This is an interesting discussion and I hope it is ok to continue it a
bit. I found the
readme for the ttBulk repo extremely enticing and I am sure many people
will want to
explore this way of working with genomic data. I have only a few moments
to explore
it and did not read the vignette, but it looks to me as if it is mostly
recapitulated in the
README, which is an excellent overview.
One thing I feel is missing is an approach to the following question: I
like the
idea of a pipe-oriented operator for programming steps in genomic workflows.
How do I make one that works the way ttBulk's operators work? Well, I can
have a look at ttBulk:::reduce_dimensions.ttBulk ...
It's involved. Are there patterns there that
are preserved across different operators? Can
they be factored out to improve maintainability?
One other point before I run
It seems to me the operators "require" that certain
fields be defined in their tibble operands.
> names(attributes(counts))
[1] "names" "class" "row.names" "parameters"
> attributes(counts)$names
[1] "sample" "transcript" "Cell type"
[4] "count" "time" "condition"
[7] "batch" "factor_of_interest"
> validObject(counts)
*Error in .classEnv(classDef) : *
* trying to get slot "package" from an object of a basic class ("NULL")
with no slots*
Enter a frame number, or 0 to exit
1: validObject(counts)
2: .classEnv(classDef)
I think you mentioned validity checking in a previous email. This
is a feature of S4 that is not frequently invoked. Of course
validObject will not work on counts, but do you have something similar?
(Not all working S4 objects from Bioc will pass validObject tests, but
they should....)
On Fri, Feb 7, 2020 at 5:26 AM Martin Morgan <mtmorgan.b...@gmail.com>
wrote:
> yes, absolutely. A common pattern might be to implement a generic
>
> setGeneric("foo", function(x, ...) standardGeneric("foo"))
>
> an ‘internal’ function that implements the method on base R data types
>
> .foo <- function(x) {
> stopifnot("'x' must be a matrix" = is.matrix(x))
> t(x)
> }
>
> and methods that act as a facade to the implementation
>
> setMethod("foo", "tbl_df", function(x) {
> x <- as.matrix(x)
> result <- .foo(x)
> as_tibble(result)
> })
>
> setMethod("foo", "SummarizedExperiment", function(x) {
> result <- .foo(assay(x))
> assays(x)[["foo"]] <- result
> x
> })
>
> One would expect the vignette and examples to primarily emphasize the use
> of the interoperable (SummmarizedExperiment) version.
>
> Martin Morgan
>
> From: stefano <mangiolastef...@gmail.com>
> Date: Friday, February 7, 2020 at 12:31 AM
> To: Michael Lawrence <lawrence.mich...@gene.com>
> Cc: Martin Morgan <mtmorgan.b...@gmail.com>, "bioc-devel@r-project.org" <
> bioc-devel@r-project.org>
> Subject: Re: [Bioc-devel] Compatibility of Bioconductor with tidyverse S3
> classes/methods
>
> Would this scenario satisfy " make the package _directly_ compatible with
> standard Bioconductor data structures"
>
> If an input is SummarizedExperiment return SummarizedExperiment, if the
> input is a tbl_df or ttBulk, return ttBulk (?)
>
>
> Best wishes.
> Stefano
>
> Stefano Mangiola | Postdoctoral fellow
> Papenfuss Laboratory
> The Walter Eliza Hall Institute of Medical Research
> +61 (0)466452544
>
>
> Il giorno ven 7 feb 2020 alle ore 16:15 Michael Lawrence <mailto:
> lawrence.mich...@gene.com> ha scritto:
> I would urge you to make the package _directly_ compatible with
> standard Bioconductor data structures; no explicit conversion. But you
> can create wrapper methods (even on an S3 generic) that perform the
> conversion automatically. You'll probably want two separate APIs
> though (in different styles), for one thing automatic conversion is
> obviously not possible for return values.
>
> Michael
>
> On Thu, Feb 6, 2020 at 5:34 PM stefano <mailto:mangiolastef...@gmail.com>
> wrote:
> >
> > Thanks Michael,
> >
> > yes in a sense, ttBulk and SummariseExperiment can be considere as two
> interfaces. Would be fair enough to create a function that convert from one
> to the other, although the default would be ttBulk?
> >
> > > I'm not sure the tidyverse is a great answer to the user interface,
> because it lacks domain semantics
> >
> > Would be fair to say that ttBulk class could be considered a tibble with
> specific semantics? In the sense that it holds information about key column
> names (.sample, .transcript, .abundance, .normalised_abundance, etc..), and
> has a validator (that is triggered at every ttBulk function).
> >
> > I think at the moment, given (i) S3 problem, and (ii) the lack of formal
> foundation on SummaisedExperiment interface (that maybe would require an S4
> technology itself, where SummariseExperiment could be a slot?) my package
> would belong more to CRAN, until those two issues will have been resolved.
> >
> > I imagine there are not many cases where a CRAN package migrated to
> Bioconductor after complying with the ecosystem policies.
> >
> > Thanks a lot.
> >
> > Best wishes.
> >
> > Stefano
> >
> >
> >
> > Stefano Mangiola | Postdoctoral fellow
> >
> > Papenfuss Laboratory
> >
> > The Walter Eliza Hall Institute of Medical Research
> >
> > +61 (0)466452544
> >
> >
> >
> > Il giorno ven 7 feb 2020 alle ore 12:12 Michael Lawrence <mailto:
> lawrence.mich...@gene.com> ha scritto:
> >>
> >> There's a difference between implementing software, where one wants
> >> formal data structures, and providing a convenient user interface.
> >> Software needs to interface with other software, so a package could
> >> provide both types of interfaces, one based on rich (S4) data
> >> structures, another on simpler structures with an API more amenable to
> >> analysis. I'm not sure the tidyverse is a great answer to the user
> >> interface, because it lacks domain semantics. This is still an active
> >> area of research (see Stuart Lee's plyranges, for example). I hope you
> >> can find a reasonable compromise that enables you to integrate ttBulk
> >> into Bioconductor, so that it can take advantage of the synergies the
> >> ecosystem provides.
> >>
> >> PS: There is no simple fix for your example.
> >>
> >> Michael
> >>
> >> On Thu, Feb 6, 2020 at 4:12 PM stefano <mailto:
> mangiolastef...@gmail.com> wrote:
> >> >
> >> > Thanks a lot for your comment Martin and Michael,
> >> >
> >> > Here I reply to Marti's comment. Michael I will try to implement your
> >> > solution!
> >> >
> >> > I think a key point from
> >> >
> https://github.com/Bioconductor/Contributions/issues/1355#issuecomment-580977106
> >> > (that I was under-looking) is
> >> >
> >> > *>> "So to sum up: if you submit a package to Bioconductor, there is
> an
> >> > expectation that your package can work seamlessly with other
> Bioconductor
> >> > packages, and your implementation should support that. The safest and
> >> > easiest way to do that is to use Bioconductor data structures"*
> >> >
> >> > In this case my package would not be suited as I do not use
> pre-existing
> >> > Bioconductor data structures, but instead i see value in using a
> simple
> >> > tibble, for the reasons in part explained in the README
> >> > https://github.com/stemangiola/ttBulk (harvesting the power of
> tidyverse
> >> > and friends for bulk transcriptomic analyses).
> >> >
> >> > *>> "with the minimum standard of being able to accept such objects
> even if
> >> > you do not rely on them internally (though you should)"*
> >> >
> >> > With this I can comply in the sense that I can built converters to
> and from
> >> > SummarizedExperiment (for example).
> >> >
> >> > * >> "If you don't want to do that, then that's a shame, but it would
> >> > suggest that Bioconductor would not be the right place to host this
> >> > package."*
> >> >
> >> > Well said.
> >> >
> >> > In summary, I do not rely on Bioconductor data structure, as I am
> proposing
> >> > another paradigm, but my back end is made of largely Bioconductor
> analysis
> >> > packages that I would like to interface with tidyverse. So
> >> >
> >> > 1) Should I build converters to Bioc. data structures, and force the
> use of
> >> > S3 object (needed to tiidyverse to work), or
> >> > 2) Submit to CRAN
> >> >
> >> > I don't have strong feeling for either, although I think Bioconductor
> would
> >> > be a good fit. Please community give me your honest opinions, I will
> take
> >> > them seriously and proceed.
> >> >
> >> >
> >> >
> >> > Best wishes.
> >> >
> >> > *Stefano *
> >> >
> >> >
> >> >
> >> > Stefano Mangiola | Postdoctoral fellow
> >> >
> >> > Papenfuss Laboratory
> >> >
> >> > The Walter Eliza Hall Institute of Medical Research
> >> >
> >> > +61 (0)466452544
> >> >
> >> >
> >> > Il giorno ven 7 feb 2020 alle ore 10:46 Martin Morgan <
> >> > mailto:mtmorgan.b...@gmail.com> ha scritto:
> >> >
> >> > > The idea isn't to use S4 at any cost, but to 'play well' with the
> >> > > Bioconductor ecosystem, including writing robust and maintainable
> code.
> >> > >
> >> > > This comment
> >> > >
> https://github.com/Bioconductor/Contributions/issues/1355#issuecomment-580977106
> >> > > provides some motivation; there was also an interesting exchange on
> the
> >> > > Bioconductor community slack about this (join at
> >> > > https://bioc-community.herokuapp.com/; discussion starting with
> >> > >
> https://community-bioc.slack.com/archives/C35G93GJH/p1580144746014800).
> >> > > The plyranges package http://bioconductor.org/packages/plyranges
> and
> >> > > recently accepted fluentGenomics workflow
> >> > > https://github.com/Bioconductor/Contributions/issues/1350 provide
> >> > > illustrations.
> >> > >
> >> > > In your domain it's really surprising that your package does not use
> >> > > (Import or Depend on) SummarizedExperiment or GenomicRanges
> packages. From
> >> > > a superficial look at your package, it seems like something like
> >> > > `reduce_dimensions()` could be defined to take & return a
> >> > > SummarizedExperiment and hence benefit from some of the points in
> the
> >> > > github issue comment mentioned above.
> >> > >
> >> > > Certainly there is a useful transition, both 'on the way in' to a
> >> > > SummarizedExperiment, and after leaving the more specialized
> bioinformatic
> >> > > computations to, e.g., display a pairs plot of the reduced
> dimensions,
> >> > > where one might re-shape the data to a tidy format and use 'plain
> old'
> >> > > tibbles; the fluentGenomics workflow might provide some guidance.
> >> > >
> >> > > At the end of the day it would not be surprising for Bioconductor
> packages
> >> > > to make use of tidy concepts and data structures, particularly in
> the
> >> > > vignette, and it would be a mistake for Bioconductor to exclude
> >> > > well-motivated 'tidy' representations.
> >> > >
> >> > > Martin Morgan
> >> > >
> >> > > On 2/6/20, 5:46 PM, "Bioc-devel on behalf of stefano" <
> >> > > mailto:bioc-devel-boun...@r-project.org on behalf of mailto:
> mangiolastef...@gmail.com>
> >> > > wrote:
> >> > >
> >> > > Hello,
> >> > >
> >> > > I have a package (ttBulk) under review. I have been told to
> replace
> >> > > the S3
> >> > > system to S4. My package is based on the class tbl_df and must
> be fully
> >> > > compatible with tidyverse methods (inheritance). After some
> tests and
> >> > > research I understood that tidyverse ecosystem is not
> compatible with
> >> > > S4
> >> > > classes.
> >> > >
> >> > > For example, several methos do not apparently handle S4
> objects based
> >> > > on
> >> > > S3 tbl_df
> >> > >
> >> > > ```library(tidyverse)setOldClass("tbl_df")
> >> > > setClass("test2", contains = "tbl_df")
> >> > > my <- new("test2", tibble(a = 1))
> >> > > my %>% mutate(b = 3)
> >> > >
> >> > > a b
> >> > > 1 1 3
> >> > > ```
> >> > >
> >> > > ```my <- new("test2", tibble(a = rnorm(100), b = 1))
> >> > > my %>% nest(data = -b)
> >> > > Error: `x` must be a vector, not a `test2` object
> >> > > Run `rlang::last_error()` to see where the error occurred.
> >> > > ```
> >> > >
> >> > > Could you please advise whether a tidyverse based package can be
> >> > > hosted on
> >> > > Bioconductor, and if S4 classes are really mandatory? I need to
> >> > > understand
> >> > > if I am forced to submit to CRAN instead (although Bioconductor
> would
> >> > > be a
> >> > > good fit, sice I try to interface transcriptional analysis
> tools to
> >> > > tidy
> >> > > universe)
> >> > >
> >> > >
> >> > > Thanks a lot.
> >> > > Stefano
> >> > >
> >> > > [[alternative HTML version deleted]]
> >> > >
> >> > > _______________________________________________
> >> > > mailto:Bioc-devel@r-project.org mailing list
> >> > > https://stat.ethz.ch/mailman/listinfo/bioc-devel
> >> > >
> >> > >
> >> >
> >> > [[alternative HTML version deleted]]
> >> >
> >> > _______________________________________________
> >> > mailto:Bioc-devel@r-project.org mailing list
> >> > https://stat.ethz.ch/mailman/listinfo/bioc-devel
> >>
> >>
> >>
> >> --
> >> Michael Lawrence
> >> Senior Scientist, Bioinformatics and Computational Biology
> >> Genentech, A Member of the Roche Group
> >> Office +1 (650) 225-7760
> >> mailto:micha...@gene.com
> >>
> >> Join Genentech on LinkedIn | Twitter | Facebook | Instagram | YouTube
>
>
>
> --
> Michael Lawrence
> Senior Scientist, Bioinformatics and Computational Biology
> Genentech, A Member of the Roche Group
> Office +1 (650) 225-7760
> mailto:micha...@gene.com
>
> Join Genentech on LinkedIn | Twitter | Facebook | Instagram | YouTube
> _______________________________________________
> Bioc-devel@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/bioc-devel
>
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