Submission tidyqpcr - Quantitative PCR analysis in the tidyverse #470
Description
Date accepted: 2022-06-10
Submitting Author Name: Edward Wallace
Submitting Author Github Handle: @ewallace
Other Package Authors Github handles: @DimmestP
Repository: https://github.com/ewallace/tidyqpcr
Version submitted: 0.3.0
Submission type: Standard
Editor: @jooolia
Reviewers: @kelshmo
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
- 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 @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 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.
- I have read the guide for authors and rOpenSci packaging guide.
This package:
- does not violate the Terms of Service of any service it interacts with.
- has a CRAN and OSI accepted license.
- contains a README with instructions for installing the development version.
- includes documentation with examples for all functions, created with roxygen2.
- contains a vignette with examples of its essential functions and uses.
- has a test suite.
- has continuous integration, including reporting of test coverage using services such as Travis CI, Coveralls and/or CodeCov.
Publication options
-
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?
-
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
- I agree to abide by rOpenSci's Code of Conduct during the review process and in maintaining my package should it be accepted.