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. 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 <lg...@cam.ac.uk> ha scritto:On 19 February 2013 22:44, Hervé Pagès <hpa...@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. LaurentThanks, H.Best wishes, Laurent _______________________________________________ Bioc-devel@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: hpa...@fhcrc.org Phone: (206) 667-5791 Fax: (206) 667-1319_______________________________________________ Bioc-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/bioc-devel_______________________________________________ Bioc-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/bioc-devel_______________________________________________ Bioc-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/bioc-devel_______________________________________________ Bioc-devel@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: hpa...@fhcrc.org Phone: (206) 667-5791 Fax: (206) 667-1319 _______________________________________________ Bioc-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/bioc-devel
