Draft rOpenSci submission

DimmestP commented 3 years ago

Submitting Author Name: Edward Wallace Submitting Author Github Handle: !--author1-->@ewallace@DimmestP<!--end-author-others-- Repository: https://github.com/ewallace/tidyqpcr Version submitted: 0.3.0 Submission type: Standard Editor: TBD Reviewers: TBD

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 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?

Some open-source libraries for qPCR analysis are available, notably qpcR (Spiess, 2018) and 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? 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 kindly responded to. In response to Sean’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 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 and rOpenSci packaging guide.

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.
[x] includes documentation with examples for all functions, created with roxygen2.
[x] contains a vignette with examples of its essential functions and uses.
[x] has a test suite.
[x] has continuous integration, 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?
[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

Code of conduct

[x] I agree to abide by rOpenSci's Code of Conduct during the review process and in maintaining my package should it be accepted.

DimmestP commented 3 years ago

Once @ewallace has accepted the two pull requests and checked this rOpenSci submission I think we are ready.

ewallace commented 3 years ago

I made a couple of minor edits. Ready to submit now!

I ticked a box for JOSS submission, which seemed odd wasn’t already there???

ewallace commented 3 years ago

Submitted at https://github.com/ropensci/software-review/issues/470

Closing!

ropensci / tidyqpcr