Submission tidyqpcr - Quantitative PCR analysis in the tidyverse

[ewallace]

Date accepted: 2022-06-10 Submitting Author Name: Edward Wallace Submitting Author Github Handle: !--author1-->@ewallace<!--end-author1-- Other Package Authors Github handles: !--author-others-->@DimmestP<!--end-author-others-- Repository: https://github.com/ewallace/tidyqpcr Version submitted: 0.3.0 Submission type: Standard Editor: !--editor-->@jooolia<!--end-editor-- Reviewers: !--reviewers-list-->@kelshmo<!--end-reviewers-list--

Due date for @kelshmo: 2021-11-19 Archive: TBD Version accepted: TBD --- - Paste the full DESCRIPTION file inside a code block below: ``` Package: tidyqpcr Type: Package Title: Quantitative PCR Analysis with the Tidyverse Version: 0.3 Authors@R: c(person("Edward", "Wallace", email = "Edward.Wallace@ed.ac.uk", role = c("aut", "cre")), person("Sam", "Haynes", email = "samuel.haynes10@gmail.com", role = c("ctb"))) Description: This package is for reproducible quantitative PCR (qPCR) analysis using packages from the tidyverse, notably dplyr and ggplot2. It normalizes (by ddCq), summarizes, and plots pre-calculated Cq data, and plots raw amplification and melt curves from Roche LightCycler machines. It does NOT (yet) calculate Cq data from amplification curves. Depends: R (>= 3.1.0), tibble, tidyr Imports: rlang, dplyr, ggplot2, readr, forcats, assertthat, lifecycle Suggests: knitr, rmarkdown, tidyverse, cowplot, testthat VignetteBuilder: knitr License: Apache License 2.0 + file LICENSE LazyData: true RoxygenNote: 7.1.1 Encoding: UTF-8 URL: https://github.com/ewallace/tidyqpcr, https://ewallace.github.io/tidyqpcr/ BugReports: https://github.com/ewallace/tidyqpcr/issues Language: en-GB ``` ## Scope - Please indicate which category or categories from our [package fit policies](https://ropensci.github.io/dev_guide/policies.html#package-categories) this package falls under: (Please check an appropriate box below. If you are unsure, we suggest you make a pre-submission inquiry.): - [ ] data retrieval - [ ] data extraction - [ ] data munging - [ ] data deposition - [ ] workflow automation - [ ] version control - [ ] citation management and bibliometrics - [ ] scientific software wrappers - [x] field and lab reproducibility tools - [ ] database software bindings - [ ] geospatial data - [ ] text analysis - Explain how and why the package falls under these categories (briefly, 1-2 sentences): tidyqpcr is an R package that empowers scientists to conduct reproducible, flexible, and best-practice compliant quantitative polymerase chain reaction (qPCR) analysis. tidyqpcr offers a standardised user interface and structure for qPCR analysis, within the tidyverse paradigm of spreadsheet-like rectangular data frames and generic functions that build up complex analyses in a series of simple steps. - Who is the target audience and what are scientific applications of this package? Any molecular biologist or bioinformatician who needs to design or analyse a qPCR experiment. Quantitative PCR is among the most common techniques in biological and biomedical re- search, used for the quantification of DNA and RNA. Standardised and open-source qPCR analysis pipelines will encourage best-practices in the reporting of qPCR results, improve the evaluation of qPCR experiments and ultimately lead to increased confidence in conclusions based on qPCR data. - Are there other R packages that accomplish the same thing? If so, how does yours differ or meet [our criteria for best-in-category](https://ropensci.github.io/dev_guide/policies.html#overlap)? Some open-source libraries for qPCR analysis are available, notably [qpcR](https://github.com/anspiess/qpcR) (Spiess, 2018) and [pcr](https://github.com/MahShaaban/pcr) (Ahmed & Kim, 2018). qpcR is a feature rich qPCR analysis package relying on an object-oriented approach using S4 classes. pcr is a less extensive qPCR analysis package based on the tidyverse suite of generic data-science tools using the paradigm of tidy data (spreadsheet-like rectangular data frames). However, available packages either assume extensive prior R knowledge, overlook best-practices in qPCR experiments, or lack extensive documentation. There remains a need for a qPCR analysis package that integrates with the user-friendly tidyverse, encourages the use of MIQE best-practice compliant experimental design, and provides detailed example analysis pipelines as R vignettes. - (If applicable) Does your package comply with our [guidance around _Ethics, Data Privacy and Human Subjects Research_](https://devguide.ropensci.org/policies.html#ethics-data-privacy-and-human-subjects-research)? Not applicable. - If you made a pre-submission inquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted. We presented tidyqpcr on the rOpenSci discussion page which [Stefanie Butland and Sean Hughes](https://discuss.ropensci.org/t/tidyqpcr-for-quantitative-pcr-analysis-pre-presubmission-community-enquiry/2056) kindly responded to. In response to @seaaan ’s comments we improved the vignettes, stuck to a consistent function naming convention and added functionality to calculate ddCq. We intend to add further functionality in future versions including: support for absolute quantification, support for multiple targets per well, and enabling the use of the plater package. In email correspondence with Stefanie, we believe Julia Gustavsen would be a perfect editor for our project as they reviewed Sean’s [plater](https://github.com/ropensci/software-review/issues/60) package. As for reviewers, we think someone with experience in conducting assays for RNA/DNA quantification and normalisation would be of benefit because of the emphasis on experimental design best-practices. ## Technical checks Confirm each of the following by checking the box. - [x] I have read the [guide for authors](https://devguide.ropensci.org/guide-for-authors.html) and [rOpenSci packaging guide](https://devguide.ropensci.org/building.html). This package: - [x] does not violate the Terms of Service of any service it interacts with. - [x] has a CRAN and OSI accepted license. - [x] contains a [README with instructions for installing the development version](https://ropensci.github.io/dev_guide/building.html#readme). - [x] includes [documentation with examples for all functions, created with roxygen2](https://ropensci.github.io/dev_guide/building.html#documentation). - [x] contains a vignette with examples of its essential functions and uses. - [x] has a [test suite](https://ropensci.github.io/dev_guide/building.html#testing). - [x] has [continuous integration](https://ropensci.github.io/dev_guide/ci.html), including reporting of test coverage using services such as Travis CI, Coveralls and/or CodeCov. ## Publication options - [x] Do you intend for this package to go on CRAN? - [ ] Do you intend for this package to go on Bioconductor? - [ ] Do you wish to submit an Applications Article about your package to [Methods in Ecology and Evolution](http://besjournals.onlinelibrary.wiley.com/hub/journal/10.1111/(ISSN)2041-210X/)? - [x] Do you wish to submit an Applications Article about your package to Journal of Open Source Software? We have included a paper.md file in the repository as per JOSS instructions to authors. ## Code of conduct - [x] I agree to abide by [rOpenSci's Code of Conduct](https://ropensci.github.io/dev_guide/policies.html#code-of-conduct) during the review process and in maintaining my package should it be accepted.

[jooolia]

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

• Briefly describe any working relationship you have (had) with the package authors.

  • Very patient and very open to useful suggestions from reviewers.

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  • A note:I am the editor for this package, but have also provided a review as one of the reviewers declined to continue with the process.

Documentation

The package includes all the following forms of documentation:

• [X] A statement of need: clearly stating problems the software is designed to solve and its target audience in README
• [X] Installation instructions: for the development version of package and any non-standard dependencies in README
• [X] Vignette(s): demonstrating major functionality that runs successfully locally
• [X] Function Documentation: for all exported functions
• [X] Examples: (that run successfully locally) for all exported functions
• [X] Community guidelines: including contribution guidelines in the README or CONTRIBUTING, and DESCRIPTION with URL, BugReports and Maintainer (which may be autogenerated via Authors@R).

Functionality

• [X] Installation: Installation succeeds as documented.
• [X] Functionality: Any functional claims of the software been confirmed.
• [X] Performance: Any performance claims of the software been confirmed.
• [ ] Automated tests: Unit tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.
  • Tests are present, but are failing so it is currently difficult to assess the full extent of how well the tests are covering the package.
• [X] Packaging guidelines: The package conforms to the rOpenSci packaging guidelines.

Estimated hours spent reviewing: 12

• [X] Should the author(s) deem it appropriate, I agree to be acknowledged as a package reviewer (“rev” role) in the package DESCRIPTION file.

---

Review Comments

Description :

• does {lifecycle} need to be in imports? It comes up as an R CMD check NOTE that it is not used.
• Do tidyr and tiblble need to be in “Depends”, could they instead be in the “Imports”?

Spell check

Selected results found using devtools::spell_check()

• designe README.md:139 - designed
• behavior calibration_vignette.Rmd:171 - elsewhere as UK spelling
• paramters platesetup_vignette.Rmd:306 - parameters
• pcr README.md:115 - PCR could be consistently capitalised here.
• targetss calculate_deltacq_bysampleid.Rd:17 - targets

Comments on specific functions

• calculate_dydx_1() - why _1 ?

• label_plate_rowcol() - I can’t find an example that works without coercefactors=TRUE, so is it necessary as an argument? I found it a bit confusing since in the plate creation you are making the plate row and columns as factors. I also found the warning about the transformation to factors confusing as I thought that I had done something wrong when constructing the plate.

• display_plate(create_blank_plate_1536well()) does not work which I can understand. Is there anything planned or could it just be done by colour after a certain size to show a bit the planning of a plate? Not sure this is useful.

• In the examples in display_plate and display_well_value there are calls to “library(dplyr)”, I think this would be better as dplyr::.

• What about the functions in plot_helpers? Where should they be used? It is not clear to me how they integrate in the package even though I could imagine they would be useful for some of the plots one may want to produce with these data. The code formatting and styling could be improved in this file (plot_helpers.R).

• Overall the naming of functions was very consistent and made it easy to understand the functions.

• Would it be possible to add very brief and basic usage to the Readme? I think that the vignette "Delta Cq 96-well plate qPCR analysis example" is a nice example of a workflow that anyone with qPCR data could use so maybe something basic could be adapted from this vignette?

• The Pkgdown website is not up to date, but that should be taken care of once the package is accepted by rOpenSci.

Overall comments

• Nice use of @family for the plate functions.

• Is there a reason that the data sets have been kept in inst/extdata and not as datasets in data/ ? Just curious. One reason I could see is that you want to keep the original file formats as examples for the users. However the disadvantage is that the loading is slightly less easy for users (but perhaps this is negligible) and the datasets are not documented in an R/data.R file. This is not a request, but just a question for you. :)

• I also found the length of the functions to be very manageable and I think this sets the package up nicely for new additions and any desired improvements in the future.

Thanks for your patience with this process. I think the easiest is that once the addressable comments are completed that you could add a comment to this issue with the different commits used to reply to the different issues (for example something like this).

Thanks, Julia

[ewallace]

Thank you @jooolia! We will work on these in some issue tickets and get back to you as soon as we can.

@kelshmo, may we also acknowledge you as a package reviewer in the DESCRIPTION file?

[kelshmo]

@ewallace absolutely, thank you!

[ewallace]

Dear @jooolia,

We have finished updating tidyqpcr in response to your comments:

• Added missing files to .Rbuildignore and changed references to licence, version and depends in DESCRIPTION https://github.com/ewallace/tidyqpcr/commit/fa29569fcee2769dcfb14526a843aadafdf6f1ba
• made packages explicit in tests https://github.com/ewallace/tidyqpcr/commit/d31933b59542593ddf372b0a12656bc14c95041c
• getting started moved in readme https://github.com/ewallace/tidyqpcr/commit/c05f925b1b8f0b4f2295cea165f646cb9d490a5d
• Added top-level help-file https://github.com/ewallace/tidyqpcr/commit/98f930b7143c2dec68ba2e52e71706103f39b501
• Adds read_qpcr_data.R tests https://github.com/ewallace/tidyqpcr/commit/f5816f1858607b1ec512edff5c56563c4fb52508
• Removes {lifecycle} from description https://github.com/ewallace/tidyqpcr/commit/da45200631965af2b402a1b22bcdf398460d1007
• Address spelling errors https://github.com/ewallace/tidyqpcr/commit/cfe2e7c5c509853b1d10e9788f94a4a20bcec3d6 and 8f354b5743849f3c6f47068b9e1c79cbb91d3cdb
• calculate_dydx_1 to calculate_dydx https://github.com/ewallace/tidyqpcr/commit/45649a114b1878951e5fea036b3d9d1b34c5d359
• changes label_plate_rowcol warnings to notes https://github.com/ewallace/tidyqpcr/commit/ba1eb67493c594f249bdf6c4d8306943f1c7103b
• display_plate_qpcr() to enable display_plate() to be more general https://github.com/ewallace/tidyqpcr/commit/bd482f225bd77a58ab2bb5fd73bb7a8a4a5ec3fd
• improved plot_helpers.R styling https://github.com/ewallace/tidyqpcr/commit/55f4ca5104b2b64394d685a938a9f9f5f32384e6
• Adds basic usage to the Readme https://github.com/ewallace/tidyqpcr/commit/25bed2de902f5a095354699a2253988b76667bf5
• Updates pkgdown website https://github.com/ewallace/tidyqpcr/commit/b88ed9f66e399c56dcc2771f4fb955f923fc7841

We created a new tag tidyqpcr v0.5, for the latest version.

We hope that we have fully addressed all your points, and look forward to your feedback.

Yours, Sam and Edward

[jooolia]

Dear @ewallace, Thanks for all your work and comments. I am having a look, but have been slowed down by devtools::check() exiting with status 1 (no problems with R CMD check after R CMD build). I think it is something on my end, but I would like to understand what is happening. I will get back to you again on Friday. thanks, Julia

[jooolia]

Hi @ewallace ,

Thanks for all the work and for the comment pointing us to your updates. I haven't figured out what was causing me to have a exit status 1 with running "check" from the build window. I will ask about this on the rOpenSci slack. R CMD check and devtools::check() from the console are fine.

Regarding the package I have a few more little comments:

What is the story on the plot_helpers functions? Will these be further developed or incorporated in the future?

URLs:

Not urgent, but can be fixed if desired.

In platesetup_vignette.Rmd

• there is a missing "s" in the Issues address - should be https://github.com/ewallace/tidyqpcr/issues (not issue)
• The cheatsheet https://rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf has been moved to https://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf

In the README.md

• https://www.force11.org/group/fairgroup/fairprinciples has been moved to https://force11.org/info/the-fair-data-principles/

Tests

• In test-calculate_efficiency.R, I think that wrapping the function call on line 29 in suppressWarnings() would help with the interpretation of the tests here. Otherwise you get two warnings, but the warnings are not related to the test results and this could be confusing to the tester.

• label_plate_rowcol() - is not actually tested with a plate with well_col or well_row that are not factors. Do you think it would be important to test this? (This is not facetious or sarcastic comment, just genuinely thinking about it)

Code

dplyr joins:

In most uses of the "joins" in dplyr the "by" is specified according to good practice, however there are a few cases where they are not:

• debaseline() line 47 in amp_melt_curve_functions.R
• less urgent, but if there is time it would be good to fix this in the vignettes where the "by" is generally not specified.

examples:

• (optional) The label_plate_rowcol() test has cases that don't throw warnings, maybe at some point it could be helpful to add to the examples because to clarify how users could construct their plates.

[ewallace]

Hi @jooolia,

Thank you for this thorough check, it has helped a lot and given us more opportunity for improvements. @DimmestP and I have addressed these:

• plot_helpers. Given the minimal use of these functions and that their capabilities are now in the scales package, we removed these in pull request https://github.com/ewallace/tidyqpcr/pull/183
• URLs. Fixed in https://github.com/ewallace/tidyqpcr/pull/184
• Tests. Addressed in https://github.com/ewallace/tidyqpcr/pull/185
• dplyr joins. Addressed in https://github.com/ewallace/tidyqpcr/pull/182

We hope that's everything for the review process? Let us know.

Also we are open to suggestions as to whether it is better to share via CRAN or via Bioconductor. I really don't know.

[jooolia]

@ropensci-review-bot submit review https://github.com/ropensci/software-review/issues/470#issuecomment-1114160848 time 12

[jooolia]

Dear @ewallace and @DimmestP, Thanks for all your hard work. 👍 This looks good to me. Since @kelshmo has already approved I will approve this and we can move forward with the next steps.

Regarding CRAN vs. Bioconductor, my personal opinion is that it depends on your targeted users, dependencies and perhaps future plans for the package. Many rOpenSci packages are on CRAN. Right now I am aware (thanks to @maelle 's help) of two rOpenSci pacakges that are on Bioconductor: https://docs.ropensci.org/genbankr/ and https://github.com/YuLab-SMU/treeio . Both CRAN and Bioconductor have their own "gotchas" as detailed in dev guide sections 1.16 and 1.17 https://devguide.ropensci.org/building.html?q=bioconductor#bioconductor-gotchas

[jooolia]

@ropensci-review-bot approve tidyqpcr

[ropensci-review-bot]

Approved! Thanks @ewallace for submitting and @kelshmo for your reviews! :grin:

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[ewallace]

@ropensci-review-bot finalize transfer of tidyqpcr

[ropensci-review-bot]

Transfer completed. The tidyqpcr team is now owner of the repository and the author has been invited to the team

[ewallace]

Thank you @jooolia.

• [x] Transfer the repo to rOpenSci's "ropensci" GitHub organization under "Settings" in your repo.
• [x] After transfer write a comment @ropensci-review-bot finalize transfer of where is the repo/package name. This will give you admin access back.
• [x] Fix all links to the GitHub repo to point to the repo under the ropensci organization.
• [x] Delete your current code of conduct file if you had one - NA.
• [x] If you already had a pkgdown website and are ok relying only on rOpenSci central docs building and branding,
  • [x] deactivate the automatic deployment you might have set up - NA.
  • [x] remove styling tweaks from your pkgdown config but keep that config file - Don't think we had any?
  • [ ] replace the whole current pkgdown website with a [redirecting page] (https://devguide.ropensci.org/redirect.html) - DO WE NEED TO DO THIS?
  • [x] replace your package docs URL with https://docs.ropensci.org/package_name In addition, in your DESCRIPTION file, include the docs link in the URL field alongside the link to the GitHub repository, e.g.: URL: https://docs.ropensci.org/foobar, https://github.com/ropensci/foobar
• [x] Fix any links in badges for CI and coverage to point to the new repository URL.
• [x] Increment the package version to reflect the changes you made during review. In NEWS.md, add a heading for the new version and one bullet for each user-facing change, and each developer-facing change that you think is relevant.
• [x] We're starting to roll out software metadata files to all rOpenSci packages via the Codemeta initiative, see https://docs.ropensci.org/codemetar/ for how to include it in your package, after installing the package - should be easy as running codemetar::write_codemeta() in the root of your package.
• [ ] You can add this installation method to your package README install.packages("", repos = "https://ropensci.r-universe.dev") thanks to R-universe. DID NOT DO this because I tried to install another ropensci package and dependencies didn't work. I don't know if it would work for ropensci.
• [x] Submit to JOSS, tidyqpcr review page at JOSS
• [x] Fix CRAN gotchas

These are all addressed in a branch pending review...

[ewallace]

@ropensci-review-bot give codecov access to ropensci/tidy

[ropensci-review-bot]

I'm sorry human, I don't understand that. You can see what commands I support by typing:

@ropensci-review-bot help

[mpadge]

@ewallace We're just tring to find out why help isn't working there. Regardless, codecov access should be automatic with your first push to the repo in the ropensci org. I checked there and it's all set up properly. We'll fix the help issue in the meantime. Thanks.

[ewallace]

Thank you @mpadge!

I was sufficiently confused to put a discussion point on adding codecov access to the dev guide and/or making it easier to know who to ask for help https://discuss.ropensci.org/t/staff-admin-team-codecov/2982

(apologies, I deleted the failed @ropensci-review-bot help after deciding it wasn't working)

[maelle]

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[ropensci-review-bot]

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