(inactive) Submission of package cleanse

[martijnvanattekum]

Update the following URL to point to the GitHub repository of the package you wish to submit to Bioconductor

• Repository: https://github.com/martijnvanattekum/cleanse

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[bioc-issue-bot]

Hi @martijnvanattekum

Thanks for submitting your package. We are taking a quick look at it and you will hear back from us soon.

The DESCRIPTION file for this package is:

Package: cleanse
Type: Package
Title: Tidyverse functions for SummarizedExperiment
Version: 0.99.0
Authors@R: person("Martijn", "van Attekum", email = "martijnvanattekum@gmail.com",
        role = c("aut", "cre"),
        comment=c(ORCID="0000-0002-5063-8489"))
Description: cleanse (clean summarized experiment) extends the SummarizedExperiments class to use tidyverse methods such as dplyr's select, filter, and mutate functions.
License: MIT + file LICENSE
Encoding: UTF-8
Imports:
  stringr (>= 1.2),
  readr (>= 1.3),
  magrittr (>= 1.5),
  tibble (>= 3.0),
  tidyr (>= 1.0),
  SummarizedExperiment (>= 1.1),
  S4Vectors (>= 0.30),
  stats (>= 4.0)
Depends:
  dplyr (>= 1.0),
  R (>= 4.3.0)
RoxygenNote: 7.2.3
Suggests:
    knitr
VignetteBuilder: knitr
biocViews: Sequencing, Transcriptomics, GeneExpression
URL: https://github.com/martijnvanattekum/cleanse
BugReports: https://github.com/martijnvanattekum/cleanse/issues

[vjcitn]

Thanks for this submission. Would you please have a look at https://github.com/tidyomics/tidyomicsWorkshopBioc2023 and consider joining the tidygenomics slack channel https://community-bioc.slack.com/archives/CEQD45CHK ... I believe there is a significant relationship between your project and the work developing there.

[martijnvanattekum]

Thank you for your reply. I am familiar with the tidySummarizedExperiment package. The main difference is that it strictly uses tidy (long format) data, whereas cleanse stays closer to the original se dimensions (wide format). Particularly aggregate operations and arithmetic (also contained in cleanse) functions are easier/safer to perform on wide format data. As an example, randomly sampling columns (se %>% sample_slice(col, n=10) in cleanse) is not easy/possible to do in tidySummarizedExperiment. I therefore think my package can be considered an alternative approach compared to tidySummarizedExperiment, and I don't see an immediate solution to integrate both approaches into one package. When published, I could note this difference in the readme, and join the tidyTranscriptomics community to ensure that there is no overlap between our packages.

[bioc-issue-bot]

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[bioc-issue-bot]

Dear Package contributor,

This is the automated single package builder at bioconductor.org.

Your package has been built on the Bioconductor Build System.

Congratulations! The package built without errors or warnings on all platforms.

Please see the build report for more details.

The following are build products from R CMD build on the Bioconductor Build System: Linux (Ubuntu 22.04.2 LTS): cleanse_0.99.0.tar.gz macOS 12.6.5 Monterey: cleanse_0.99.0.tar.gz

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[LiNk-NY]

Hi Martijn, @martijnvanattekum

Thank you for your submission. Please see the review below. Best, Marcel

---

cleanse #3114

• The package does not seem to provide a cohesive central representation and straddles the line between the tidyverse and the S4 SummarizedExperiment class leading to inefficiencies due to multiple data copies.
• Consider depending on tidySummarizedExperiment and / or providing solely the function(s) that convert the data to tidy (wide) format.
• The exported S3 operations are not needed once the data is in the wide format tibble.
• The package should adhere to the tidyverse semantics and avoid using arguments like axis.

DESCRIPTION

• Avoid specifying versions for all packages in Imports, is is not necessary.

NAMESPACE

• I am not sure that providing S3 methods for SummarizedExperiment (as implemented) is the right direction.
• Avoid using %>% and use the native |>

R

• It seems to me like the package should only provide ways to convert a SummarizedExperiment into the tidy data class.
• Once converted, the package's S3 methods are not needed.
• It is less memory efficient to operate with both tidyverse and SummarizedExperiment versions of the data.
• See the tidySummarizedExperiment implementation and consider depending on their interface.
• Remove package startup messages.

[LiNk-NY]

Hi Martijn, @martijnvanattekum Any updates on the response to the review? Otherwise, we will close the issue due to inactivity. Best, Marcel

[bioc-issue-bot]

This issue is being closed because there has been no progress for an extended period of time. You may reopen the issue when you have the time to actively participate in the review / submission process. Please also keep in mind that a package accepted to Bioconductor requires a commitment on your part to ongoing maintenance.

Thank you for your interest in Bioconductor.