelink package: Ordinary function with the following args:
>>>>>>
>>>>>> normalize(object, method="quantiles", log.it=TRUE,
>>>>>> preserve=FALSE, weights=NULL, verbose=FALSE)
>>>>>>
>>>>>> ** EBImage package: Ordinary function with the following args:
>>>>>>
>>>>>> normalize(x, separate=TRUE, ft=c(0, 1))
>>>>>>
>>>>>> ** diffGeneAnalysis package: Ordinary function with the following
>>>>>> args:
>>>>>>
>>>>>> normalize(rawdata, numSlides, ctrl, expm, ctrlbg=0.30,
>>>>>> expmbg=0.30)
>>>>>>
>>>>>> ** deepSNV package: S4 generic with the following args:
>>>>>>
>>>>>> normalize(test, control, ...)
>>>>>>
>>>>>> ** isobar package: S4 generic with the following args:
>>>>>>
>>>>>> normalize(x, f=median, target="intensity", exclude.protein=NULL,
>>>>>> use.protein=NULL, f.doapply=TRUE, log=TRUE,
>>>>>> channels=NULL, na.rm=FALSE, per.file=TRUE, ...)
>>>>>>
>>>>>> ** affy package: S4 generic with the following args:
>>>>>>
>>>>>> normalize(object, ...)
>>>>>>
>>>>>> ** flowCore package: S4 generic with the following args:
>>>>>>
>>>>>> normalize(data, x, ...)
>>>>>>
>>>>>> ** MSnbase package: S4 generic with the following args:
>>>>>>
>>>>>> normalize(object, method, ...)
>>>>>>
>>>>>> ** oligo package: S4 generic with the following args:
>>>>>>
>>>>>> normalize(object, method=normalizationMethods(),
>>>>>> copy=TRUE, subset=NULL,
>>>>>> target='core', verbose=TRUE, ...)
>>>>>>
>>>>>> So it looks like the greatest common factor is normalize(x, ...).
>>>>>> Not too surprising for a generic that covers such a wide range of
>>>>>> related but slightly different concepts / algorithms.
>>>>>>
>>>>>> One technical difficulty though is that, even though almost all these
>>>>>> functions seem to take an S4 object as their 1st arg, some of them
>>>>>> don't:
>>>>>>
>>>>>> (a) For EBImage::normalize(), 'x' can be an ordinary array in
>>>>>> addition to an Image object.
>>>>>>
>>>>>> (b) For diffGeneAnalysis::normalize(), 'rawdata' is an ordinary
>>>>>> matrix.
>>>>>>
>>>>>> (c) For deepSNV::normalize(), 'test' can be an ordinary matrix
>>>>>> in addition to a deepSNV object.
>>>>>>
>>>>>> (d) For oligo::normalize(), 'object' can be an ordinary matrix
>>>>>> in addition to a FeatureSet object.
>>>>>>
>>>>>> So how can we disambiguate when the first arg is an ordinary matrix?
>>>>>> IMO normalize() should fail in that case i.e. no package should define
>>>>>> methods for ordinary arrays or matrices. Not ideal but better than the
>>>>>> current situation where what is returned depends on which package was
>>>>>> loaded last.
>>>>>>
>>>>>> I could put normalize(x, ...) in BiocGenerics if nobody objects, but
>>>>>> that's all. I don't have time to fix the 10 packages that this change
>>>>>> will affect. However, I'd rather wait the beginning of the Bioc 2.13
>>>>>> devel cycle (April) for such a change. For some packages like
>>>>>> diffGeneAnalysis (which doesn't use S4 at all), that will probably
>>>>>> require a significant amount of changes since it will need to pass
>>>>>> the data to normalize in an S4 container instead of an ordinary
>>>>>> matrix.
>>>>>>
>>>>>> Comments and suggestions are welcome.
>>>>>
>>>>> Fine by me.
>>>>>
>>>>> Laurent
>>>>>
>>>>>> Thanks,
>>>>>> H.
>>>>>>
>>>>>>> Best wishes,
>>>>>>>
>>>>>>> Laurent
>>>>>>>
>>>>>>> _______________________________________________
>>>>>>> Bioc-devel at r-project.org mailing list
>>>>>>> https://stat.ethz.ch/mailman/listinfo/bioc-devel
>>>>>>>
>>>>>> --
>>>>>> Hervé Pagès
>>>>>>
>>>>>> 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 fhcrc.org
>>>>>> Phone: (206) 667-5791
>>>>>> Fax: (206) 667-1319
>>>>>
>>>>> _______________________________________________
>>>>> Bioc-devel at r-project.org mailing list
>>>>> https://stat.ethz.ch/mailman/listinfo/bioc-devel
>>>>
>>>> _______________________________________________
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>>>>
>>> _______________________________________________
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>>
>>
>> _______________________________________________
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>
>
> --
> Hervé Pagès
>
> 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 fhcrc.org
> Phone: (206) 667-5791
> Fax: (206) 667-1319
>
> _______________________________________________
> Bioc-devel at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/bioc-devel
--
Robert Gentleman
rgentlem at gmail.com
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