[Bioc-devel] Compatibility of Bioconductor with tidyverse S3 classes/methods

[stefano]

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 <
mtmorgan.bioc using 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" <
> bioc-devel-bounces using r-project.org on behalf of mangiolastefano using 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
>
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>
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