Closed realbp closed 2 months ago
Looks like a good fit for an rOpenSci submission. As for the checks, you don't need to necessarily address all the "good practices" notes. You will need to get the main checks (✔️) from the ropensci bot to pass in order to get an editor assigned (which will kick off the full process). Let me know if that doesn't make sense.
I'd recommend adding some details to the Readme. Also, I'm always a big fan of having pkgdown
produce some rendered documentation. I usually recommend usethis::use_pkgdown_github_pages()
to get started.
Thank you for the feedback! I pkgdown is now up and running at http://getwilds.org/cancerprof/.
I also ran pkgcheck() and got all of the checks to pass.
Should I open up a issue for submission to start the peer review process?
Please do, thanks!
Submitting Author Name: Brian Park Submitting Author Github Handle: !--author1-->@realbp<!--end-author1-- Repository: https://github.com/getwilds/cancerprof Submission type: Pre-submission Language: en
Scope
Please indicate which category or categories from our package fit policies or statistical package categories this package falls under. (Please check an appropriate box below):
Data Lifecycle Packages
[ ] data retrieval
[x] 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
Statistical Packages
[ ] Bayesian and Monte Carlo Routines
[ ] Dimensionality Reduction, Clustering, and Unsupervised Learning
[ ] Machine Learning
[ ] Regression and Supervised Learning
[ ] Exploratory Data Analysis (EDA) and Summary Statistics
[ ] Spatial Analyses
[ ] Time Series Analyses
Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:
cancerprof allows users to extract data from State Cancer Profiles for programmable analysis. cancerprof makes accessing the unstructured api from state cancer profiles intuitive and easy.
The target audience for cancerprof is anyone who wants to access data from state cancer profiles to conduct programmable analysis without having to navigate the complex nature of its GUI. Specifically, cancer researchers could use cancerprof to conduct reproducable analysis of cancer crossed references with a variety of topics found within the data from state cancer profiles.
Currently there are not other softwares or packages that extracts the publicly available data from State Cancer Profiles.
Cancerprof does not breach any data privacy laws and complies with the ethics policies of ropensci.
pkgcheck()
and found a lot of "good practice" notes. Am I required to resolve all of these notes for submission or is it okay to ignore these for special cases?