spiro: Manage Data from Cardiopulmonary Exercise Testing #541
Description
Date accepted: 2022-08-17
Submitting Author Name: Simon Nolte
Submitting Author Github Handle: @smnnlt
Repository: https://github.com/smnnlt/spiro
Version submitted: 0.0.5
Submission type: Standard
Editor: @melvidoni
Reviewers: @jameshunterbr, @manuramon
Due date for @manuramon: 2022-07-22
Archive: TBD
Version accepted: TBD
Language: en
- Paste the full DESCRIPTION file inside a code block below:
Package: spiro
Title: Manage Data from Cardiopulmonary Exercise Testing
Version: 0.0.5
Authors@R:
person(given = "Simon",
family = "Nolte",
role = c("aut", "cre"),
email = "s.nolte@dshs-koeln.de",
comment = c(ORCID = "0000-0003-1643-1860"))
Description: Import, process, summarize and visualize raw data from
metabolic carts.
License: MIT + file LICENSE
URL: https://github.com/smnnlt/spiro, https://smnnlt.github.io/spiro/
BugReports: https://github.com/smnnlt/spiro/issues
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.0
Imports:
ggplot2,
xml2,
readxl,
knitr,
cowplot,
digest,
signal
Suggests:
testthat (>= 3.0.0),
rmarkdown,
ggborderline
VignetteBuilder: knitr
Config/testthat/edition: 3
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
- data validation and testing
- 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):
The spiro package allows to read and process data from raw data files of different metabolic carts.
- Who is the target audience and what are scientific applications of this package?
This package is primarily written for researchers in exercise science, who want to make their analysis of cardiopulmonary exercise testing more standardized, reproducible and faster. It may also be used in a commercial context (e.g., training diagnostics business).
- Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?
The whippr package has a different approach to the same problem. Compared to whippr, spiro has a more automated and simpler data workflow (basically one function for reading and processing data, and one function for summarizing or plotting). spiro has several relevant additional features, that whippr does not have: Automated detection and manual generation of exercise test protocols; data summary by load steps; adding and synchronizing external heart rate data; import of raw data file meta data; advanced data filtering methods (e.g., Butterworth filters; moving breath averages); Wasserman 9-Panel-Plots. Compared to whippr, the spiro package does not offer methods for VO2 kinetics analysis and automated outlier removal.
- (If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research?
This package works with cardiopulmonary exercise data, which is per se sensitive health data. Meta data from the original raw data files is read and anonymized by default (with the exception of data on body mass, which is necessary to perform certain calculations of variables). The anonymization can optionally be deactivated by means of a function argument [spiro(anonymize = FALSE)], so that meta data is saved alongside the processed data. This may be helpful in some settings when there is no intent to share the data. Sharing of the resulting data in such situations could potentially reveal personal information, which is why this option is not activated by default.
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This package:
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- 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
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MEE Options
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Code of conduct
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